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1. Ackland, Marcus PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_0_j_idt585",{id:"formSmash:items:resultList:0:j_idt585",widgetVar:"widget_formSmash_items_resultList_0_j_idt585",onLabel:"Ackland, Marcus ",offLabel:"Ackland, Marcus ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_0_j_idt588",{id:"formSmash:items:resultList:0:j_idt588",widgetVar:"widget_formSmash_items_resultList_0_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:0:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Wargentin, RobinKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:0:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); How prices of condominiums vary with respect to distance from the city center in 20 major cities in Sweden2014Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_0_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:0:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_0_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This report will examine how condominium prices vary with respect to the distance from the city center in 20 major cities in Sweden. With regression analysis three models are construct-ed for each city to predict the price of a condominium in the city with a known set of variables such as area, monthly fee and distance from city center. The three models each depend on the distance parameter in different ways; linearly, exponentially, and exponentially with a higher degree polynomial as an exponent. The models are then examined statistically between cities to determine if there is any correlation between price function with regards to distance and population size. Results show that prices do decline substantially when distance to city center increases in all observed cities. There is a significant correlation between price function of distance and population size, but the relation is not enough to, by itself, explain the differ-ences between cities.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:0:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 2. Adelstrand, Carl PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_1_j_idt585",{id:"formSmash:items:resultList:1:j_idt585",widgetVar:"widget_formSmash_items_resultList_1_j_idt585",onLabel:"Adelstrand, Carl ",offLabel:"Adelstrand, Carl ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_1_j_idt588",{id:"formSmash:items:resultList:1:j_idt588",widgetVar:"widget_formSmash_items_resultList_1_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:1:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Gavefalk, SofiaKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:1:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); In times of regional geopolitical turmoil – Why do some equity funds performbetter than others?2014Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_1_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:1:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_1_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In times of regional geopolitical turmoil – why do some investment portfolios, equity funds, perform better than others? Is it simply luck, the effects of systematic risk or do factors such as investment styles and managerial skills play a significant part in the performance of a fund?

As financial markets often reflect the macro environment, much of the previous year’s fluctuations of Eastern European stocks can be seen to derive from a number of geopolitical events; from the 2013 summer clashes between the Turkish police and opposing parties to the current issue concerning Russia and Ukraine. Needless to say, these events have affected return on equity in their regions and created a distressed environment for investors and equity fund managers investing in Eastern Europe.

This thesis aims to explore how the aforementioned macroeconomic events impact the market and thus the portfolios of asset managers. The thesis also intends to provide aspects of eventual investment strategies that are more preferable than others under such circumstances, in order to mitigate the subsequent risks.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:1:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 3. Ahlberg, Fredrik PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_2_j_idt585",{id:"formSmash:items:resultList:2:j_idt585",widgetVar:"widget_formSmash_items_resultList_2_j_idt585",onLabel:"Ahlberg, Fredrik ",offLabel:"Ahlberg, Fredrik ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:2:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:2:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Application of the Ordered Lorenz Curve in the Analysis of a Non-Life Insurance Portfolio2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_2_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:2:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_2_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Insurance analysts have a great variety of assessment tools at their disposal in order to ensure a healthy insurance portfolio. To describe the financial income and loss distribution of the insurance portfolio one of the more fundamental mathematical instrument is the Lorenz curve. A measure developed in the early 19th centrury by Max O. Lorenz which intended to describe a population’s income distribution in a macro perspective. By developing further on this method with guidance from the article by Frees, Meyers and Cummings, [5], a link between the Lorenz curve and the insurance portfolio’s risk segment will be investigated.

By constructing an insurance rating function which determine an insurance expected loss, depending on the policyholders characteristics, ordering the premium and loss distributions by its relative loss the intent is to identify profitable blocks along the ordered Lorenz curve. With this insight an analyst can redefine the portfolio structure and highlight the desirable characteristics which define a policyholder. In order to keep up with the competition an insurer has to, in the long run, create a sustainable, profitable portfolio with lowering the risk of occurring greater insurance claims.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:2:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 4. Ahlgren, Marcus PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_3_j_idt585",{id:"formSmash:items:resultList:3:j_idt585",widgetVar:"widget_formSmash_items_resultList_3_j_idt585",onLabel:"Ahlgren, Marcus ",offLabel:"Ahlgren, Marcus ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:3:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:3:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Claims Reserving using Gradient Boosting and Generalized Linear Models2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_3_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:3:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_3_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); One fundamental function of an insurance company revolves around calculating the expected claims costs for which the insurer has to compensate its policyholders for. This is the process of claims reserving which is practised by actuaries using statistical methods. Over the last few decades statistical learning methods have become increasingly popular due to their ability to find complex patterns in any type of data. However, they have not been widely adapted within the insurance sector. In this thesis we evaluate the capability of claims reserving with the method of gradient boosting, a non-parametric statistical learning method that has proven to be successful within multiple other disciplines which has made it very popular. The gradient boosting technique is compared with the generalized linear model(GLM) which is widely used for modelling claims. We compare the models by using a claims data set provided by Länsförsäkringar AB which allows us to train the models and evaluate their performance on data not yet seen by the models. The models were implemented using R. The results show that the GLM has a lower prediction error. Also, the gradient boosting method requires more fine tuning to handle claims data properly while the GLM already possesses certain features that makes it suitable for claims reserving without making as many adjustments in the model implementation. The advantage of capturing complex dependencies in data is not fully utilized in this thesis since we only work with 6 predictor variables. It is more likely that gradient boosting can compete with GLM when predicting more complicated claims.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:3:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 5. Ahlgren, Markus PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_4_j_idt585",{id:"formSmash:items:resultList:4:j_idt585",widgetVar:"widget_formSmash_items_resultList_4_j_idt585",onLabel:"Ahlgren, Markus ",offLabel:"Ahlgren, Markus ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:4:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:4:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Internal Market Risk Modelling for Power Trading Companies2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_4_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:4:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_4_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Since the financial crisis of 2008, the risk awareness has increased in the -financial sector. Companies are regulated with regards to risk exposure. These regulations are driven by the Basel Committee that formulates broad supervisory standards, guidelines and recommends statements of best practice in banking supervision. In these regulations companies are regulated with own funds requirements for market risks.

This thesis constructs an internal model for risk management that, according to the "Capital Requirements Regulation" (CRR) respectively the "Fundamental Review of the Trading Book" (FRTB), computes the regulatory capital requirements for market risks. The capital requirements according to CRR and FRTB are compared to show how the suggested move to an expected shortfall (

*ES*) based model in FRTB will affect the capital requirements. All computations are performed with data that have been provided from a power trading company to make the results fit reality. In the results, when comparing the risk capital requirements according to CRR and FRTB for a power portfolio with only linear assets, it shows that the risk capital is higher using the value-at-risk (*VaR*) based model. This study shows that the changes in risk capital mainly depend on the different methods of calculating the risk capital according to CRR and FRTB respectively and minor on the change of risk measure.PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:4:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 6. Ahlin, Filip PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_5_j_idt585",{id:"formSmash:items:resultList:5:j_idt585",widgetVar:"widget_formSmash_items_resultList_5_j_idt585",onLabel:"Ahlin, Filip ",offLabel:"Ahlin, Filip ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:5:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:5:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Internal model for spread risk under Solvency II2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_5_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:5:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_5_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In May 2009 the European Commission decided on new regulations regarding solvency among insurance firms, the Solvency II Directive. The directive aims to strengthen the connection between the requirement of solvency and risks for insurance firms. The directive partly consists of a market risk module, in which a credit spread risk is a sub category.

In this thesis a model for credit spread risk is implemented. The model is an extended version of the Jarrow, Lando and Turnbull model (A Markov Model for theTerm Structure of Credit Risk Spreads, 1997) as proposed by Dubrana (A Stochastic Model for Credit Spreads under a Risk-Neutral Framework through the use of an Extended Version of the Jarrow, Lando and Turnbull Model, 2011). The implementation includes the calibration of a stochastic credit risk driver as well as a simulation of bond returns with the allowance of credit transitions and defaults.

