Calculation of VaR — Based on the Account Manager's Perspective
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v5i3.2358
Abstract
Value at Risk (VaR) is one of the risk measurement methods used by international financial institutions, which can be applied to stock, bond, future, option, complex derivative and other financial markets. VaR is also a primary measure for quantifying market risk and has gradually become the main basis for banks to calculate their capital requirements for market risk using internal models. This paper attempts to use three methods (variance-covariance method, historical simulation method, Monte-Carlo simulation method) to calculate VaR in both single asset and multiple assets scenarios to help account managers manage portfolios and guard against various potential risks. In addition, it compares the advantages and disadvantages of three methods in different scenarios to assist account managers adopt algorithms flexibly.
Keywords
Value at Risk, variance-covariance method, historical simulation method, Monte-Carlo simulation method, A-Share market
Full Text
PDF - Viewed/Downloaded: 2 TimesReferences
[1] Daan Frenkel. Introduction to monte carlo methods. J. von Neumann Inst. Comput., 23, 01, 2004.
[2] Ervin Indarwati and Rosita Kusumawati. Estimation of the portfolio risk from conditional value at risk using monte carlo simulation. Jurnal Matematika, Statistika dan Komputasi, 17:370–380, 05, 2021.
[3] Xiaoning Kang, Zhiyang Zhang, and Xinwei Deng. Covariance Estimation via the Modified Cholesky Decomposition, pages 887–900. 04, 2023.
[4] Simone Manganelli and Robert F. Engle. Value at risk models in finance. New York University Stern School of Business Research Paper Series, 2001.
[5] Harry Markowitz. Portfolio selection. The Journal of Finance, 7(1):77–91, 1952.
[6] Robert Merton. Lifetime portfolio selection under uncertainty: The continuous-time case. The Review of Economics and Statistics, 51:247–57, 02, 1969.
[7] J Morgan/Reuters. RiskMetrics-Technical Document. 01, 1996.
[8] Zhijie Xiao and Roger Koenker. Conditional quantile estimation for garch models (preliminary). 04, 2008.
[2] Ervin Indarwati and Rosita Kusumawati. Estimation of the portfolio risk from conditional value at risk using monte carlo simulation. Jurnal Matematika, Statistika dan Komputasi, 17:370–380, 05, 2021.
[3] Xiaoning Kang, Zhiyang Zhang, and Xinwei Deng. Covariance Estimation via the Modified Cholesky Decomposition, pages 887–900. 04, 2023.
[4] Simone Manganelli and Robert F. Engle. Value at risk models in finance. New York University Stern School of Business Research Paper Series, 2001.
[5] Harry Markowitz. Portfolio selection. The Journal of Finance, 7(1):77–91, 1952.
[6] Robert Merton. Lifetime portfolio selection under uncertainty: The continuous-time case. The Review of Economics and Statistics, 51:247–57, 02, 1969.
[7] J Morgan/Reuters. RiskMetrics-Technical Document. 01, 1996.
[8] Zhijie Xiao and Roger Koenker. Conditional quantile estimation for garch models (preliminary). 04, 2008.
Copyright © 2024 Yansong Wang, Xianshuo Qi, Shu Qin
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License