Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data

Degiannakis, Stavros; Potamia, Artemis

doi:10.1016/j.irfa.2016.10.008

Cited by 23 publications

(15 citation statements)

References 46 publications

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“…Working with daily data January 1993 and 2013, the author fits the data into three different non-linear long memory volatility models (FIGARCH, FIAPARCH, HYGARCH) and finds that for all three white metals, a Fractionally Integrated Asymmetric Power ARCH (FIAPARCH) model is best suited to capture their long memory, asymmetry and fat tails, outperforming the other models in predicting oneday-ahead VaR positions. Degiannakis and Potamia (2016) base their research on the recommendations of the Basel Committee on Banking Supervision and examine whether inter-day or intra-day model provide accurate predictions for reliable Valueat-Risk (VaR) and Expected Shortfall (ES) forecasts. Daily data for silver between the 3 rd of January 2000 and the 5 th of August 2015, indicates that a GARCH-skT model, relying on inter-day data, provides better results than a HAR-RV-skT model, as it satisifes most of the conditions implied in VaR and ES forecasting, but that it overall fails to provide accurate forecasts of the risk measures implied.…”

Section: Modeling Price Datamentioning

confidence: 99%

The financial economics of white precious metals — A survey

Vigne

Lucey

O’Connor

et al. 2017

International Review of Financial Analysis

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This article provides a review of the academic literature on the financial economics of silver, platinum and palladium. The survey covers the findings on a wide variety of topics relation to the White Precious Metals including Market Efficiency, Forecastability, Behavioral Findings, Diversification Benefits, Volatility Drivers, Macroeconomic Determinants, and their relationships with other assets.

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Section: Modeling Price Datamentioning

confidence: 99%

The financial economics of white precious metals — A survey

Vigne

Lucey

O’Connor

et al. 2017

International Review of Financial Analysis

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“…They analyzed the accuracy of VaR and ES at 95% and 99% level of confidence. Degiannakis & Potamia (2017) check the intraday reliability of VaR and ES predictions with the recommendations of basel committee of banking supervision. The multiple periods VaR and ES predictions are adequate for 95% level of confidence.…”

Section: Introductionmentioning

confidence: 99%

The Application of Value at Risk and Expected Shortfall as Controlling Mechanism of Systematic Risk of Pakistani Stock Market

Haque¹,

Nasir²

2018

Proceedings of the 9th Economics &Amp; Finance Conference, London

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Fama and French (1992) three factor and Fama and French (2014) five-factor Model estimated relevant idiosyncratic factors and CAPM beta as the systematic risk factor for stock returns' variations. Application of Value at Risk (VaR) and Expected Shortfall (ES) modified the risk management criteria. This study applies traditional one factor, three factor and five factor model on Pakistan's manufacturing companies. Compares and modifies the stated models while using VaR and ES as systematic risk factor and check the robustness of the significant extent of worst expected loss provided by VaR and ES by measuring 95% and 99% confidence levels and their impact on the stock returns. In comparison with traditional market risk factor, our findings are in favor of VaR and ES factor as it significantly affects the cross-sectional of excess stock returns and fulfills the criteria of risk aversion.

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“…Idiosyncratic risk factors prediction is under Model 14. The sensitivity of stock excess returns and idiosyncratic risk factors increases with the increase in the level of confidence of ES, which advocates the proposition of Degiannakis et al [31].…”

Section: Resultsmentioning

confidence: 80%

Optimisation of Time-Varying Asset Pricing Models with Penetration of Value at Risk and Expected Shortfall

et al. 2021

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This study aims to apply value at risk (VaR) and expected shortfall (ES) as time-varying systematic and idiosyncratic risk factors to address the downside risk anomaly of various asset pricing models currently existing in the Pakistan stock exchange. The study analyses the significance of high minus low VaR and ES portfolios as a systematic risk factor in one factor, three-factor, and five-factor asset pricing model. Furthermore, the study introduced the six-factor model, deploying VaR and ES as the idiosyncratic risk factor. The theoretical and empirical alteration of traditional asset pricing models is the study’s contributions. This study reported a strong positive relationship of traditional market beta, value at risk, and expected shortfall. Market beta pertains its superiority in estimating the time-varying stock returns. Furthermore, value at risk and expected shortfall strengthen the effects of traditional beta impact on stock returns, signifying the proposed six-factor asset pricing model. Investment and profitability factors are redundant in conventional asset pricing models.

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Multiple-days-ahead value-at-risk and expected shortfall forecasting for stock indices, commodities and exchange rates: Inter-day versus intra-day data

Cited by 23 publications

References 46 publications

The financial economics of white precious metals — A survey

The financial economics of white precious metals — A survey

The Application of Value at Risk and Expected Shortfall as Controlling Mechanism of Systematic Risk of Pakistani Stock Market

Optimisation of Time-Varying Asset Pricing Models with Penetration of Value at Risk and Expected Shortfall

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