The modeling will be made with the requirements of the Solvency II Directive in mind. Finally, the result will be compared with the Solvency II standard formula for the spread risk sub-module.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:5:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 7. Ahmadi-Djam, Adrian PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_6_j_idt585",{id:"formSmash:items:resultList:6:j_idt585",widgetVar:"widget_formSmash_items_resultList_6_j_idt585",onLabel:"Ahmadi-Djam, Adrian ",offLabel:"Ahmadi-Djam, Adrian ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_6_j_idt588",{id:"formSmash:items:resultList:6:j_idt588",widgetVar:"widget_formSmash_items_resultList_6_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:6:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Belfrage Nordström, SeanKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:6:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Forecasting Non-Maturing Liabilities2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_6_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:6:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_6_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); With ever increasing regulatory pressure financial institutions are required to carefully monitor their liquidity risk. This Master thesis focuses on asserting the appropriateness of time series models for forecasting deposit volumes by using data from one undisclosed financial institution. Holt-Winters, Stochastic Factor, ARIMA and ARIMAX models are considered with the latter being the one with best out-of-sample performance. The ARIMAX model is appropriate for forecasting deposit volumes on a 3 to 6 month horizon with seasonality accounted for through monthly dummy variables. Explanatory variables such as market volatility and interest rates do improve model accuracy but vastly increases complexity due to the simulations needed for forecasting.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:6:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 8. Ahmed, Ilyas PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_7_j_idt585",{id:"formSmash:items:resultList:7:j_idt585",widgetVar:"widget_formSmash_items_resultList_7_j_idt585",onLabel:"Ahmed, Ilyas ",offLabel:"Ahmed, Ilyas ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:7:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:7:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Importance Sampling for Least-Square Monte Carlo Methods2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_7_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:7:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_7_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Pricing American style options is challenging due to early exercise opportunities. The conditional expectation in the Snell envelope, known as the continuation value is approximated by basis functions in the Least-Square Monte Carlo-algorithm, giving robust estimation for the options price. By change of measure in the underlying Geometric Brownain motion using Importance Sampling, the variance of the option price can be reduced up to 9 times. Finding the optimal estimator that gives the minimal variance requires careful consideration on the reference price without adding bias in the estimator. A stochastic algorithm is used to find the optimal drift that minimizes the second moment in the expression of the variance after change of measure. The usage of Importance Sampling shows significant variance reduction in comparison with the standard Least-Square Monte Carlo. However, Importance Sampling method may be a better alternative for more complex instruments with early exercise opportunity.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:7:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 9. Aho, Yousef PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_8_j_idt585",{id:"formSmash:items:resultList:8:j_idt585",widgetVar:"widget_formSmash_items_resultList_8_j_idt585",onLabel:"Aho, Yousef ",offLabel:"Aho, Yousef ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_8_j_idt588",{id:"formSmash:items:resultList:8:j_idt588",widgetVar:"widget_formSmash_items_resultList_8_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:8:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Persson, JohannesKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:8:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Factors Affecting the Conversion Rate in the Flight Comparison Industry: A Logistic Regression Approach2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_8_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:8:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_8_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Using logistic regression, we aim to construct a model to examine the factors that are most influential in affecting user behavior on the flight comparison site flygresor.se. The factors examined were number of adults, number of children, number of stops on the inbound trip, number of stops on the outbound trip, number of days between the search date and the departure date and number of search results displayed for the user. The data sample, collected during a one-week period, was taken from Flygresor and consisted of trips to or from Sweden, made within Europe, excluding Nordic countries, and made more than six days before departure. To find the variables which best explain the user behavior, variable selection methods were used along with hypothesis testing. Also, multicollinearity analysis and residual analysis were performed to evaluate the final model. The result showed that the factor number of children had no significant impact on the conversion rate, while the remaining factors had a high impact. The final model has a high predictive ability on the user's propensity to select a certain flight.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:8:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 10. Alam, Amit PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_9_j_idt585",{id:"formSmash:items:resultList:9:j_idt585",widgetVar:"widget_formSmash_items_resultList_9_j_idt585",onLabel:"Alam, Amit ",offLabel:"Alam, Amit ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_9_j_idt588",{id:"formSmash:items:resultList:9:j_idt588",widgetVar:"widget_formSmash_items_resultList_9_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:9:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Inas, YakubKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:9:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Analys av reporäntans påverkan på prissättningen av bostäder: Slår reporänteförändringar lika mycket på bostäder av olika storlek?2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_9_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:9:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_9_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The aim of this study is to investigate whether changes of the repo rate has diverse effects on apartments of different sizes, targeting specific areas in Stockholm. A conclusion, that the effect of the repo rate differs for apartments of different sizes, was made based on regression analysis and hypothesis testing. The housing market is characterized by vast shifts and the repo rate has reached a historical low-point of -0.25 per cent. It is reflected upon how the central bank’s steering interest rate actually impacts the prices on the housing market and whether it has distinct effects on apartments of different sizes. Apartments sold between years 2005-2015 have been analyzed where the gravity of the repo rate has been taken into consideration and if its significance varies amongst apartments of different sizes. Important parameters concerning apartment prices have been utilized in the constructed model.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:9:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 11. Alenlov, Johan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_10_j_idt585",{id:"formSmash:items:resultList:10:j_idt585",widgetVar:"widget_formSmash_items_resultList_10_j_idt585",onLabel:"Alenlov, Johan ",offLabel:"Alenlov, Johan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_10_j_idt588",{id:"formSmash:items:resultList:10:j_idt588",widgetVar:"widget_formSmash_items_resultList_10_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Uppsala Univ, Dept Informat Technol, S-75236 Uppsala, Sweden..PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:10:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Olsson, JimmyKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:10:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models2019In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, no 21, p. 5571-5582Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_10_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:10:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_10_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We present a novel algorithm, an adaptive-lag smoother, approximating efficiently, in an online fashion, sequences of expectations under the marginal smoothing distributions in general state-space models. The algorithm evolves recursively a bank of estimators, one for each marginal, in resemblance with the so-called particle-based, rapid incremental smoother (PaRIS). Each estimator is propagated until a stopping criterion, measuring the fluctuations of the estimates, is met. The presented algorithm is furnished with theoretical results describing its asymptotic limit and memory usage.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:10:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 12. Alger, Ingela et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_11_j_idt588",{id:"formSmash:items:resultList:11:j_idt588",widgetVar:"widget_formSmash_items_resultList_11_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:11:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Weibull, Jörgen W.KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics. Toulouse Sch Econ, France.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:11:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Evolution and Kantian morality2016In: Games and Economic Behavior, ISSN 0899-8256, E-ISSN 1090-2473, Vol. 98, p. 56-67Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_11_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:11:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_11_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); What kind of preferences should one expect evolution to favor? We propose a definition of evolutionary stability of preferences in interactions in groups of arbitrary finite size. Groups are formed under random matching that may be assortative. Individuals' preferences are their private information. The set of potential preferences are all those that can be represented by continuous functions. We show that a certain class of such preferences, that combine self-interest with morality of a Kantian flavor, are evolutionarily stable, and that preferences resulting in other behaviors are evolutionarily unstable. We also establish a connection between evolutionary stability of preferences and a generalized version of Maynard Smith's and Price's (1973) notion of evolutionary stability of strategies.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:11:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 13. Ali, Dana PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_12_j_idt585",{id:"formSmash:items:resultList:12:j_idt585",widgetVar:"widget_formSmash_items_resultList_12_j_idt585",onLabel:"Ali, Dana ",offLabel:"Ali, Dana ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_12_j_idt588",{id:"formSmash:items:resultList:12:j_idt588",widgetVar:"widget_formSmash_items_resultList_12_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:12:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Kap, GoranKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:12:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Statistical Analysis of Computer Network Security2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_12_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:12:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_12_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this thesis it isshown how to measure the annual loss expectancy of computer networks due to therisk of cyber attacks. With the development of metrics for measuring theexploitation difficulty of identified software vulnerabilities, it is possibleto make a measurement of the annual loss expectancy for computer networks usingBayesian networks. To enable the computations, computer net-work vulnerabilitydata in the form of vulnerability model descriptions, vulnerable dataconnectivity relations and intrusion detection system measurements aretransformed into vector based numerical form. This data is then used to generatea probabilistic attack graph which is a Bayesian network of an attack graph.The probabilistic attack graph forms the basis for computing the annualizedloss expectancy of a computer network. Further, it is shown how to compute anoptimized order of vulnerability patching to mitigate the annual lossexpectancy. An example of computation of the annual loss expectancy is providedfor a small invented example network

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:12:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 14. Alic, Almedina PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_13_j_idt585",{id:"formSmash:items:resultList:13:j_idt585",widgetVar:"widget_formSmash_items_resultList_13_j_idt585",onLabel:"Alic, Almedina ",offLabel:"Alic, Almedina ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_13_j_idt588",{id:"formSmash:items:resultList:13:j_idt588",widgetVar:"widget_formSmash_items_resultList_13_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:13:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Emilsson, CarolineKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:13:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Att modellera utfallen i en fotbollsmatch: med multinomial respektive ordinal logistisk regression2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_13_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:13:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_13_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This study examines how well multinomial and ordinal logistic regressions predict the outcome of football games. The two models have been used for comparison, since the multinomial logistic model treats the outcome as nominal while the ordinal model treats the outcome as ordered variables, 1 > X > 2. The outcome of the game is affected by quantitative explanatory variables, based on data from Premier League 2015/2016, which describe the teams form and performance.

