Filtered Historical Simulation Value-at-Risk Models and Their Competitors

2015 ◽  
Author(s):  
Pedro Gurrola ◽  
David Murphy
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Models ◽  
Historical Simulation

scholarly journals Applying three VaR (value at risk) approaches in measuring market risk of stock portfolio: The case study of VN-30 stocks basket in HOSE

2017 ◽  
Vol 24 (02) ◽  
pp. 90-113
Author(s):  
Thinh Nguyen Quang ◽  
Quy Vo Thi
Keyword(s):  
At Risk ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Value At Risk ◽  
Stock Price ◽  
Stock Exchange ◽  
Market Risk ◽  
Risk Models ◽  
Historical Simulation ◽  
Back Testing

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 confi-dence level: 90%, 93%, 95%, 97.5%, 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 97.5% con-fidence 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 port-folio due to its flexibility in distribution simulation. Recommenda-tions for further research and investigations are provided according-ly.

scholarly journals EVALUATING MEASURES OF MARKET RISK IN CIRCUMSTANCES OF GLOBAL FINANCIAL CRISIS – EMPIRICAL EVIDENCE FROM FIVE COUNTRIES

2013 ◽  
Vol 1 ◽  
pp. 75-81
Author(s):  
Ivica Terzić ◽  
Marko Milojević
Keyword(s):  
Value At Risk ◽  
Global Financial Crisis ◽  
Market Risk ◽  
Var Models ◽  
Risk Models ◽  
Historical Simulation ◽  
Rolling Window ◽  
Independence Properties ◽  
Window Approach ◽  
Metrics Model

The purpose of this paper is to evaluate performance of value-at-risk (VaR) produced by two risk models: historical simulation and Risk Metrics. We perform three backtest: unconditional coverage, independence and conditional coverage. We present results on both VaR 1% and VaR 5% on a one-day horizon for the following indices: S&P 500, DAX, SAX, PX and Belex 15. Our results show that Historical simulation 500 days rolling window approach satisfies unconditional coverage for all tested indices, while Risk Metrics has many rejection cases. On the other hand Risk Metrics model satisfies independence backtest for three indices, while Historical simulation has rejected more times. Based on our strong criteria to accept accuracy of VaR models only if both unconditional coverage and independence properties are satisfied, results indicate that during the crisis period all tested VaR models underestimate the true level of market risk exposure.

scholarly journals Evaluating Value-at-Risk Models with Desk-Level Data

2011 ◽  
Vol 57 (12) ◽  
pp. 2213-2227 ◽  
Author(s):  
Jeremy Berkowitz ◽  
Peter Christoffersen ◽  
Denis Pelletier
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Models ◽  
Level Data

Selection of Value-at-Risk models

2003 ◽  
Vol 22 (4) ◽  
pp. 337-358 ◽  
Author(s):  
Mandira Sarma ◽  
Susan Thomas ◽  
Ajay Shah
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Models ◽  
Selection Of

A proposal for evaluating value-at-risk models

2000 ◽  
Vol 28 (3) ◽  
pp. 378-378
Author(s):  
Marta Korczak
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Models

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.

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