首页    期刊浏览 2024年11月30日 星期六
登录注册

文章基本信息

  • 标题:Modelling extreme risk of the South African Financial Index (J580) using the generalised Pareto distribution
  • 本地全文:下载
  • 作者:Owen Jakata ; Delson Chikobvu
  • 期刊名称:Journal of Economic and Financial Sciences
  • 印刷版ISSN:1995-7076
  • 电子版ISSN:2312-2803
  • 出版年度:2019
  • 卷号:12
  • 期号:1
  • 页码:7-13
  • DOI:10.4102/jef.v12i1.407
  • 摘要:Abstract Orientation: In light of the global financial instabilities, investors and risk analysts need extreme risk management tools to help them accurately monitor and reduce market exposure in an investment portfolio. Research purpose: The main aim of the study was to apply extreme value theory results to quantify the extreme downside risk and upside risk of the South African Financial Index (J580). Motivation for the study: Financial markets have been characterised by significant instabilities caused by occurrence of extreme events. This means there is a need to develop proper risk management models that can accurately assess these extreme events. Research approach, design and method: The peak over threshold approach was used to obtain the excess returns over the threshold. The generalised Pareto distribution (GPD) was fitted to the excess returns over the threshold to estimate the parameters, which were used to quantify the downside and upside risk in the form of value at risk and expected shortfall. Main findings: The findings indicate that the upside risk of the Financial Index (J580) outweighs the downside risk. Practical/managerial implications: These findings would be important for hedging purposes, investment decision-making and help risk analysts to monitor the exposure of market risk and protect their investment portfolios accordingly. Contribution/value-add: This article will contribute to empirical evidence of the research into the behaviour of the extreme returns on the Johannesburg Stock Exchange. The GPD model formulated will be used to assess tail-related risk.
  • 其他摘要:Orientation: In light of the global financial instabilities, investors and risk analysts need extreme risk management tools to help them accurately monitor and reduce market exposure in an investment portfolio. Research purpose: The main aim of the study was to apply extreme value theory results to quantify the extreme downside risk and upside risk of the South African Financial Index (J580). Motivation for the study: Financial markets have been characterised by significant instabilities caused by occurrence of extreme events. This means there is a need to develop proper risk management models that can accurately assess these extreme events. Research approach, design and method: The peak over threshold approach was used to obtain the excess returns over the threshold. The generalised Pareto distribution (GPD) was fitted to the excess returns over the threshold to estimate the parameters, which were used to quantify the downside and upside risk in the form of value at risk and expected shortfall. Main findings: The findings indicate that the upside risk of the Financial Index (J580) outweighs the downside risk. Practical/managerial implications: These findings would be important for hedging purposes, investment decision-making and help risk analysts to monitor the exposure of market risk and protect their investment portfolios accordingly. Contribution/value-add: This article will contribute to empirical evidence of the research into the behaviour of the extreme returns on the Johannesburg Stock Exchange. The GPD model formulated will be used to assess tail-related risk.
  • 关键词:extreme value theory; peak over threshold; generalised Pareto distribution; financial index (J580); value at risk; expected shortfall; downside risk; upside risk.
  • 其他关键词:extreme value theory;peak over threshold;generalised Pareto distribution;financial index (J580);value at risk;expected shortfall;downside risk;upside risk
国家哲学社会科学文献中心版权所有