The multinomial model has a prediction measure of 53.4 % and the ordinal model has a prediction measure of 43.8 %. Furthermore, most of the explanatory variables have small and unexpected influence. The conclusion is that modeling with solely historical data is a good basis, but can be improved. In future research the number of observations should be increased and the model should be tested on data different from the one used to develop the model. Furthermore, the goal difference could be used as the response variable, to examine if the prediction measure improves.

The mathematical study is completed with an industrial management approach, which consists of an analysis of the betting industry with Porters Five Forces and suggestions of establishment strategies with focus on marketing. Because of the Swedish gambling monopoly, the competition from local operators is limited, but foreign network operators increase their market shares. A new foreign network operator must thus use digital distribution channels to reach the Swedish betting market. The Swedish consumer is price sensitive, why transaction marketing with focus on 4P, above all price, is preferable towards these.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:13:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 15. Al-Khalaf, Adnan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_14_j_idt585",{id:"formSmash:items:resultList:14:j_idt585",widgetVar:"widget_formSmash_items_resultList_14_j_idt585",onLabel:"Al-Khalaf, Adnan ",offLabel:"Al-Khalaf, Adnan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_14_j_idt588",{id:"formSmash:items:resultList:14:j_idt588",widgetVar:"widget_formSmash_items_resultList_14_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:14:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Gustafsson, Steve OskarKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:14:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Valuing Patents with Linear Regression: Identifying value indicators and using a linear regression model to value patents2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_14_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:14:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_14_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis consist of two parts. The first part of the thesis will conduct a multiple regression on a data-set obtained from the Ocean Tomo’s auction results between 2006 to 2008 with the purpose to identify key value indicators and investigate to what extent it is possible to predict the value of a patent. The final regression model consist of the following covariates Average number of citings per year, share of active family members, age of the patent, average invested USD per year, and nine CPC’s as dummy variables. The second part of the thesis will investigate why it is difficult to value a patent and the different factors and changes that have contributed to a growing importance of patent valuation by applying theories from knowledge-based economy and industrial change. This is done by conducting a literature review and interviews.

The results of this thesis states that it is only possible to construct a model that has an explanation degree of 50.21%. The complexity of a patents value derives from uncertainties about future context of the patent and non-quantifiable parameters of the patent. Furthermore we find evidence of a shift from tangible assets to intangible assets in industrial nations which motivates the growing importance of patent valuation.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:14:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 16. Alm, Jonas PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_15_j_idt585",{id:"formSmash:items:resultList:15:j_idt585",widgetVar:"widget_formSmash_items_resultList_15_j_idt585",onLabel:"Alm, Jonas ",offLabel:"Alm, Jonas ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_15_j_idt588",{id:"formSmash:items:resultList:15:j_idt588",widgetVar:"widget_formSmash_items_resultList_15_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Chalmers.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:15:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Lindskog, FilipKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:15:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Foreign-currency interest-rate swaps in asset-liability management for insurers2013In: European Actuarial Journal, ISSN 2190-9733, E-ISSN 2190-9741, Vol. 3, no 1, p. 133-158Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_15_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:15:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_15_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We consider an insurer with purely domestic business whose liabilities towards its policy holders have long durations. The relative shortage of domestic government bonds with long maturities makes the insurer’s net asset value sensitive to fluctuations in the zero rates used for liability valuation. Therefore, in order to increase the duration of the insurer’s assets, it is common practice for insurers to take a position as the fixed-rate receiver in an interest-rate swap. We assume that this is not possible in the domestic currency but in a foreign currency supporting a larger market of interest-rate swaps. Monthly data over 16 years are used as the basis for investigating the risks to the future net asset value of the insurer from using foreign-currency interest-rate swaps as a proxy for domestic ones in asset–liability management. We find that although a suitable position in swaps may reduce the standard deviation of the future net asset value it may significantly increase the exposure to tail risk that has a substantial effect on the estimation of the solvency capital requirements.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:15:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 17. Almerström Przybyl, Simon PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_16_j_idt585",{id:"formSmash:items:resultList:16:j_idt585",widgetVar:"widget_formSmash_items_resultList_16_j_idt585",onLabel:"Almerström Przybyl, Simon ",offLabel:"Almerström Przybyl, Simon ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:16:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:16:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A Trade-based Inference Algorithm for Counterfactual Performance Estimation2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_16_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:16:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_16_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); A methodology for increasing the success rate in debt collection by matching individual call center agents with optimal debtors is developed. This methodology, called the trade algorithm, consists of the following steps. The trade algorithm first identifies groups of debtors for which agent performance varies. Based on these diﬀerences in performance, agents are put into clusters. An optimal call allocation for the clusters is then decided. Two methods to estimate the performance of an optimal call allocation are suggested. These methods are combined with Monte Carlo cross-validation and an alternative time-consistent validation procedure. Tests of significance are applied to the results and the eﬀect size is estimated.

The trade algorithm is applied to a dataset from the credit management services company Intrum and is shown to enhance performance.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:16:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 18. Almgren, Lars PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_17_j_idt585",{id:"formSmash:items:resultList:17:j_idt585",widgetVar:"widget_formSmash_items_resultList_17_j_idt585",onLabel:"Almgren, Lars ",offLabel:"Almgren, Lars ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:17:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:17:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Evaluation of HYDRA - A risk model for hydropower plants2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_17_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:17:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_17_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Vattenfall Hydro AB has more than 50 large scale power plants. In these power plants there are over 130 power generating units. The planning of renewals of these units is important to minimize the risk of having big breakdowns which inflict long downtime. Because all power plants are different Vattenfall Hydro AB started using a self developed risk model in 2003 to improve the comparisons between power plants. Since then the model has been used without larger improvements or validation.

The purpose of this study is to evaluate and analyse how well the risk model has performed and is performing. This thesis is divided into five subsections where analyses are made on the input to the model, adverse events used in the model, the probabilities used in the model, risk forecasts from the model and finally trends for the periods the model has been used. In each subsection different statistical methods are used for the analyses.

From the analyses it is clear that the low number of adverse events in power plants makes the usage of statistical methods for evaluating performance of Vattenfall Hydro AB’s risk model imprecise. Based on the results of this thesis the conclusion is made that if the risk model is to be used in the future it needs further improvements to generate more accurate results.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:17:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 19. Alpsten, Erik PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_18_j_idt585",{id:"formSmash:items:resultList:18:j_idt585",widgetVar:"widget_formSmash_items_resultList_18_j_idt585",onLabel:"Alpsten, Erik ",offLabel:"Alpsten, Erik ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:18:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:18:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Modeling News Data Flows using Multivariate Hawkes Processes2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_18_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:18:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_18_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis presents a multivariate Hawkes process approach to model flows of news data. The data is divided into classes based on the news' content and sentiment levels, such that each class contains a homogeneous type of observations. The arrival times of news in each class are related to a unique element in the multivariate Hawkes process. Given this framework, the massive and complex flow of information is given a more compact representation that describes the excitation connections between news classes, which in turn can be used to better predict the future flow of news data. Such a model has potential applications in areas such as finance and security. This thesis focuses especially on the different bucket sizes used in the discretization of the time scale as well as the differences in results that these imply. The study uses aggregated news data provided by RavenPack and software implementations are written in Python using the TensorFlow package.

