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A study incorporating skewness in Expected Shortfall Estimation

Prajeesh, Sreeja Madhavi LU (2021) NEKN02 20202
Department of Economics
Abstract
Expected Shortfall has become a prominent risk measure after the global financial
crisis which hit the economy in 2007. This master thesis examines whether Expected Shortfall (ES) estimation gives better estimates when we incorporate skewness and the impact during turbulent versus tranquil period. This specific analysis scrutinized daily total returns (TR) of three Indexes: Standard & Poor 500 (S&P 500), US benchmark 10 year DS GOVT index (BMUS10Y), and S&P GSCI Gold Total Return - RETURN IND (GSGCTOT). The sample for the estimation was from Jan 2000 to end of Dec 2019, which embrace a turbulent as well as a tranquil period. The Value at Risk (VaR) and Expected Shortfall (ES) forecasts was done with different distributions and evaluated... (More)
Expected Shortfall has become a prominent risk measure after the global financial
crisis which hit the economy in 2007. This master thesis examines whether Expected Shortfall (ES) estimation gives better estimates when we incorporate skewness and the impact during turbulent versus tranquil period. This specific analysis scrutinized daily total returns (TR) of three Indexes: Standard & Poor 500 (S&P 500), US benchmark 10 year DS GOVT index (BMUS10Y), and S&P GSCI Gold Total Return - RETURN IND (GSGCTOT). The sample for the estimation was from Jan 2000 to end of Dec 2019, which embrace a turbulent as well as a tranquil period. The Value at Risk (VaR) and Expected Shortfall (ES) forecasts was done with different distributions and evaluated with back testing procedures. However, skewed t-distribution elucidated the main research purpose. The empirical results, gives the idea that ES
estimates incorporating skewness helps by retrieving better estimates during turbulent period as well as during tranquil/normal period. (Less)
Please use this url to cite or link to this publication:
author
Prajeesh, Sreeja Madhavi LU
supervisor
organization
course
NEKN02 20202
year
type
H1 - Master's Degree (One Year)
subject
keywords
Value at Risk, Expected shortfall, normal distribution, student t-distribution, skewed student t-distribution.
language
English
id
9040527
date added to LUP
2021-03-11 12:18:26
date last changed
2021-03-11 12:18:26
@misc{9040527,
  abstract     = {{Expected Shortfall has become a prominent risk measure after the global financial
crisis which hit the economy in 2007. This master thesis examines whether Expected Shortfall (ES) estimation gives better estimates when we incorporate skewness and the impact during turbulent versus tranquil period. This specific analysis scrutinized daily total returns (TR) of three Indexes: Standard & Poor 500 (S&P 500), US benchmark 10 year DS GOVT index (BMUS10Y), and S&P GSCI Gold Total Return - RETURN IND (GSGCTOT). The sample for the estimation was from Jan 2000 to end of Dec 2019, which embrace a turbulent as well as a tranquil period. The Value at Risk (VaR) and Expected Shortfall (ES) forecasts was done with different distributions and evaluated with back testing procedures. However, skewed t-distribution elucidated the main research purpose. The empirical results, gives the idea that ES
estimates incorporating skewness helps by retrieving better estimates during turbulent period as well as during tranquil/normal period.}},
  author       = {{Prajeesh, Sreeja Madhavi}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{A study incorporating skewness in Expected Shortfall Estimation}},
  year         = {{2021}},
}