Analyzing Stock Performance in the Banking Sector: Unveiling Value-at-Risk and Conditional Value-at-Risk Strategies
Keywords:
Value at risk, conditional value at risk, historical simulation approach, normal exponential weighted moving averageAbstract
This study explores stock ranking in the banking sector using Value at Risk (VaR) and Conditional Value at Risk (CVaR). The research focuses on bank stocks and employs the Normal Exponential Weighted Moving Average (EWMA) method for volatility calculation and the Historical Simulation Approach for model generation. Data from the Thai stock market’s banking sector, specifically the SET Finance index, is analyzed from January 1, 2017, to December 31, 2021, with confidence levels set at 95 % and 99 %. Model quality is assessed through the Violation Ratio, Three-zone Approach, and Normalized CVaR testing. The findings facilitate stock ranking and aid investors in risk estimation. Results reveal the ranking of banks based on VaR and CVaR, with Bank A identified as the highest-risk bank and Bank B as the lowest-risk bank. Two models, VaR using the Normal EWMA method at the 99% confidence level and CVaR using the Historical Simulation Approach at the 95%
and 99% confidence levels, pass the model quality testing and provide valuable insights for stock
ranking
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