For the cases with larger bucket sizes and datasets containing a larger number of observations, the results suggest that the Hawkes models give a better fit to training data than the Poisson model alternatives. The Poisson models tend to give better performance when models trained on historic data are tested on subsequent data flows. Moreover, the connections between news classes are given to vary significantly depending on the underlying datasets. The results indicate that lack of observations in certain news classes lead to over-fitting in the training of the Hawkes models and that the model ought to be extended to take into account the deterministic and periodic behaviors of the news data flows.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:18:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 20. Alpsten, Gustav PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_19_j_idt585",{id:"formSmash:items:resultList:19:j_idt585",widgetVar:"widget_formSmash_items_resultList_19_j_idt585",onLabel:"Alpsten, Gustav ",offLabel:"Alpsten, Gustav ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_19_j_idt588",{id:"formSmash:items:resultList:19:j_idt588",widgetVar:"widget_formSmash_items_resultList_19_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:19:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Samanci, SercanKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:19:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Portfolio Protection Strategies: A study on the protective put and its extensions2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_19_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:19:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_19_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The need among investors to manage volatility has made itself painfully clear over the past century, particularly during sudden crashes and prolonged drawdowns in the global equity markets. This has given rise to a liquid portfolio insurance market in the form of options, as well as attracted the attention of many researchers. Previous literature has, in particular, studied the effectiveness of the widely known protective put strategy, which serially buys a put option to protect a long position in the underlying asset. The results are often uninspiring, pointing towards few, if any, protective benefits with high option premiums as a main concern. This raises the question if there are ways to improve the protective put strategy or if there are any cost-efficient alternatives that provide a relatively be.er protection. This study extends the previous literature by investigating potential improvements and alternatives to the protective put strategy. In particular, three alternative put spread strategies and one collar strategy are constructed. In addition, a modified protective put this introduced to mitigate the path dependency in a rolling protection strategy.

The results show that no option-based protection strategy can dominate the other in all market situations. Although reducing the equity position is generally more effective than buying options, we report that a collar strategy that buys 5% OTM put options and sells 5% OTM call options has an attractive risk-reward profile and protection against drawdowns. We also show that the protective put becomes more effective, both in terms of risk-adjusted return and tail protection, for longer maturities.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:19:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 21. Amundsson, Karl PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_20_j_idt585",{id:"formSmash:items:resultList:20:j_idt585",widgetVar:"widget_formSmash_items_resultList_20_j_idt585",onLabel:"Amundsson, Karl ",offLabel:"Amundsson, Karl ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:20:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:20:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Approximate Bayesian Learning of Partition Directed Acyclic Graphs2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_20_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:20:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_20_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Partition directed acyclic graphs (PDAGs) is a model whereby the conditional probability tables (CPTs) are partitioned into parts with equal probability. In this way, the number of parameters that need to be learned can be significantly reduced so that some problems become more computationally feasible. PDAGs have been shown to be connected to labeled DAGs (LDAGs) and the connection is summarized here. Furthermore, a clustering algorithm is compared to an exact algorithm for determining a PDAG. To evaluate the algorithm, we use it on simulated data where the expected result is known.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:20:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 22. Andersson, Alexandra PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_21_j_idt585",{id:"formSmash:items:resultList:21:j_idt585",widgetVar:"widget_formSmash_items_resultList_21_j_idt585",onLabel:"Andersson, Alexandra ",offLabel:"Andersson, Alexandra ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:21:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:21:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Smart Beta Investering Baserad på Makroekonomiska Indikatorer2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_21_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:21:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_21_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis examines the possibility to find a relationship between the Nasdaq Nordea Smart Beta Indices and a series of macroeconomic indicators. This relationship will be used as a signal-value and implemented in a portfolio consisting of all six smart beta indices. To investigate the impact of the signal-value on the portfolio performance, three portfolio strategies are examined with the equally weighted portfolio as a benchmark. The portfolio weights will be re-evaluated monthly and the portfolios examined are the mean-variance portfolio, the mean-variance portfolio based on the signal-value and the equally weighted portfolio based on the signal-value.

In order to forecast the performance of the portfolio, a multivariate GARCH model with time-varying correlations is fitted to the data and three different error-distributions are considered. The performances of the portfolios are studied both in- and out-of-sample and the analysis is based on the Sharpe ratio.

