Efficiently Backtesting Conditional Value-at-Risk and Conditional Expected Shortfall

Su, Qihui; Qin, Zhongling; Peng, Liang; Qin, Gengsheng

doi:10.1080/01621459.2020.1763804

Cited by 7 publications

(3 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Berinvestasi saham, selain memberikan keuntungan juga tidak terlepas dari adanya risiko yang mungkin terjadi selama melakukan investasi, sehingga diperlukan pengelolaan risiko [7]. Terdapat dua metode yang dapat digunakan untuk menganalisis risiko yaitu Metode Value at Risk (VaR) dan Expected Shortfall (ES) [18]. VaR adalah kerugian yang dapat ditoleransi dengan tingkat kepercayaan tertentu.…”

Section: Pendahuluanunclassified

Implementation of Jump Diffusion to Predict Stock Prices and Risk Analysis Using Value At Risk and Expected Shortfall (Case Study: PT. Indofood Sukses Makmur Tbk)

Seru,

Jannah,

Tandiangnga

2024

View full text Add to dashboard Cite

Stock prices often fluctuate; therefore, a model is needed to predict the stock price. One of the models that can be used to predict stock prices when experiencing a jump is Jump Diffusion. In addition to predicting, investment is inseparable from the risks that may be borne, so it is also necessary to measure risk. This study aims to implement the Jump Diffusion Model in predicting the stock price of PT Indofood Sukses Makmur Tbk and conduct a risk analysis of the prediction results using Value at Risk (VaR) and Expected Shortfall (ES). In this study, a model was obtained that was used to predict the share price of PT Indofood Sukses Makmur Tbk with a Mean Absolute Percentage Error (MAPE) value of 6.41%. This shows that the accuracy of the stock price prediction results is included in the very good category. In addition, the VaR value of the prediction results with a confidence level of 90%, 95%, and 99% is 0.0292, 0.0372, and 0.0523, and the ES value is 0.0402, 0.0474, and 0.0613.

show abstract

Section: Pendahuluanunclassified

Implementation of Jump Diffusion to Predict Stock Prices and Risk Analysis Using Value At Risk and Expected Shortfall (Case Study: PT. Indofood Sukses Makmur Tbk)

Seru,

Jannah,

Tandiangnga

2024

View full text Add to dashboard Cite

show abstract

“…When diagnosing the complete dependence structure, the effect of any remaining residual extremal dependence may be 'washed-out'. However, overlooked serial dependence in the extremes may be very harmful as it invalidates, e.g., the model's risk forecasts, such as VaR and ES forecasts (Su et al, 2021+). As pointed out above, misspecified risk forecasts are penalized under the Basel framework.…”

Section: Motivationmentioning

confidence: 99%

Extremal Dependence-Based Specification Testing of Time Series

Hoga¹

2021

Preprint

View full text Add to dashboard Cite

We propose a specification test for conditional location-scale models based on extremal dependence properties of the standardized residuals. We do so comparing the left-over serial extremal dependence-as measured by the pre-asymptotic tail copula-with that arising under serial independence at different lags. Our main theoretical resultsshow that the proposed Portmanteau-type test statistics have nuisance parameterfree asymptotic limits. The test statistics are easy to compute, as they only depend on the standardized residuals, and critical values are likewise easily obtained from the limiting distributions. This contrasts with extant tests (based, e.g., on autocorrelations of squared residuals), where test statistics depend on the parameter estimator of the model and critical values may need to be bootstrapped. We show that our test performs well in simulations. An empirical application to S&P 500 constituents illustrates that our test can uncover violations of residual serial independence that are not picked up by standard autocorrelation-based specification tests, yet are relevant when the model is used for, e.g., risk forecasting.

show abstract

“…Numerous empirical papers have tried to quantify risk during periods of stress using different VaR forecasting models (Gençay and Selçuk, 2004;Angelidis et al, 2007;Dimitrakopoulos et al, 2010;Slim et al, 2017;Su et al, 2021). Another area of the literature has analyzed the impact of new market risk measures on the occurrence of VaR models in the conventional market during the previous financial crisis (Rossignolo et al, 2012(Rossignolo et al, , 2013Burchi, PRR 2013;Prorokowski and Prorokowski, 2014;Drenovak et al, 2017) but their findings have generally been inconclusive.…”

Section: Introductionmentioning

confidence: 99%

The Basel 2.5 capital regulatory framework and the COVID-19 crisis: evidence from the ethical investment market

Ben Ayed,

Ben Hassen

2023

PRR

View full text Add to dashboard Cite

PurposeThis research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.Design/methodology/approachThis research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).FindingsThe main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.Research limitations/implicationsSince the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.Practical implicationsThe results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.Originality/valuePrevious studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.

show abstract

Efficiently Backtesting Conditional Value-at-Risk and Conditional Expected Shortfall

Cited by 7 publications

References 24 publications

Implementation of Jump Diffusion to Predict Stock Prices and Risk Analysis Using Value At Risk and Expected Shortfall (Case Study: PT. Indofood Sukses Makmur Tbk)

Implementation of Jump Diffusion to Predict Stock Prices and Risk Analysis Using Value At Risk and Expected Shortfall (Case Study: PT. Indofood Sukses Makmur Tbk)

Extremal Dependence-Based Specification Testing of Time Series

The Basel 2.5 capital regulatory framework and the COVID-19 crisis: evidence from the ethical investment market

Contact Info

Product

Resources

About