Scholarlink

Abstract <p>The authors describe a modified scenario simulation to assessing the risks of financial instruments. It is based on the technique proposed by F. Jamshidian and Y. Zhu, which allows considerable acceleration of calculating risk indicators for large portfolios, relative to the Monte Carlo approach. The modification proposed in this work consists of changing the way of selecting scenarios (points of the approximating distribution) and allows the quality of the approximation and the accuracy of the estimates to be improved. It does not impose restrictions on the distribution of factors influencing the portfolio price, expanding the scope of its application. The VaR indicator estimates obtained in the two ways are compared in a financial portfolio consisting of an interest rate swap for cases where the values of the factors influencing its price have normal, gamma, and Student’s <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="11968_2025_5144_Article_IEq1.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="10" /> </InlineMediaObject> <EquationSource Format="TEX">\(t\)</EquationSource> <!--CMatCMGU2470030Gudkov-m1--> </InlineEquation> distributions.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Optimizing the Selection of Scenarios for Assessing the Risks of Financial Instruments

  • 期刊论文

  • 发表日期：

    2025年3月29日

查看全文
  • I. D. Gudkov,
  • D. A. Demin,
  • L. V. Nazarov

摘要

Abstract

The authors describe a modified scenario simulation to assessing the risks of financial instruments. It is based on the technique proposed by F. Jamshidian and Y. Zhu, which allows considerable acceleration of calculating risk indicators for large portfolios, relative to the Monte Carlo approach. The modification proposed in this work consists of changing the way of selecting scenarios (points of the approximating distribution) and allows the quality of the approximation and the accuracy of the estimates to be improved. It does not impose restrictions on the distribution of factors influencing the portfolio price, expanding the scope of its application. The VaR indicator estimates obtained in the two ways are compared in a financial portfolio consisting of an interest rate swap for cases where the values of the factors influencing its price have normal, gamma, and Student’s \(t\) distributions.