The results indicate that a mean-variance portfolio based on the relationship with the macroeconomic indicators outperforms the other portfolios for the in-sample period, with respect to the Sharpe ratio. In the out-of-sample period however, none of the portfolio strategies has Sharpe ratios that are statistically different from that of an equally weighted portfolio.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:21:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 23. Andersson, Daniel PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_22_j_idt585",{id:"formSmash:items:resultList:22:j_idt585",widgetVar:"widget_formSmash_items_resultList_22_j_idt585",onLabel:"Andersson, Daniel ",offLabel:"Andersson, Daniel ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:22:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:22:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A mixed relaxed singular maximum principle for linear SDEs with random coefficientsArticle in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_22_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:22:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_22_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We study singular stochastic control of a two dimensional stochastic differential equation, where the first component is linear with random and unbounded coefficients. We derive existence of an optimal relaxed control and necessary conditions for optimality in the form of a mixed relaxed-singular maximum principle in a global form. A motivating example is given in the form of an optimal investment and consumption problem with transaction costs, where we consider a portfolio with a continuum of bonds and where the portfolio weights are modeled as measure-valued processes on the set of times to maturity.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:22:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 24. Andersson, Daniel PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_23_j_idt585",{id:"formSmash:items:resultList:23:j_idt585",widgetVar:"widget_formSmash_items_resultList_23_j_idt585",onLabel:"Andersson, Daniel ",offLabel:"Andersson, Daniel ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:23:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:23:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); The relaxed general maximum principle for singular optimal control of diffusions2009In: Systems & control letters (Print), ISSN 0167-6911, E-ISSN 1872-7956, ISSN 01676911, Vol. 58, no 1, p. 76-82Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_23_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:23:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_23_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this paper we study optimality in stochastic control problems where the state process is a stochastic differential equation (SDE) and the control variable has two components, the first being absolutely continuous and the second singular. A control is defined as a solution to the corresponding martingale problem. To obtain existence of an optimal control Haussmann and Suo [U.G. Haussmann, W. Suo, Singular optimal stochastic controls I: Existence, SIAM J. Control Optim. 33 (3) (1995) 916-936] relaxed the martingale problem by extending the absolutely continuous control to the space of probability measures on the control set. Bahlali et al. [S. Bahlali, B. Djehiche, B. Mezerdi, The relaxed stochastic maximum principle in singular optimal control of diffusions, SIAM J. Control Optim. 46 (2) (2007) 427-444] established a maximum principle for relaxed singular control problems with uncontrolled diffusion coefficient. The main goal of this paper is to extend their results to the case where the control enters the diffusion coefficient. The proof is based on necessary conditions for near optimality of a sequence of ordinary controls which approximate the optimal relaxed control. The necessary conditions for near optimality are obtained by Ekeland's variational principle and the general maximum principle for (strict) singular control problems obtained in Bahlali and Mezerdi [S. Bahlali, B. Mezerdi, A general stochastic maximum principle for singular control problems, Electron J. Probab. 10 (2005) 988-1004. Paper no 30]. © 2008 Elsevier B.V. All rights reserved.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:23:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 25. Andersson, Daniel PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_24_j_idt585",{id:"formSmash:items:resultList:24:j_idt585",widgetVar:"widget_formSmash_items_resultList_24_j_idt585",onLabel:"Andersson, Daniel ",offLabel:"Andersson, Daniel ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_24_j_idt588",{id:"formSmash:items:resultList:24:j_idt588",widgetVar:"widget_formSmash_items_resultList_24_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:24:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Djehiche, BoualemKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:24:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A maximum principle for relaxed stochastic control of linear SDEs with application to bond portfolio optimization2010In: Mathematical Methods of Operations Research, ISSN 1432-2994, E-ISSN 1432-5217, Vol. 72, no 2, p. 273-310Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_24_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:24:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_24_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We study relaxed stochastic control problems where the state equation is a one dimensional linear stochastic differential equation with random and unbounded coefficients. The two main results are existence of an optimal relaxed control and necessary conditions for optimality in the form of a relaxed maximum principle. The main motivation is an optimal bond portfolio problem in a market where there exists a continuum of bonds and the portfolio weights are modeled as measure-valued processes on the set of times to maturity.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:24:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 26. Andersson, Daniel PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_25_j_idt585",{id:"formSmash:items:resultList:25:j_idt585",widgetVar:"widget_formSmash_items_resultList_25_j_idt585",onLabel:"Andersson, Daniel ",offLabel:"Andersson, Daniel ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_25_j_idt588",{id:"formSmash:items:resultList:25:j_idt588",widgetVar:"widget_formSmash_items_resultList_25_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:25:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Djehiche, BoualemKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:25:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A maximum principle for SDEs of mean-field type2011In: Applied mathematics and optimization, ISSN 0095-4616, E-ISSN 1432-0606, Vol. 63, no 3, p. 341-356Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_25_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:25:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_25_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We study the optimal control of a stochastic differential equation (SDE) of mean-field type, where the coefficients are allowed to depend on some functional of the law as well as the state of the process. Moreover the cost functional is also of mean-field type, which makes the control problem time inconsistent in the sense that the Bellman optimality principle does not hold. Under the assumption of a convex action space a maximum principle of local form is derived, specifying the necessary conditions for optimality. These are also shown to be sufficient under additional assumptions. This maximum principle differs from the classical one, where the adjoint equation is a linear backward SDE, since here the adjoint equation turns out to be a linear mean-field backward SDE. As an illustration, we apply the result to the mean-variance portfolio selection problem.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:25:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 27. Andersson, Gabriella PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_26_j_idt585",{id:"formSmash:items:resultList:26:j_idt585",widgetVar:"widget_formSmash_items_resultList_26_j_idt585",onLabel:"Andersson, Gabriella ",offLabel:"Andersson, Gabriella ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_26_j_idt588",{id:"formSmash:items:resultList:26:j_idt588",widgetVar:"widget_formSmash_items_resultList_26_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:26:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Karlsson, LouiseKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:26:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Factors affecting the proportion of smartphone usage at Flygresor.se2017Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_26_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:26:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_26_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Digitization has changed the way people access the internet. Smartphones is soon to be the preferred internet access device leading us into a new generation of e-commerce, namely mobile commerce or m-commerce. The on-going transition, from desktop to smartphone has led to an uprising problem for companies within the area of e-commerce. Visitors coming from a smartphone device tend to not go through with the purchase. With this transition in mind, the thesis aimed to identify the factors that affect the proportion of smartphone visitors on a website, more specifically at the flight comparison site Flygresor.se. The method used was multiple linear regression analysis. To see whether the chosen factors affected the proportion of smartphone transactions or just the proportion of smartphone sessions two regression were performed. One with response variable Sessions and one with response variable Transactions, where Sessions refer to the number of visitors on the website and Transactions refer to the number of visitors moving on to the final booking website. The explanatory variables used were divided into four categories; Marketing, Channels, Season and Other, where the category Other contained the variables Total number of visitors and Amount of MB used per smartphone subscription. The study showed that all categories contained variables with significant impact on both of the response variables. There was only one variable that had different impact on the models, namely the Total number of visitors. The result indicates that smartphone users tend to, in comparison with desktop users, to a less extent continue to the final booking website. Since there were no other variables that only had an impact on Transactions it was assumed that there exist other factors which have a greater impact on smartphone users tendency to finalize a booking.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:26:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 28. Andersson, Joacim PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_27_j_idt585",{id:"formSmash:items:resultList:27:j_idt585",widgetVar:"widget_formSmash_items_resultList_27_j_idt585",onLabel:"Andersson, Joacim ",offLabel:"Andersson, Joacim ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_27_j_idt588",{id:"formSmash:items:resultList:27:j_idt588",widgetVar:"widget_formSmash_items_resultList_27_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:27:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Falk, HenrikKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:27:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Missing Data in Value-at-Risk Analysis: Conditional Imputation in Optimal Portfolios Using Regression2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_27_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:27:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_27_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); A regression-based method is presented in order toregenerate missing data points in stock return time series. The method usesonly complete time series of assets in optimal portfolios, in which the returnsof the underlying tend to correlate inadequately with each other. The studyshows that the method is able to replicate empirical VaR-backtesting resultswhere all data are available, even when up to 90% of the time series in half ofthe assets in the portfolios have been removed.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:27:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 29. Andersson, Johan PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_28_j_idt585",{id:"formSmash:items:resultList:28:j_idt585",widgetVar:"widget_formSmash_items_resultList_28_j_idt585",onLabel:"Andersson, Johan ",offLabel:"Andersson, Johan ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:28:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:28:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Locating Multiple Change-Points Using a Combination of Methods2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_28_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:28:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_28_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The aim of this study is to find a method that is able to locate multiple change-points in a time series with unknown properties. The methods that are investigated are the CUSUM and CUSUM of squares test, the CUSUM test with OLS residuals, the Mann-Whitney test and Quandt’s log likelihood ratio. Since all methods are detecting single change-points, the binary segmentation technique is used to find multiple change-points. The study shows that the CUSUM test with OLS residuals, Mann-Whitney test and Quandt’s log likelihood ratio work well on most samples while the CUSUM and CUSUM of squares are not able to detect the location of the change-points. Furthermore the study shows that the binary segmentation technique works well with all methods and is able to detect multiple change-points in most circumstances. The study also shows that the results can, most of the time, be improved by using a combination of the methods.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:28:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 30. Andersson, Markus PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_29_j_idt585",{id:"formSmash:items:resultList:29:j_idt585",widgetVar:"widget_formSmash_items_resultList_29_j_idt585",onLabel:"Andersson, Markus ",offLabel:"Andersson, Markus ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:29:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:29:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Multivariate Financial Time Series and Volatility Models with Applications to Tactical Asset Allocation2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_29_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:29:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_29_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The financial markets have a complex structure and the modelling techniques have recently been more and more complicated. So for a portfolio manager it is very important to find better and more sophisticated modelling techniques especially after the 2007-2008 banking crisis. The idea in this thesis is to find the connection between the components in macroeconomic environment and portfolios consisting of assets from OMX Stockholm 30 and use these relationships to perform Tactical Asset Allocation (TAA). The more specific aim of the project is to prove that dynamic modelling techniques outperform static models in portfolio theory.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:29:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 31. Andersson, Markus PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_30_j_idt585",{id:"formSmash:items:resultList:30:j_idt585",widgetVar:"widget_formSmash_items_resultList_30_j_idt585",onLabel:"Andersson, Markus ",offLabel:"Andersson, Markus ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_30_j_idt588",{id:"formSmash:items:resultList:30:j_idt588",widgetVar:"widget_formSmash_items_resultList_30_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:30:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Singh, NirankarKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:30:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); EN UNDERSÖKNING KRING PRISPÅVERKAN VID INRÄTTANDE AV EN NYBYGGNATION.2013Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_30_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:30:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_30_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This report is aimed at building companies and brokers who are interested to

see how the trends in prices are on older buildings, near a new construction

project. It may be that it is easier for construction companies to get through

the planning permission if it can be shown that the new construction projects

have a positive impact on the price of existing adjacent buildings. The

study may be viewed as a pilot project where this kind of reports are rare

and probably not done before in Sweden. The model must be extended to

more areas in order to ensure the result of higher significance.

The conclusion about the study is that it is an indication of positive price

impact, but the modeling and the approach has been the central focus of the

study. It is likely to assume that in order to make a better model, even more

factors have be taken into account. For example, it is possible that when a

construction project is built, it can be improved communications to the area,

new stores can be built or similar improvements, so even such aspects would

be needed for a more rigorous study.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:30:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 32. Andersson, Nicole PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_31_j_idt585",{id:"formSmash:items:resultList:31:j_idt585",widgetVar:"widget_formSmash_items_resultList_31_j_idt585",onLabel:"Andersson, Nicole ",offLabel:"Andersson, Nicole ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_31_j_idt588",{id:"formSmash:items:resultList:31:j_idt588",widgetVar:"widget_formSmash_items_resultList_31_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:31:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Söderberg, PetraKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:31:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A study of the most important volume drivers for sparkling wine in Sweden2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_31_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:31:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_31_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This paper examines the factors that affect volume of sparkling wine sold at licensed Swedish liquor stores. Regression analysis is used to model the relationship between the identified parameters believed to have an impact on the volume sold.

Social sustainability is also covered, and will be examined in the context of a deregulated alcohol market in the future. A 5C analysis and an analysis based on both WACOSS Social Sustainability framework and Social Life’s framework have been conducted.

