Expected Shortfall – An Alternative Risk Measure to Value-at-Risk

2020 ◽  
Author(s):  
Shiu-Wah Chu ◽  
Ritabrata Bhattacharyya
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Measure ◽  
Expected Shortfall

A LIQUIDATION RISK ADJUSTMENT FOR VALUE AT RISK AND EXPECTED SHORTFALL

2018 ◽  
Vol 21 (03) ◽  
pp. 1850010 ◽  
Author(s):  
LAKSHITHE WAGALATH ◽  
JORGE P. ZUBELLI
Keyword(s):  
At Risk ◽  
Financial Institutions ◽  
Risk Adjustment ◽  
Value At Risk ◽  
Financial Institution ◽  
Risk Measures ◽  
Risk Measure ◽  
Expected Shortfall ◽  
Adjusted Risk ◽  
Risk Managers

This paper proposes an intuitive and flexible framework to quantify liquidation risk for financial institutions. We develop a model where the “fundamental” dynamics of assets is modified by price impacts from fund liquidations. We characterize mathematically the liquidation schedule of financial institutions and study in detail the fire sales resulting endogenously from margin constraints when a financial institution trades through an exchange. Our study enables to obtain tractable formulas for the value at risk and expected shortfall of a financial institution in the presence of fund liquidation. In particular, we find an additive decomposition for liquidation-adjusted risk measures. We show that such a measure can be expressed as a “fundamental” risk measure plus a liquidation risk adjustment that is proportional to the size of fund positions as a fraction of asset market depths. Our results can be used by risk managers in financial institutions to tackle liquidity events arising from fund liquidations better and adjust their portfolio allocations to liquidation risk more accurately.

scholarly journals An evaluation and comparison of Value at Risk and Expected Shortfall

2018 ◽  
Vol 15 (4) ◽  
pp. 17-34 ◽  
Author(s):  
Tom Burdorf ◽  
Gary van Vuuren
Keyword(s):  
At Risk ◽  
Monte Carlo ◽  
Emerging Economies ◽  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Expected Shortfall ◽  
Significance Level ◽  
Tail Conditional Expectation ◽  
The Uk

As a risk measure, Value at Risk (VaR) is neither sub-additive nor coherent. These drawbacks have coerced regulatory authorities to introduce and mandate Expected Shortfall (ES) as a mainstream regulatory risk management metric. VaR is, however, still needed to estimate the tail conditional expectation (the ES): the average of losses that are greater than the VaR at a significance level These two risk measures behave quite differently during growth and recession periods in developed and emerging economies. Using equity portfolios assembled from securities of the banking and retail sectors in the UK and South Africa, historical, variance-covariance and Monte Carlo approaches are used to determine VaR (and hence ES). The results are back-tested and compared, and normality assumptions are tested. Key findings are that the results of the variance covariance and the Monte Carlo approach are more consistent in all environments in comparison to the historical outcomes regardless of the equity portfolio regarded. The industries and periods analysed influenced the accuracy of the risk measures; the different economies did not.

scholarly journals Backtesting Marginal Expected Shortfall and Related Systemic Risk Measures

2020 ◽  
Author(s):  
Denisa Banulescu-Radu ◽  
Christophe Hurlin ◽  
Jérémy Leymarie ◽  
Olivier Scaillet
Keyword(s):  
At Risk ◽  
Financial Institutions ◽  
Systemic Risk ◽  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Expected Shortfall ◽  
Conditional Value At Risk ◽  
Finite Sample ◽  
Marginal Expected Shortfall

This paper proposes an original approach for backtesting systemic risk measures. This backtesting approach makes it possible to assess the systemic risk measure forecasts used to identify the financial institutions that contribute the most to the overall risk in the financial system. Our procedure is based on simple tests similar to those generally used to backtest the standard market risk measures such as value-at-risk or expected shortfall. We introduce a concept of violation associated with the marginal expected shortfall (MES), and we define unconditional coverage and independence tests for these violations. We can generalize these tests to any MES-based systemic risk measures such as the systemic expected shortfall (SES), the systemic risk measure (SRISK), or the delta conditional value-at-risk ([Formula: see text]CoVaR). We study their asymptotic properties in the presence of estimation risk and investigate their finite sample performance via Monte Carlo simulations. An empirical application to a panel of U.S. financial institutions is conducted to assess the validity of MES, SRISK, and [Formula: see text]CoVaR forecasts issued from a bivariate GARCH model with a dynamic conditional correlation structure. Our results show that this model provides valid forecasts for MES and SRISK when considering a medium-term horizon. Finally, we propose an early warning system indicator for future systemic crises deduced from these backtests. Our indicator quantifies how much is the measurement error issued by a systemic risk forecast at a given point in time which can serve for the early detection of global market reversals. This paper was accepted by Kay Giesecke, finance.

Expected shortfall or median shortfall

2014 ◽  
Vol 01 (01) ◽  
pp. 1450007 ◽  
Author(s):  
Steven Kou ◽  
Xianhua Peng
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Measure ◽  
Model Misspecification ◽  
Capital Requirements ◽  
Expected Shortfall ◽  
Banking Supervision ◽  
Tail Risk ◽  
Basel Committee ◽  
Distributional Robustness

In a recent consultative document, the Basel Committee on Banking Supervision suggests replacing Value-at-Risk (VaR) by expected shortfall (ES) for setting capital requirements for banks' trading books because ES better captures tail risk than VaR. However, besides ES, another risk measure called median shortfall (MS) also captures tail risk by taking into account both the size and likelihood of losses. We argue that MS is a better alternative than ES as a risk measure for setting capital requirements because: (i) MS is elicitable but ES is not; (ii) MS has distributional robustness with respect to model misspecification but ES does not; (iii) MS is easy to implement but ES is not.

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

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 394
Author(s):  
Adeel Nasir ◽  
Kanwal Iqbal Khan ◽  
Mário Nuno Mata ◽  
Pedro Neves Mata ◽  
Jéssica Nunes Martins
Keyword(s):  
At Risk ◽  
Asset Pricing ◽  
Stock Returns ◽  
Value At Risk ◽  
Expected Shortfall ◽  
Time Varying ◽  
Pricing Models ◽  
Asset Pricing Model ◽  
Asset Pricing Models ◽  
Market Beta

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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