杠杆 ETF 预期效用的长期稳健增长率

IF 0.9 3区 经济学 Q3 BUSINESS, FINANCE
Tim Leung, Hyungbin Park, Heejun Yeo
{"title":"杠杆 ETF 预期效用的长期稳健增长率","authors":"Tim Leung, Hyungbin Park, Heejun Yeo","doi":"10.1007/s11579-024-00371-1","DOIUrl":null,"url":null,"abstract":"<p>This paper analyzes the robust long-term growth rate of expected utility and expected return from holding a leveraged exchange-traded fund. When the Markovian model parameters in the reference asset are uncertain, the robust long-term growth rate is derived by analyzing the worst-case parameters among an uncertainty set. We compute the growth rate and describe the optimal leverage ratio maximizing the robust long-term growth rate. To achieve this, the worst-case parameters are analyzed by the comparison principle, and the growth rate of the worst-case is computed using the Hansen–Scheinkman decomposition. The robust long-term growth rates are obtained explicitly under a number of models for the reference asset, including the geometric Brownian motion, Cox–Ingersoll–Ross, 3/2, and Heston and 3/2 stochastic volatility models. Additionally, we demonstrate the impact of stochastic interest rates, such as the Vasicek and inverse GARCH short rate models. This paper is an extended work of Leung and Park (Int J Theor Appl Finance 20(6):1750037, 2017).</p>","PeriodicalId":48722,"journal":{"name":"Mathematics and Financial Economics","volume":"63 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust long-term growth rate of expected utility for leveraged ETFs\",\"authors\":\"Tim Leung, Hyungbin Park, Heejun Yeo\",\"doi\":\"10.1007/s11579-024-00371-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This paper analyzes the robust long-term growth rate of expected utility and expected return from holding a leveraged exchange-traded fund. When the Markovian model parameters in the reference asset are uncertain, the robust long-term growth rate is derived by analyzing the worst-case parameters among an uncertainty set. We compute the growth rate and describe the optimal leverage ratio maximizing the robust long-term growth rate. To achieve this, the worst-case parameters are analyzed by the comparison principle, and the growth rate of the worst-case is computed using the Hansen–Scheinkman decomposition. The robust long-term growth rates are obtained explicitly under a number of models for the reference asset, including the geometric Brownian motion, Cox–Ingersoll–Ross, 3/2, and Heston and 3/2 stochastic volatility models. Additionally, we demonstrate the impact of stochastic interest rates, such as the Vasicek and inverse GARCH short rate models. This paper is an extended work of Leung and Park (Int J Theor Appl Finance 20(6):1750037, 2017).</p>\",\"PeriodicalId\":48722,\"journal\":{\"name\":\"Mathematics and Financial Economics\",\"volume\":\"63 1\",\"pages\":\"\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematics and Financial Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1007/s11579-024-00371-1\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematics and Financial Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1007/s11579-024-00371-1","RegionNum":3,"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

摘要

本文分析了持有杠杆式交易所交易基金的预期效用和预期收益的稳健长期增长率。当参考资产中的马尔可夫模型参数不确定时,通过分析不确定性集合中的最坏情况参数,得出稳健长期增长率。我们计算增长率,并描述使稳健长期增长率最大化的最优杠杆比率。为此,我们采用比较原则分析最坏情况参数,并利用汉森-申克曼分解法计算最坏情况的增长率。在参考资产的多种模型下,包括几何布朗运动模型、考克斯-英格索尔-罗斯模型、3/2 模型以及赫斯顿和 3/2 随机波动模型,都能明确地得到稳健的长期增长率。此外,我们还展示了随机利率的影响,如 Vasicek 和逆 GARCH 短利率模型。本文是 Leung 和 Park(Int J Theor Appl Finance 20(6):1750037,2017)的扩展工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Robust long-term growth rate of expected utility for leveraged ETFs

Robust long-term growth rate of expected utility for leveraged ETFs

This paper analyzes the robust long-term growth rate of expected utility and expected return from holding a leveraged exchange-traded fund. When the Markovian model parameters in the reference asset are uncertain, the robust long-term growth rate is derived by analyzing the worst-case parameters among an uncertainty set. We compute the growth rate and describe the optimal leverage ratio maximizing the robust long-term growth rate. To achieve this, the worst-case parameters are analyzed by the comparison principle, and the growth rate of the worst-case is computed using the Hansen–Scheinkman decomposition. The robust long-term growth rates are obtained explicitly under a number of models for the reference asset, including the geometric Brownian motion, Cox–Ingersoll–Ross, 3/2, and Heston and 3/2 stochastic volatility models. Additionally, we demonstrate the impact of stochastic interest rates, such as the Vasicek and inverse GARCH short rate models. This paper is an extended work of Leung and Park (Int J Theor Appl Finance 20(6):1750037, 2017).

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Mathematics and Financial Economics
Mathematics and Financial Economics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
2.80
自引率
6.20%
发文量
17
期刊介绍: The primary objective of the journal is to provide a forum for work in finance which expresses economic ideas using formal mathematical reasoning. The work should have real economic content and the mathematical reasoning should be new and correct.
×
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