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Evaluating Switching GARCH Volatility Forecasts During the Recent Financial Crisis

Augustsson, Viktor LU (2014) NEKN01 20142
Department of Economics
Abstract
Forecasting volatility is a fundamental topic in in both academic and applied financial economics. Different GARCH-specifications are by far the most popular model based approach used for this purpose. This thesis evaluates the forecast accuracy of some specific GARCH-models; GARCH, EGARCH, APGARCH and MRS-GARCH. The primary purpose of the essay is to investigate whether the more flexible two-regime MRS-GARCH model outperforms the more conventional one-regime GARCH models in a very volatile time period during the recent financial crises. The evaluation period stretches from the day when Lehman Brothers went bankrupt and one year ahead. Each model is evaluated using two indexes with different characteristics; the Standard & Poor 500 and the... (More)
Forecasting volatility is a fundamental topic in in both academic and applied financial economics. Different GARCH-specifications are by far the most popular model based approach used for this purpose. This thesis evaluates the forecast accuracy of some specific GARCH-models; GARCH, EGARCH, APGARCH and MRS-GARCH. The primary purpose of the essay is to investigate whether the more flexible two-regime MRS-GARCH model outperforms the more conventional one-regime GARCH models in a very volatile time period during the recent financial crises. The evaluation period stretches from the day when Lehman Brothers went bankrupt and one year ahead. Each model is evaluated using two indexes with different characteristics; the Standard & Poor 500 and the Bombay Sensex index. The result shows that the MRS-GARCH models are superior in predictive ability on S&P500 compared to the other tested models. Conversely, the overall relative performance accuracy of the BSE is less clear-cut since none of the tested models seem to perform particularly well. Generally, the results indicate that the MRS-GARCH provides better forecasts on S&P 500 compared to the other models and that no forecast can be distinguished as entirely superior on the BSE. (Less)
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author
Augustsson, Viktor LU
supervisor
organization
course
NEKN01 20142
year
type
H1 - Master's Degree (One Year)
subject
keywords
MRS-GARCH, Out of Sample Evaluation, DM Test, Bombay Sensex, Standard & Poor's 500
language
English
id
4739052
date added to LUP
2014-11-03 14:57:41
date last changed
2014-11-03 14:57:41
@misc{4739052,
  abstract     = {Forecasting volatility is a fundamental topic in in both academic and applied financial economics. Different GARCH-specifications are by far the most popular model based approach used for this purpose. This thesis evaluates the forecast accuracy of some specific GARCH-models; GARCH, EGARCH, APGARCH and MRS-GARCH. The primary purpose of the essay is to investigate whether the more flexible two-regime MRS-GARCH model outperforms the more conventional one-regime GARCH models in a very volatile time period during the recent financial crises. The evaluation period stretches from the day when Lehman Brothers went bankrupt and one year ahead. Each model is evaluated using two indexes with different characteristics; the Standard & Poor 500 and the Bombay Sensex index. The result shows that the MRS-GARCH models are superior in predictive ability on S&P500 compared to the other tested models. Conversely, the overall relative performance accuracy of the BSE is less clear-cut since none of the tested models seem to perform particularly well. Generally, the results indicate that the MRS-GARCH provides better forecasts on S&P 500 compared to the other models and that no forecast can be distinguished as entirely superior on the BSE.},
  author       = {Augustsson, Viktor},
  keyword      = {MRS-GARCH,Out of Sample Evaluation,DM Test,Bombay Sensex,Standard & Poor's 500},
  language     = {eng},
  note         = {Student Paper},
  title        = {Evaluating Switching GARCH Volatility Forecasts During the Recent Financial Crisis},
  year         = {2014},
}