Results from the regression analysis show that the parameters which affected the volume sold fell into three categories: Country, what kind of grape, and price. Most parameters affected the volume sold in a positive way; except for wines from New Zealand and higher priced wine which reduce the volume sold.

This thesis arrives at the conclusion that a regulated alcohol market is favorable in Sweden since the aim is to keep the alcohol consumption low and the overall public health high.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:31:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 33. André, Léo PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_32_j_idt585",{id:"formSmash:items:resultList:32:j_idt585",widgetVar:"widget_formSmash_items_resultList_32_j_idt585",onLabel:"André, Léo ",offLabel:"André, Léo ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:32:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:32:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Prediction of French day-ahead electricity prices: Comparison between a deterministic and a stochastic approach2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_32_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:32:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_32_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis deals with the new flow-based computation method used in the Central Western Europe Area. This is done on the financial side. The main aim is to produce some robust methods for predicting. Two approaches are used: the first one is based on a deterministic and algorithmic method involving the study of the interaction between the fundamentals and the prices. The other one is a more statistical approach based on a time series modeling of the French flow-based prices. Both approaches have advantages and disadvantages which will be discussed in the following. The work is mainly based on global simulated data provided by CASC in their implementation phase of the flow-base in Western Europe.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:32:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 34. Annink, Marit PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_33_j_idt585",{id:"formSmash:items:resultList:33:j_idt585",widgetVar:"widget_formSmash_items_resultList_33_j_idt585",onLabel:"Annink, Marit ",offLabel:"Annink, Marit ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_33_j_idt588",{id:"formSmash:items:resultList:33:j_idt588",widgetVar:"widget_formSmash_items_resultList_33_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:33:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Larsson, RebeccaKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:33:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Introduction of the Academic Factor Quality Minus Junk to a Commercial Factor Model and its Effect on the Explanatory Power. An OLS Regression on Stock Returns2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_33_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:33:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_33_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The ability to predict stock returns is an ability many wish to possess, and in an accurate way as possible. For many years there has been an interest in the field of factor models explaining the returns, with the aim to increase the explanatory power. This is however a complex business since the factors and their improvement of explanatory power need to be significant. Now and then, researchers come up with new significant factors that have a positive impact on models. AQR Capital Management is no exception to this, since they in 2013 presented the factor Quality Minus Junk, earning significant risk-adjusted returns. This bachelor thesis work within mathematical statistics and industrial engineering and management, aims to investigate whether or not the commercial multi-factor model used at the public pension fund Fjärde AP-fonden will be improved by adding the factor Quality Minus Junk, in the sense of explanatory power. The method used is mainly based on multiple linear regression and three three-year time periods are studied ranging from 2010 to 2018. The results from this thesis work show that the QMJ factor provides significant increases in explanatory power for one of three time periods, the most recent period 2016$-$2018. However, since the results are inconclusive further studies are needed in order to better understand how to interpret the results and whether or not to include the QMJ factor in the model.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:33:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 35. Arbegard, Fredrik PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_34_j_idt585",{id:"formSmash:items:resultList:34:j_idt585",widgetVar:"widget_formSmash_items_resultList_34_j_idt585",onLabel:"Arbegard, Fredrik ",offLabel:"Arbegard, Fredrik ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:34:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:34:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Inflyttning i Stockholmsområdet - En regressionsanalys av variabler som påverkar inflyttningen i Stockholmskommunerna.2012Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [sv] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_34_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:34:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_34_j_idt623_0_j_idt624",onLabel:"Abstract [sv]",offLabel:"Abstract [sv]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Undersökningen handlade om att ta fram en modell med variabler för att avgöra om det finns några variabler som påverkar inflyttningen till en kommun i Stockholmsområdet och i så fall vilka dessa är.

Undersökningen gjordes med hjälp av regressionsanalys av variablerna och metoden som användes var stepwise regression.

På så sätt erhölls koefficienterna till modellen och med hjälp utav dessa kunde man tolka om variablerna hade positiv eller negativ inverkan samt testa huruvida väntevärdet skulle kunna vara negativt eller positivt med hjälp av hypotestest med konfidensintervall.

Vid tolkning av variablerna så erhöll man att dem flesta variablerna betedde sig enligt dem hypoteserna man slagit fast vid tidigare.

Det visade sig att dem flesta utav variablernas väntevärde vid 95% konfidens intervall faktiskt låg inom ett område där det kunde anta både positivt och negativt tecken.

Dessutom gjordes residualplottar för att undersöka hur bra modellen var och om det förekom några mönster i variansen, det slogs fast vid observation att inga mönster förekom i plottarna.

