Modelling market risk using bootstrapping and filtered historical simulation. A case study of Old Mutual.

Author

Machinya, Rufaro T

Title

Modelling market risk using bootstrapping and filtered historical simulation. A case study of Old Mutual.

Abstract

For any organization, managing financial risk must include market risk. Companies utilize a variety of quantitative strategies, including Expected Shortfall (ES) and Value at Risk (VaR), to manage market risk. VaR, a commonly used indicator of market risk, assesses the largest loss an organization may reasonably expect to suffer over a particular time period with a certain level of confidence. VaR has some drawbacks, such as the inability to account for the tail risk, which is the likelihood of extremely large losses beyond a certain point. Companies use ES, which calculates the average loss that is anticipated to occur over a specific threshold level, to get around this restriction. The historical data, which is used to calculate the probability distribution of market returns, is one of the main inputs in VaR and ES models. However, historical data might not always be trustworthy, particularly in times of economic crisis or market volatility. In these circumstances, organizations estimate the probability distribution of market returns using different techniques like bootstrapping and filtered historical simulation (FHS). This study examines the modeling of market risk using daily equity returns from OLD MUTUAL portfolio over time to assess the forecasting performance of Value at Risk (VaR). The paper employs VaR models like bootstrapping and filtered historical simulation. As part of this procedure, the residuals from the filtered historical simulation GJR-GARCH will be bootstrapped, and a comparison between the residuals that have been adjusted for volatility and those that have not will be made. The findings indicate that a portfolio that has been volatility-adjusted will be more successful. In conclusion, utilizing bootstrapping and FHS to simulate market risk is an efficient way for businesses to manage their market risk. A more accurate estimate of the probability distribution of market returns is provided by the model, which can also assist businesses in making more informed judgments regarding their risk management plans.

Date

2023

Publisher

BUSE

Keywords

Managing financial risk

Expected Shortfall

Value at Risk

Supervisor

Mr. Ngwende