This study examines and applies the three statistical value at risk models including variance-covariance, historical simulation, and Monte Carlo simulation in measuring market risk of VN-30 portfolio of Ho Chi Minh stock exchange (HOSE) in Vietnam stock market and some back-testing techniques in assessing the validity of the VaR performance in the timeframe of January 30, 2012–February 26, 2016. | 90 Nguyen Quang Thinh & Vo Thi Quy / Journal of Economic Development 24(2) 90-114 Applying three VaR approaches in measuring market risk of stock portfolio: The case study of VN-30 stock basket in HOSE NGUYEN QUANG THINH International University, Vietnam National University – Ho Chi Minh City – thinhnguyen23394@ VO THI QUY International University, Vietnam National University – Ho Chi Minh City – vtquy@ ARTICLE INFO ABSTRACT Article history: This study examines and applies the three statistical value at risk models including variance-covariance, historical simulation, and Monte Carlo simulation in measuring market risk of VN-30 portfolio of Ho Chi Minh stock exchange (HOSE) in Vietnam stock market and some back-testing techniques in assessing the validity of the VaR performance in the timeframe of January 30, 2012–February 26, 2016. The models are constructed from two volatility methods of stock price: SMA and EWMA throughout the five chosen confidence level: 90%, 93%, 95%, , and 99%. The findings of the study show that the differences among the results of three models are not significant. Additionally, three VaR (Value at Risk) models have generally the similar accepted range assessed in both types of back-tests at all confidence levels considered and at the confidence level. They can work best to achieve the highest validity level of results in satisfying both conditional and unconditional back-tests. The Monte Carlo Simulation (MCS) has been considered the most appropriate method to apply in the context of VN-30 portfolio due to its flexibility in distribution simulation. Recommendations for further research and investigations are provided accordingly. Received: Aug. 15, 2016 Received in revised form: Jan. 12, 2017 Accepted: Mar. 31, 2017 Keywords: Value at risk Market risk Stock portfolio Variance-covariance Historical simulation Monte Carlo simulation Nguyen Quang Thinh & Vo Thi Quy / Journal of Economic .