Slutsatsen man kom fram till att även om vissa variabler betedde sig enligt dem uppskattade hypoteserna så tar modellen inte hänsyn till en del faktorer som kan ändra inflyttningen, samt att det finns fler variabler som kan ha större betydelse för hur folk väljer sin hemkommun.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:34:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 36. Armerin, Fredrik PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_35_j_idt585",{id:"formSmash:items:resultList:35:j_idt585",widgetVar:"widget_formSmash_items_resultList_35_j_idt585",onLabel:"Armerin, Fredrik ",offLabel:"Armerin, Fredrik ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_35_j_idt588",{id:"formSmash:items:resultList:35:j_idt588",widgetVar:"widget_formSmash_items_resultList_35_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Architecture and the Built Environment (ABE), Real Estate and Construction Management, Building and Real Estate Economics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:35:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Hallgren, JonasKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.Koski, TimoKTH, School of Engineering Sciences (SCI), Mathematics (Dept.).PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:35:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Forecasting Ranking in Harness Racing Using Probabilities Induced by Expected Positions2019In: Applied Artificial Intelligence, ISSN 0883-9514, E-ISSN 1087-6545, Vol. 33, no 2, p. 171-189Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_35_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:35:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_35_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Ranked events are pivotal in many important AI-applications such as Question Answering and recommendations systems. This paper studies ranked events in the setting of harness racing. For each horse there exists a probability distribution over its possible rankings. In the paper, it is shown that a set of expected positions (and more generally, higher moments) for the horses induces this probability distribution. The main contribution of the paper is a method, which extracts this induced probability distribution from a set of expected positions. An algorithm is proposed where the extraction of the induced distribution is given by the estimated expectations. MATLAB code is provided for the methodology. This approach gives freedom to model the horses in many different ways without the restrictions imposed by for instance logistic regression. To illustrate this point, we employ a neural network and ordinary ridge regression. The method is applied to predicting the distribution of the finishing positions for horses in harness racing. It outperforms both multinomial logistic regression and the market odds. The ease of use combined with fine results from the suggested approach constitutes a relevant addition to the increasingly important field of ranked events.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:35:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 37. Aro, Helena et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_36_j_idt588",{id:"formSmash:items:resultList:36:j_idt588",widgetVar:"widget_formSmash_items_resultList_36_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:36:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Djehiche, BoualemKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.Löfdahl, BjörnKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:36:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Stochastic modelling of disability insurance in a multi-period framework2015In: Scandinavian Actuarial Journal, ISSN 0346-1238, E-ISSN 1651-2030, no 1, p. 88-106Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_36_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:36:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_36_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We propose a stochastic semi-Markovian framework for disability modelling in a multi-period discrete-time setting. The logistic transforms of disability inception and recovery probabilities are modelled by means of stochastic risk factors and basis functions, using counting processes and generalized linear models. The model for disability inception also takes IBNR claims into consideration. We fit various versions of the models into Swedish disability claims data.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:36:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 38. Ashant, Aidin PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_37_j_idt585",{id:"formSmash:items:resultList:37:j_idt585",widgetVar:"widget_formSmash_items_resultList_37_j_idt585",onLabel:"Ashant, Aidin ",offLabel:"Ashant, Aidin ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_37_j_idt588",{id:"formSmash:items:resultList:37:j_idt588",widgetVar:"widget_formSmash_items_resultList_37_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:37:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Hakim, ElisabethKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:37:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Quantitative Portfolio Construction Using Stochastic Programming2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_37_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:37:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_37_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this study within quantitative portfolio optimization, stochastic programming is investigated as an investment decision tool. This research takes the direction of scenario based Mean-Absolute Deviation and is compared with the traditional Mean-Variance model and widely used Risk Parity portfolio. Furthermore, this thesis is done in collaboration with the First Swedish National Pension Fund, AP1, and the implemented multi-asset portfolios are thus tailored to match their investment style. The models are evaluated on two different fund management levels, in order to study if the portfolio performance benefits from a more restricted feasible domain. This research concludes that stochastic programming over the investigated time period is inferior to Risk Parity, but outperforms the Mean-Variance Model. The biggest aw of the model is its poor performance during periods of market stress. However, the model showed superior results during normal market conditions.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:37:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 39. Asmussen, Sören et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_38_j_idt588",{id:"formSmash:items:resultList:38:j_idt588",widgetVar:"widget_formSmash_items_resultList_38_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:38:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Rydén, TobiasKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:38:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); A Note on Skewness in Regenerative Simulation2011In: Communications in statistics. Simulation and computation, ISSN 0361-0918, E-ISSN 1532-4141, Vol. 40, no 1, p. 45-57Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_38_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:38:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_38_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The purpose of this article is to show, empirically and theoretically, that performance evaluation by means of regenerative simulation often involves random variables with distributions that are heavy tailed and heavily skewed. This, in turn, leads to the variance of estimators being poorly estimated, and confidence intervals having actual coverage quite different from (typically lower than) the nominal one. We illustrate these general ideas by estimating the mean occupancy and tail probabilities in M/G/1 queues, comparing confidence intervals computed from batch means to various intervals computed from regenerative cycles. In addition, we provide theoretical results on skewness to support the empirical findings.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:38:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 40. Aurell, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_39_j_idt585",{id:"formSmash:items:resultList:39:j_idt585",widgetVar:"widget_formSmash_items_resultList_39_j_idt585",onLabel:"Aurell, Alexander ",offLabel:"Aurell, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:39:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:39:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Mean-Field Type Games between Two Players Driven by Backward Stochastic Differential Equations2018In: Games, ISSN 2073-4336, E-ISSN 2073-4336, Vol. 9, no 5Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_39_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:39:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_39_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); In this paper, mean-field type games between two players with backward stochastic dynamics are defined and studied. They make up a class of non-zero-sum, non-cooperating, differential games where the players’ state dynamics solve backward stochastic differential equations (BSDE) that depend on the marginal distributions of player states. Players try to minimize their individual cost functionals, also depending on the marginal state distributions. Under some regularity conditions, we derive necessary and sufficient conditions for existence of Nash equilibria. Player behavior is illustrated by numerical examples, and is compared to a centrally planned solution where the social cost, the sum of playercosts, is minimized. The inefficiency of a Nash equilibrium, compared to socially optimal behavior, is quantified by the so-called price of anarchy. Numerical simulations of the price of anarchy indicate how the improvement in social cost achievable by a central planner depends on problem parameters.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:39:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 41. Aurell, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_40_j_idt585",{id:"formSmash:items:resultList:40:j_idt585",widgetVar:"widget_formSmash_items_resultList_40_j_idt585",onLabel:"Aurell, Alexander ",offLabel:"Aurell, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:40:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:40:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); The SVI implied volatility model and its calibration2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_40_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:40:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_40_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); The SVI implied volatility model is a parametric model for stochastic implied volatility.The SVI is interesting because of the possibility to state explicit conditions on its parameters so that the model does not generate prices where static arbitrage opportunities can occur. Calibration of the SVI model to real market data requires non-linear optimization algorithms and can be quite time consuming. In recent years, methods to calibrate the SVI model that use its inherent structure to reduce the dimensions of the optimization problem have been invented in order to speed up the calibration. The ?first aim of this thesis is to justify the use of the model and the no static arbitrage conditions from a theoretic point of view. Important theorems by Kellerer and Lee and their proofs are discussed in detail and the conditions are carefully derived. The second aim is to implement the model so that it can be calibrated to real market implied volatility data. A calibration method is presented and the outcome of two numerical experiments validate it. The performance of the calibration method introduced in this thesis is measured in how big a fraction of the total market volume the method manages to ?t within the market spread. Tests show that the model manages to ?t most of the market volume inside the spread, even for options with short time to maturity. Further tests show that the model is capable to recalibrate an SVI parameter set that allows for static arbitrage opportunities into an SVI parameter set that does not.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:40:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 42. Aurell, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_41_j_idt585",{id:"formSmash:items:resultList:41:j_idt585",widgetVar:"widget_formSmash_items_resultList_41_j_idt585",onLabel:"Aurell, Alexander ",offLabel:"Aurell, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:41:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:41:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Topics in the mean-field type approach to pedestrian crowd modeling and conventions2019Doctoral thesis, comprehensive summary (Other academic)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_41_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:41:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_41_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis consists of five appended papers, primarily addressingtopics in pedestrian crowd modeling and the formation of conventions.The first paper generalizes a pedestrian crowd model for competingsubcrowds to include nonlocal interactions and an arbitrary (butfinite) number of subcrowds. Each pedestrian is granted a ’personalspace’ and is effected by the presence of other pedestrians within it.The interaction strength may depend on subcrowd affinity. The paperinvestigates the mean-field type game between subcrowds and derivesconditions for the reduction of the game to an optimization problem.The second paper suggest a model for pedestrians with a predeterminedtarget they have to reach. The fixed and non-negotiablefinal target leads us to formulate a model with backward stochasticdifferential equations of mean-field type. Equilibrium in the game betweenthe tagged pedestrians and a surrounding crowd is characterizedwith the stochastic maximum principle. The model is illustrated by anumber of numerical examples.The third paper introduces sticky reflected stochastic differentialequations with boundary diffusion as a means to include walls andobstacles in the mean-field approach to pedestrian crowd modeling.The proposed dynamics allow the pedestrians to move and interactwhile spending time on the boundary. The model only admits a weaksolution, leading to the formulation of a weak optimal control problem.The fourth paper treats two-player finite-horizon mean-field typegames between players whose state trajectories are given by backwardstochastic differential equations of mean-field type. The paper validatesthe stochastic maximum principle for such games. Numericalexperiments illustrate equilibrium behavior and the price of anarchy.The fifth paper treats the formation of conventions in a large populationof agents that repeatedly play a finite two-player game. Theplayers access a history of previously used action profiles and form beliefson how the opposing player will act. A dynamical model wheremore recent interactions are considered to be more important in thebelief-forming process is proposed. Convergence of the history to acollection of minimal CURB blocks and, for a certain class of games,to Nash equilibria is proven.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:41:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 43. Aurell, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_42_j_idt585",{id:"formSmash:items:resultList:42:j_idt585",widgetVar:"widget_formSmash_items_resultList_42_j_idt585",onLabel:"Aurell, Alexander ",offLabel:"Aurell, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_42_j_idt588",{id:"formSmash:items:resultList:42:j_idt588",widgetVar:"widget_formSmash_items_resultList_42_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:42:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Dinetan, LeeKarreskog, GustavPrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:42:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Stochastic stability of mixed equilibriaManuscript (preprint) (Other academic)44. Aurell, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_43_j_idt585",{id:"formSmash:items:resultList:43:j_idt585",widgetVar:"widget_formSmash_items_resultList_43_j_idt585",onLabel:"Aurell, Alexander ",offLabel:"Aurell, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_43_j_idt588",{id:"formSmash:items:resultList:43:j_idt588",widgetVar:"widget_formSmash_items_resultList_43_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:43:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Djehiche, BoualemKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:43:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Behavior near walls in the mean-field approach to crowd dynamicsManuscript (preprint) (Other academic)45. Aurell, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_44_j_idt585",{id:"formSmash:items:resultList:44:j_idt585",widgetVar:"widget_formSmash_items_resultList_44_j_idt585",onLabel:"Aurell, Alexander ",offLabel:"Aurell, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_44_j_idt588",{id:"formSmash:items:resultList:44:j_idt588",widgetVar:"widget_formSmash_items_resultList_44_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:44:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Djehiche, BoualemKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:44:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Mean-field type modeling of nonlocal crowd aversion in pedestrian crowd dynamics2018In: SIAM Journal of Control and Optimization, ISSN 0363-0129, E-ISSN 1095-7138, Vol. 56, no 1, p. 434-455Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_44_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:44:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_44_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); We extend the class of pedestrian crowd models introduced by Lachapelle and Wolfram [Transp. Res. B: Methodol., 45 (2011), pp. 1572–1589] to allow for nonlocal crowd aversion and arbitrarily but finitely many interacting crowds. The new crowd aversion feature grants pedestrians a “personal space” where crowding is undesirable. We derive the model from a particle picture and treat it as a mean-field type game. Solutions to the mean-field type game are characterized via a Pontryagin-type maximum principle. The behavior of pedestrians acting under nonlocal crowd aversion is illustrated by a numerical simulation.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:44:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 46. Aurell, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_45_j_idt585",{id:"formSmash:items:resultList:45:j_idt585",widgetVar:"widget_formSmash_items_resultList_45_j_idt585",onLabel:"Aurell, Alexander ",offLabel:"Aurell, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_45_j_idt588",{id:"formSmash:items:resultList:45:j_idt588",widgetVar:"widget_formSmash_items_resultList_45_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:45:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Djehiche, BoualemKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:45:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Modeling tagged pedestrian motion: A mean-field type game approach2019In: Transportation Research Part B: Methodological, ISSN 0191-2615, E-ISSN 1879-2367, Vol. 121, p. 168-183Article in journal (Refereed)Abstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_45_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:45:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_45_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This paper suggests a model for the motion of tagged pedestrians: Pedestrians moving towards a specified targeted destination, which they are forced to reach. It aims to be a decision-making tool for the positioning of fire fighters, security personnel and other services in a pedestrian environment. Taking interaction with the surrounding crowd into account leads to a differential nonzero-sum game model where the tagged pedestrians compete with the surrounding crowd of ordinary pedestrians. When deciding how to act, pedestrians consider crowd distribution-dependent effects, like congestion and crowd aversion. Including such effects in the parameters of the game, makes it a mean-field type game. The equilibrium control is characterized, and special cases are discussed. Behavior in the model is studied by numerical simulations.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:45:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 47. Avril, Luc-Lao PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_46_j_idt585",{id:"formSmash:items:resultList:46:j_idt585",widgetVar:"widget_formSmash_items_resultList_46_j_idt585",onLabel:"Avril, Luc-Lao ",offLabel:"Avril, Luc-Lao ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:46:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:46:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); ESG Integration in AP1 Systematic Equity Strategies2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_46_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:46:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_46_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Responsible investing consists of buying more sustainable stocks, or green stocks, and selling the controversial ones. As a pension fund, and with the current climate regulations, it is a concern for Första AP-fonden to know if responsible investing is a plus value for financial aspects. Since our commissioner also has interests in factor strategies, rule-based systematic investment strategies, and possesses some, we will study and explain what are factor strategies. Financial beneﬁts from responsible investing could be explained by savings made on carbon taxes, if a company has a strong environmental policy. On the other hand, factor strategies have proven to work well historically, like the Fama-French value strategy which performed more than decently during the 80s, growing up to around 10 times the initial budget. By using an optimization approach, that maximizes ESG and factor scores with equal importance, we observed that half of the factors had lower performance when combined with ESG. Moreover, the factor portfolios lost their initial characteristics after ESG integration. We concluded that quality was the most promising candidate for a potential new systematic strategy.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:46:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 48. Axelsson, Rebecca PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_47_j_idt585",{id:"formSmash:items:resultList:47:j_idt585",widgetVar:"widget_formSmash_items_resultList_47_j_idt585",onLabel:"Axelsson, Rebecca ",offLabel:"Axelsson, Rebecca ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_47_j_idt588",{id:"formSmash:items:resultList:47:j_idt588",widgetVar:"widget_formSmash_items_resultList_47_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:47:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Källsbo, RebeccaKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:47:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Analys av variabler som påverkar lönsamheten i gymbranschen med multipel linjär regression2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_47_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:47:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_47_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); This thesis combines mathematical statistics with industrial economics and management to examine the profitability of the fitness industry in Sweden. The study was conducted with a dozen fitness businesses and the data mainly consisted of the companies’ annual reports from 2009 to 2014. The operating margin is the measure for profitability used in the calculations. A survey was conducted with multiple linear regressions to identify explanatory variables that affect the profitability and the extent of influence by these variables. The results of the regression analysis are discussed from economic aspects. This thesis contributes with strategic conclusions to the development of a business model for new and existing fitness businesses that aim to maximize profitability. The thesis can also be used as a tool in strategic development and give insight to how companies should approach the market. It includes an analysis of the competitive forces and external factors that may affect companies in the industry. Risk factors and growth opportunities are taken into account in the discussion about how companies can finance their operations. The regression analysis concludes that it is primarily the factors that affect the companies’ revenues and costs that have a significant impact on profitability. However, the results of the thesis also indicate that qualitative factors have a major impact on profitability.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:47:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 49. Back, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_48_j_idt585",{id:"formSmash:items:resultList:48:j_idt585",widgetVar:"widget_formSmash_items_resultList_48_j_idt585",onLabel:"Back, Alexander ",offLabel:"Back, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_48_j_idt588",{id:"formSmash:items:resultList:48:j_idt588",widgetVar:"widget_formSmash_items_resultList_48_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:48:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Keith, WilliamKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:48:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Bayesian Neural Networks for Financial Asset Forecasting2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_48_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:48:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_48_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Neural networks are powerful tools for modelling complex non-linear mappings, but they often suffer from overfitting and provide no measures of uncertainty in their predictions. Bayesian techniques are proposed as a remedy to these problems, as these both regularize and provide an inherent measure of uncertainty from their posterior predictive distributions. By quantifying predictive uncertainty, we attempt to improve a systematic trading strategy by scaling positions with uncertainty. Exact Bayesian inference is often impossible, and approximate techniques must be used. For this task, this thesis compares dropout, variational inference and Markov chain Monte Carlo. We find that dropout and variational inference provide powerful regularization techniques, but their predictive uncertainties cannot improve a systematic trading strategy. Markov chain Monte Carlo provides powerful regularization as well as promising estimates of predictive uncertainty that are able to improve a systematic trading strategy. However, Markov chain Monte Carlo suffers from an extreme computational cost in the high-dimensional setting of neural networks.

