{"title":"Directional approach to gradual cover: the continuous case","authors":"T. Drezner, Z. Drezner, P. Kalczynski","doi":"10.1007/s10287-020-00378-1","DOIUrl":"https://doi.org/10.1007/s10287-020-00378-1","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"18 1","pages":"25 - 47"},"PeriodicalIF":0.9,"publicationDate":"2020-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10287-020-00378-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48748138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the application of Wishart process to the pricing of equity derivatives: the multi-asset case","authors":"G. La Bua, D. Marazzina","doi":"10.2139/ssrn.3466259","DOIUrl":"https://doi.org/10.2139/ssrn.3466259","url":null,"abstract":"Given the inherent complexity of financial markets, a wide area of research in the field of mathematical finance is devoted to develop accurate models for the pricing of contingent claims. Focusing on the stochastic volatility approach (i.e. we assume to describe asset volatility as an additional stochastic process), it appears desirable to introduce reliable dynamics in order to take into account the presence of several assets involved in the definition of multi-asset payoffs. In this article we deal with the multi asset Wishart Affine Stochastic Correlation model, that makes use of Wishart process to describe the stochastic variance covariance matrix of assets return. The resulting parametrization turns out to be a genuine multi-asset extension of the Heston model: each asset is exactly described by a single instance of the Heston dynamics while the joint behaviour is enriched by cross-assets and cross-variances stochastic correlation, all wrapped in an affine modeling. In this framework, we propose a fast and accurate calibration procedure, and two Monte Carlo simulation schemes.","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"18 1","pages":"149 - 176"},"PeriodicalIF":0.9,"publicationDate":"2019-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49127636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring the dynamics of business survey data using Markov models","authors":"Werner Hölzl, S. Kaniovski, Y. Kaniovski","doi":"10.1007/s10287-019-00354-4","DOIUrl":"https://doi.org/10.1007/s10287-019-00354-4","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"16 1","pages":"621 - 649"},"PeriodicalIF":0.9,"publicationDate":"2019-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10287-019-00354-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44632883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Berkhout, B. Heidergott, Jennifer Sommer, H. Daduna
{"title":"Robustness analysis of generalized Jackson network","authors":"J. Berkhout, B. Heidergott, Jennifer Sommer, H. Daduna","doi":"10.1007/s10287-019-00355-3","DOIUrl":"https://doi.org/10.1007/s10287-019-00355-3","url":null,"abstract":"","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"16 1","pages":"697 - 714"},"PeriodicalIF":0.9,"publicationDate":"2019-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10287-019-00355-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42160343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Asset allocation under predictability and parameter uncertainty using LASSO","authors":"Andrea Rigamonti, Alex Weissensteiner","doi":"10.2139/ssrn.3257749","DOIUrl":"https://doi.org/10.2139/ssrn.3257749","url":null,"abstract":"We consider a short-term investor who exploits return predictability in stocks and bonds to maximize mean-variance utility. Since the true parameters are unknown, we resort to portfolio optimization in form of linear regression with LASSO in order to mitigate problems related to estimation errors. As standard cross-validation relies on the assumption of i.i.d. returns, we propose a new type of cross-validation that selects $$ lambda $$ λ from simulated returns sampled from a multivariate normal distribution. We find an inverse U-shaped relationship between the selected $$ lambda $$ λ and the expected utility, and we show that the optimal value of $$ lambda $$ λ declines as the number of observations used to estimate the parameters increases. We finally show how our strategy outperforms some commonly employed benchmarks.","PeriodicalId":46743,"journal":{"name":"Computational Management Science","volume":"1 1","pages":"1-23"},"PeriodicalIF":0.9,"publicationDate":"2019-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46417374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}