Optimal portfolios with anticipating information on the stochastic interest rate

IF 1.4 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Bernardo D’Auria, José A. Salmeron
{"title":"Optimal portfolios with anticipating information on the stochastic interest rate","authors":"Bernardo D’Auria, José A. Salmeron","doi":"10.1007/s10203-024-00463-z","DOIUrl":null,"url":null,"abstract":"<p>By employing the technique of enlargement of filtrations, we demonstrate how to incorporate information about the future trend of the stochastic interest rate process into a financial model. By modeling the interest rate as an affine diffusion process, we obtain explicit formulas for the additional expected logarithmic utility in solving the optimal portfolio problem. We begin by solving the problem when the additional information directly refers to the interest rate process, and then extend the analysis to the case where the information relates to the values of an underlying Markov chain. The dynamics of this chain may depend on anticipated market information, jump at predefined epochs, and modulate the parameters of the stochastic interest rate process. The theoretical study is then complemented by an illustrative numerical analysis.\n</p>","PeriodicalId":43711,"journal":{"name":"Decisions in Economics and Finance","volume":"7 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Decisions in Economics and Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10203-024-00463-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SOCIAL SCIENCES, MATHEMATICAL METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

By employing the technique of enlargement of filtrations, we demonstrate how to incorporate information about the future trend of the stochastic interest rate process into a financial model. By modeling the interest rate as an affine diffusion process, we obtain explicit formulas for the additional expected logarithmic utility in solving the optimal portfolio problem. We begin by solving the problem when the additional information directly refers to the interest rate process, and then extend the analysis to the case where the information relates to the values of an underlying Markov chain. The dynamics of this chain may depend on anticipated market information, jump at predefined epochs, and modulate the parameters of the stochastic interest rate process. The theoretical study is then complemented by an illustrative numerical analysis.

Abstract Image

具有随机利率预期信息的最优投资组合
通过使用放大过滤技术,我们展示了如何将随机利率过程的未来趋势信息纳入金融模型。通过将利率建模为仿射扩散过程,我们得到了求解最优投资组合问题时额外预期对数效用的明确公式。我们首先解决附加信息直接涉及利率过程时的问题,然后将分析扩展到信息涉及底层马尔可夫链值的情况。该链的动态可能取决于预期的市场信息,在预定的时间点跳变,并调节随机利率过程的参数。理论研究随后辅以说明性的数值分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Decisions in Economics and Finance
Decisions in Economics and Finance SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
2.50
自引率
9.10%
发文量
10
期刊介绍: Decisions in Economics and Finance: A Journal of Applied Mathematics is the official publication of the Association for Mathematics Applied to Social and Economic Sciences (AMASES). It provides a specialised forum for the publication of research in all areas of mathematics as applied to economics, finance, insurance, management and social sciences. Primary emphasis is placed on original research concerning topics in mathematics or computational techniques which are explicitly motivated by or contribute to the analysis of economic or financial problems.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信