Investigating the Role of Probability Distributions on the Performance of Value at Risk and Expected Drawdown

Akbarian, Mohammad Reza; Ghadimi, Mohammad Jafar

doi:10.22034/jmsmo.2025.513297.1022

Investigating the Role of Probability Distributions on the Performance of Value at Risk and Expected Drawdown

Document Type : Original Article

Authors

Mohammad Reza Akbarian

Mohammad Jafar Ghadimi

Department of Management, Deh.C, Islamic Azad University, Isfahan, Iran

10.22034/jmsmo.2025.513297.1022

Abstract

The aim of this study is to empirically investigate the role of probability distributions on the performance of value at risk and expected return on the Tehran Stock Exchange. Probability distributions are of great importance in portfolio management, hedging, asset pricing, and trading strategies. Appropriate accuracy in their estimation makes the modeling results more accurate and reliable. In the present study, six distributions were used to estimate two risk measures, including value at risk and expected return (conditional value at risk), including normal distributions, t-space-scale, log normal, inverse normal, general distribution of extreme points, and general Pareto distribution. The maximum likelihood statistical approach was also used to fit the distribution to the empirical data. The results of the research on the total index in the period 2011 to 2019 show that the most appropriate distribution for estimating value at risk and expected drawdown in a one-day time horizon is the location-scale t-distribution, and the most appropriate distribution for estimating value at risk and conditional value at risk in weekly and monthly time horizons is the general distribution of extreme points. Therefore, choosing these distributions can increase the accuracy of risk estimation.

Keywords

Probability Density Function

Value at Risk

Conditional Value at Risk

Marginal Distributions

Subjects

Other topics related to management and organization

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