Capturing value-at-risk in futures markets: a revised filtered historical simulation approach

2012 ◽  
Vol 6 (4) ◽  
pp. 67-93
Author(s):  
Chang-Cheng Changchien ◽  
Chu-Hsiung Lin ◽  
Wei-Shun Kao
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Futures Markets ◽  
Simulation Approach ◽  
Historical Simulation

scholarly journals Measuring Value at Risk for Kijang Emas Investment using Historical Simulation Approach

2019 ◽  
Vol 9 (9) ◽  
Author(s):  
Farah Azaliney Mohd Amin ◽  
Nurulhazwan Izmi Othman ◽  
Mohamad Khairil Amri Khairuddin ◽  
Muhammad Haikal Muhaimin Hazahar
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Simulation Approach ◽  
Historical Simulation

scholarly journals Measuring Market Risk of Commercial Banks Implementing VaR with Historical Simulation Approach

2021 ◽  
pp. 79-99
Author(s):  
Minhaz-Ul Haq
Keyword(s):  
Stock Prices ◽  
Commercial Banks ◽  
Value At Risk ◽  
First Generation ◽  
Market Risk ◽  
Jel Classification ◽  
Simulation Approach ◽  
Share Prices ◽  
Historical Simulation ◽  
The Impact

This paper attempts to picture the impact of the market risk of ten commercial banks located in Bangladesh with the help of a non-parametric model known as the Historical Simulation Approach over the course of eight years. These banks' daily stock prices were used as inputs and analyzed in Microsoft Excel by means of Percentile and LN function. The study revealed market risk exposure as third, second-and first-generation banks from the least to the highest. It also pointed out the ups and downs of these banks' share prices in the selected period. Further analysis showed the portfolio VaR estimation for different time intervals. JEL classification numbers: G32. Keywords: Value-at-risk, Historical Simulation, Market Risk, Confidence Interval.

What do the value-at-risk measure and the respective legislative framework really offer to financial stability? Critical views and pro-cyclicality

2020 ◽  
Vol 17 (1) ◽  
pp. 39-60
Author(s):  
Evangelos Vasileiou ◽  
Themistoclis Pantos
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Financial Stability ◽  
Financial Risk ◽  
Risk Measure ◽  
Counterparty Risk ◽  
Financial Industry ◽  
Historical Simulation ◽  
Statistical Measures ◽  
Legislative Framework

In this paper, we examine how value at risk (VaR) contributes to the financial market's stability. We apply the Guidelines on Risk Measurement and the Calculation of Global Exposure and Counterparty Risk for UCITS of the Committee of European Securities Regulators (CESR 2010) to the main indices of the 12 stock markets of the countries that have used the euro as their official currency since its initial circulation. We show that gaps in the legislative framework give incentives to investment funds to adopt conventional models for the VaR estimation in order to avoid the increased costs that the advanced models involve. For this reason, we apply the commonly used historical simulation VaR (HVaR) model, which is: (i) taught at most finance classes; (ii) widely applied in the financial industry; and (iii) accepted by CESR (2010). The empirical evidence shows the HVaR does not really contribute to financial stability, and the legislative framework does not offer the appropriate guidance. The HVaR model is not representative of the real financial risk, and does not give any signal for trends in the near future. The HVaR is absolutely backward-looking and this increases the stock market's overreaction. The fact that the suggested confidence level in CESR (2010) is set at 99 percent leads to hidden pro-cyclicality. Scholars and researchers should focus on issues such as the abovementioned, otherwise the VaR estimations will become, sooner or later, just a formality, and such conventional statistical measures rarely contribute to financial stability.

Sign in / Sign up

Export Citation Format

Share Document