Empirical Analysis of the Market Risk of Chinese Open-Ended Funds Based on GARCH-VaR Models

2009 ◽  
Author(s):  
Jian Wang ◽  
Xiaotao Wu ◽  
Mingli Zhong
Keyword(s):  
Empirical Analysis ◽  
Market Risk ◽  
Var Models

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.

Market risk in carbon market: an empirical analysis of the EUA and sCER

2014 ◽  
Vol 75 (S2) ◽  
pp. 333-346 ◽  
Author(s):  
Bao-jun Tang ◽  
Cheng Shen ◽  
Yi-fan Zhao
Keyword(s):  
Empirical Analysis ◽  
Market Risk ◽  
Carbon Market

Part III Investment Banking, 13 Trading Book—Standardized Approaches

2018 ◽  
Author(s):  
Gleeson Simon
Keyword(s):  
Default Risk ◽  
Investment Banking ◽  
Market Risk ◽  
Expected Shortfall ◽  
Capital Adequacy ◽  
Third Party ◽  
Regulatory Capital ◽  
Var Models ◽  
Risk Models ◽  
Basel 3

This chapter discusses trading book models. Risk models come in a variety of types. However, for market risk purposes there have been a number of types which may be used within the framework. The simplest is the ‘CAD 1’ model — named after the first Capital Adequacy Directive, which permitted such models to be used in the calculation of regulatory capital. VaR models, permitted by Basel 2, were more complex, and this complexity was increased by Basel 2.5, which required the use of ‘stressed VAR’. In due course all of this will be replaced by the Basel 3 FRTB calculation, which rejects VAR and is based on the calculation of an expected shortfall (ES) market risk charge, a VaR based default risk charge (DRC) (for those exposures where the bank is exposed to the default of a third party), and a stressed ES-based capital add-on.

Selection of Value-at-Risk models for MENA Islamic indices

2020 ◽  
Vol 11 (9) ◽  
pp. 1689-1708
Author(s):  
Wassim Ben Ayed ◽  
Ibrahim Fatnassi ◽  
Abderrazak Ben Maatoug
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Prediction Models ◽  
Market Risk ◽  
Parametric Models ◽  
Arch Model ◽  
Var Models ◽  
Content Type ◽  
Cent Level

Purpose The purpose of this study is to investigate the performance of Value-at-Risk (VaR) models for nine Middle East and North Africa Islamic indices using RiskMetrics and VaR parametric models. Design/methodology/approach The authors test the performance of several VaR models using Kupiec and Engle and Manganelli tests at 95 and 99 per cent levels for long and short trading positions, respectively, for the period from August 10, 2006 to December 14, 2014. Findings The authors’ findings show that the VaR under Student and skewed Student distribution are preferred at a 99 per cent level VaR. However, at 95 per cent level, the VaR forecasts obtained under normal distribution are more accurate than those generated using models with fat-tailed distributions. These results suggest that VaR is a good tool for measuring market risk. The authors support the use of RiskMetrics during calm periods and the asymmetric models (Generalized Autoregressive Conditional Heteroskedastic and the Asymmetric Power ARCH model) during stressed periods. Practical implications These results will be useful to investors and risk managers operating in Islamic markets, because their success depends on the ability to forecast stock price movements. Therefore, because a few Islamic financial institutions use internal models for their capital calculations, the regulatory committee should enhance market risk disclosure. Originality/value This study contributes to the knowledge in this area by improving our understanding of market risk management for Islamic assets during the stress periods. Then, it highlights important implications regarding financial risk management. Finally, this study fills a gap in the literature, as most empirical studies dealing with evaluating VaR prediction models have focused on quantifying the model risk in the conventional market.

scholarly journals The Prudent Investor Rule and Market Risk: An Empirical Analysis

2017 ◽  
Vol 14 (1) ◽  
pp. 129-168 ◽  
Author(s):  
Max M. Schanzenbach ◽  
Robert H. Sitkoff
Keyword(s):  
Empirical Analysis ◽  
Market Risk ◽  
Prudent Investor Rule

scholarly journals Market Risk Analysis of Energy in Vietnam

Risks ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 112 ◽  
Author(s):  
Ngoc Phu Tran ◽  
Thang Cong Nguyen ◽  
Duc Hong Vo ◽  
Michael McAleer
Keyword(s):  
At Risk ◽  
Economic Development ◽  
Empirical Evidence ◽  
Empirical Analysis ◽  
Value At Risk ◽  
Oil And Gas ◽  
Market Risk ◽  
Conditional Value At Risk ◽  
Key Industries ◽  
The Empirical Analysis

The purpose of this paper is to evaluate and estimate market risk for the ten major industries in Vietnam. The focus of the empirical analysis is on the energy sector, which has been designated as one of the four key industries, together with services, food, and telecommunications, targeted for economic development by the Vietnam Government through to 2020. The oil and gas industry is a separate energy-related major industry, and it is evaluated separately from energy. The data set is from 2009 to 2017, which is decomposed into two distinct sub-periods after the Global Financial Crisis (GFC), namely the immediate post-GFC (2009–2011) period and the normal (2012–2017) period, in order to identify the behavior of market risk for Vietnam’s major industries. For the stock market in Vietnam, the website used in this paper provided complete and detailed data for each stock, as classified by industry. Two widely used approaches to measure and analyze risk are used in the empirical analysis, namely Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). The empirical findings indicate that Energy and Pharmaceuticals are the least risky industries, whereas oil and gas and securities have the greatest risk. In general, there is strong empirical evidence that the four key industries display relatively low risk. For public policy, the Vietnam Government’s proactive emphasis on the targeted industries, including energy, to achieve sustainable economic growth and national economic development, seems to be working effectively. This paper presents striking empirical evidence that Vietnam’s industries have substantially improved their economic performance over the full sample, moving from relatively higher levels of market risk in the immediate post-GFC period to a lower risk environment in a normal period several years after the end of the calamitous GFC.

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