{"title":"Short Communication: Monte Carlo Expected Wealth and Risk Measure Trade-Off Portfolio Optimization","authors":"Raino A. E. Mäkinen, Jari Toivanen","doi":"10.1137/23m1624439","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Financial Mathematics, Volume 15, Issue 2, Page SC41-SC53, June 2024. <br/> Abstract.A multiperiod portfolio optimization is described with Monte Carlo sampled risky asset paths under realistic constraints on the investment policies. The proposed approach can be used with various asset and risk models. It is flexible as it does not require dynamic programming or any transformations. As examples, the variance and semivariance risks are considered leading to mean-variance and mean-semivariance formulations, respectively. A quasi-Newton method with an adjoint gradient computation can solve the resulting optimization problems efficiently. Numerical examples show efficient frontiers together with optimal asset allocations computed for mean-variance and mean-semivariance portfolios with two and five assets.","PeriodicalId":48880,"journal":{"name":"SIAM Journal on Financial Mathematics","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Financial Mathematics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1137/23m1624439","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
SIAM Journal on Financial Mathematics, Volume 15, Issue 2, Page SC41-SC53, June 2024. Abstract.A multiperiod portfolio optimization is described with Monte Carlo sampled risky asset paths under realistic constraints on the investment policies. The proposed approach can be used with various asset and risk models. It is flexible as it does not require dynamic programming or any transformations. As examples, the variance and semivariance risks are considered leading to mean-variance and mean-semivariance formulations, respectively. A quasi-Newton method with an adjoint gradient computation can solve the resulting optimization problems efficiently. Numerical examples show efficient frontiers together with optimal asset allocations computed for mean-variance and mean-semivariance portfolios with two and five assets.
期刊介绍：
SIAM Journal on Financial Mathematics (SIFIN) addresses theoretical developments in financial mathematics as well as breakthroughs in the computational challenges they encompass. The journal provides a common platform for scholars interested in the mathematical theory of finance as well as practitioners interested in rigorous treatments of the scientific computational issues related to implementation. On the theoretical side, the journal publishes articles with demonstrable mathematical developments motivated by models of modern finance. On the computational side, it publishes articles introducing new methods and algorithms representing significant (as opposed to incremental) improvements on the existing state of affairs of modern numerical implementations of applied financial mathematics.
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