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Convex Optimization
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.ORCID iD: 0000-0001-9210-121X
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.).ORCID iD: 0000-0002-0775-9680
2012 (English)In: Springer Series in Operations Research and Financial Engineering, Springer Nature , 2012, p. 33-38Chapter in book (Refereed)
Abstract [en]

Many of the investment and hedging problems we will encounter can be formulated as a minimization of a function over a set determined by the investor’s risk and budget constraints and other restrictions on the type of positions that the investor can take. Such problems become particularly tractable if both the function to be minimized and the set over which the minimization is done are convex. The minimization problem is in this case called a convex optimization problem. This chapter presents basic results for solving convex optimization problems that will be applied in subsequent chapters.

Place, publisher, year, edition, pages
Springer Nature , 2012. p. 33-38
Keywords [en]
Basic Result, Budget Constraint, Convex Subset, Inequality Constraint, Minimization Problem
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-304455DOI: 10.1007/978-1-4614-4103-8_2Scopus ID: 2-s2.0-85098118761OAI: oai:DiVA.org:kth-304455DiVA, id: diva2:1608674
Note

QC 20211104

Available from: 2021-11-04 Created: 2021-11-04 Last updated: 2022-12-12Bibliographically approved

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Hult, HenrikLindskog, Filip

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