部分信息和异质先验的相对财富考量

IF 1.4 4区 经济学 Q3 BUSINESS, FINANCE
Chao Deng, Xizhi Su, Chao Zhou
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引用次数: 0

摘要

SIAM 金融数学期刊》,第 15 卷第 2 期,第 360-398 页,2024 年 6 月。摘要.当市场收益不可观测时,我们为具有相对财富表现标准的[数学]代理人建立了纳什均衡。我们证明,随机收益率模型下的最优投资策略可以用一个完全耦合的前向-后向随机微分方程(FBSDE)来表征。我们建立了一类具有随机系数的 FBSDE 的存在性和唯一性结果,并利用深度神经网络求解了部分信息下的效用博弈。我们通过与线性情况下的半解析解进行基本情况比较,证明了其效率和准确性。我们通过数值模拟检验了夏普比率和方差风险比率。我们发现,先验估计最准确的代理很可能会领导牛群。此外,与同质情况相比,竞争对异质代理的影响随市场特征的变化更大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relative Wealth Concerns with Partial Information and Heterogeneous Priors
SIAM Journal on Financial Mathematics, Volume 15, Issue 2, Page 360-398, June 2024.
Abstract.We establish a Nash equilibrium for [math] agents with the relative wealth performance criteria when the market return is unobservable. We show that the optimal investment strategy under a stochastic return rate model can be characterized by a fully coupled forward-backward stochastic differential equation (FBSDE). We establish the existence and uniqueness results for the class of FBSDEs with stochastic coefficients and solve the utility game under partial information by using deep neural networks. We demonstrate the efficiency and accuracy by a base-case comparison with the semianalytical solution in the linear case. We examined the Sharpe ratios and the variance risk ratios by numerical simulation. We observe that the agent with the most accurate prior estimate is likely to lead the herd. Moreover, the effect of competition on heterogeneous agents varies more with market characteristics compared to that of the homogeneous case.
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来源期刊
SIAM Journal on Financial Mathematics
SIAM Journal on Financial Mathematics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
2.30
自引率
10.00%
发文量
52
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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