PrimeFaces.cw("Panel","tryPanel",{id:"formSmash:items:resultList:48:j_idt623:0:abstractPanel",widgetVar:"tryPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); 50. Back, Alexander PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_49_j_idt585",{id:"formSmash:items:resultList:49:j_idt585",widgetVar:"widget_formSmash_items_resultList_49_j_idt585",onLabel:"Back, Alexander ",offLabel:"Back, Alexander ",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); et al. PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_49_j_idt588",{id:"formSmash:items:resultList:49:j_idt588",widgetVar:"widget_formSmash_items_resultList_49_j_idt588",onLabel:"et al.",offLabel:"et al.",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:49:orgPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Keith, WilliamKTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.PrimeFaces.cw("Panel","testPanel",{id:"formSmash:items:resultList:49:etAlPanel",widgetVar:"testPanel",toggleable:true,toggleSpeed:500,collapsed:false,toggleOrientation:"vertical",closable:true,closeSpeed:500}); Valuation of Contingent Convertible Bonds2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAbstract [en] PrimeFaces.cw("SelectBooleanButton","widget_formSmash_items_resultList_49_j_idt623_0_j_idt624",{id:"formSmash:items:resultList:49:j_idt623:0:j_idt624",widgetVar:"widget_formSmash_items_resultList_49_j_idt623_0_j_idt624",onLabel:"Abstract [en]",offLabel:"Abstract [en]",onIcon:"ui-icon-triangle-1-s",offIcon:"ui-icon-triangle-1-e"}); Contingent convertible bonds are hybrid capital instruments, contingent on some form of indicator of financial distress of the issuing bank. Following the financial crisis, these instruments are proposed as a solution to the moral hazard issue of banks too big to fail. With the increased capital requirements of the Basel III directive, contingent capital enables banks to increase their capitalization without issuing expensive equity. Also, in times of historically low interest rates, these instruments might be interesting for investors in search of higher yields, as well as long term investors wanting to implement countercyclical investment strategies. However, due to the high complexity of these instruments, valuation has proven diffcult. The purpose of this thesis is to value instruments contingent on the bank's common equity tier 1 to risk-weighted assets ratio. We build our model upon the work of Glasserman & Nouri (2012), and extend it to include contingency on risk-weighted assets, instant non-continuous conversion to equity, and a combination of fixed imposed loss and fixed conversion price as terms of conversion. We use a capital structure model in continuous time to define asset dynamics, asset claims and the event of conversion and liquidation of the bank. Thereafter we use two important results from Glasserman & Nouri (2012) to value the discounted cash flows to holders of debt and contingent debt. From this, we arrive at closed form solutions for the coupon rates of these securities.

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