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on Risk Management |
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Issue of 2016‒03‒17
twenty papers chosen by |
| By: | Dominique Guegan (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Bertrand K. Hassani (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique); Kehan Li (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | The financial industry has extensively used quantile-based risk measures relying on the Value-at-Risk (VaR). They need to be estimated from relevant historical data set. Consequently, they contain uncertainty. We propose an alternative quantile-based risk measure (the Spectral Stress VaR) to capture the uncertainty in the historical VaR approach. This one provides flexibility to the risk manager to implement prudential regulatory framework. It can be a VaR based stressed risk measure. In the end we propose a stress testing application for it. |
| Keywords: | Prudential financial regulation,Stress risk measure,Tail risk measure,Historical method,Uncertainty,Value-at-Risk,Stress testing |
| Date: | 2016–01 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-01277880&r=rmg |
| By: | Zura Kakushadze; Willie Yu |
| Abstract: | We give complete algorithms and source code for constructing statistical risk models, including methods for fixing the number of risk factors. One such method is based on eRank (effective rank) and yields results similar to (and further validates) the method set forth in an earlier paper by one of us. We also give a complete algorithm and source code for computing eigenvectors and eigenvalues of a sample covariance matrix which requires i) no costly iterations and ii) the number of operations linear in the number of returns. The presentation is intended to be pedagogical and oriented toward practical applications. |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1602.08070&r=rmg |
| By: | Matthias Leiss; Heinrich H. Nax |
| Abstract: | Foster and Hart (2009) introduce an objective measure of the riskiness of an asset that implies a bound on how much of one’s wealth is ‘safe’ to invest in the asset while (a.s.) guaranteeing no-bankruptcy in the long run. In this study, we translate the Foster-Hart measure from static and abstract gambles to dynamic and applied finance using nonparametric estimation of risk-neutral densities from S&P 500 call and put option prices covering 2003 to 2013. This exercise results in an option-implied market view of objective riskiness. The dynamics of the resulting ‘option-implied Foster-Hart bound’ are analyzed and assessed in light of well-known risk measures including value at risk, expected shortfall and risk-neutral volatility. The new measure is shown to be a significant predictor of ahead-return downturns. Furthermore, it is able to grasp more characteristics of the risk-neutral probability distributions than other measures, furthermore exhibiting predictive consistency. The robustness of the risk-neutral density estimation method is analyzed via a bootstrap. |
| Keywords: | risk measure; risk dynamics; risk-neutral densities; vaue at risk; expected shortfall |
| JEL: | D81 D84 G32 |
| Date: | 2015–11–12 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:65446&r=rmg |
| By: | Paola Cerchiello (Department of Economics and Management, University of Pavia); Paolo Giudici (Department of Economics and Management, University of Pavia); Giancarlo Nicola (Department of Economics and Management, University of Pavia) |
| Abstract: | A very important area of financial risk management is systemic risk modelling,which concerns the estimation of the interrelationships between financial institutions, with the aim of establishing which of them are more central and, therefore, more contagious/subject to contagion. The aim of this paper is to develop a systemic risk model which, differently from existing ones, employs not only the information contained in financial market prices, but also big data coming from financial tweets. From a methodological viewpoint, we propose a new framework, based on graphical models, that can estimate systemic risks with models based on two different sources: financial markets and financial tweets, and suggest a way to combine them, using a Bayesian approach. From an applied viewpoint, we present the first systemic risk model based on big data, and show that such a model can shed further light on the interrelationships between financial institutions. This can help predicting the level of returns of a bank, conditionally on the others, for example when a shock occurs in another bank, or exogeneously. |
| Keywords: | Financial Risk Management, Graphical models, Systemic risks, Twitter data analysis |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:pav:demwpp:demwp0117&r=rmg |
| By: | Dilip Kumar (Indian Institute of Management Kashipur) |
| Abstract: | We provide a framework based on the unbiased extreme value volatility estimator (Namely, the AddRS estimator) to compute and predict the long position and a short position VaR, henceforth referred to as the ARFIMA-AddRS-SKST model. We evaluate its VaR forecasting performance using the unconditional coverage test and the conditional coverage test for long and short positions on four global indices (S&P 500, CAC 40, IBOVESPA and S&P CNX Nifty) and compare the results with that of a bunch of alternative models. Our findings indicate that the ARFIMA-AddRS-SKST model outperforms the alternative models in predicting the long and short position VaR. Finally, we examine the economic significance of the proposed framework in estimating and predicting VaR using Lopez loss function approach so as to identify the best model that provides the least monetary loss. Our findings indicate that the VaR forecasts based on the ARFIMA-AddRS-SKST model provides the least total loss for various x% long and short positions VaR and this supports the superior properties of the proposed framework in forecasting VaR more accurately. |
| Keywords: | Extreme value volatility estimator; Value-at-risk; Skewed Student t distribution; Risk management. |
| JEL: | C22 C53 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iefpro:3205528&r=rmg |
| By: | Coppens, François; Mayer, Manuel; Millischer, Laurent; Resch, Florian; Sauer, Stephan; Schulze, Klaas |
| Abstract: | When back-testing the calibration quality of rating systems two-sided statistical tests can detect over- and underestimation of credit risk. Some users though, such as risk-averse investors and regulators, are primarily interested in the underestimation of risk only, and thus require one-sided tests. The established one-sided tests are multiple tests, which assess each rating class of the rating system separately and then combine the results to an overall assessment. However, these multiple tests may fail to detect underperformance of the whole rating system. Aiming to improve the overall assessment of rating systems, this paper presents a set of one-sided tests, which assess the performance of all rating classes jointly. These joint tests build on the method of Sterne [1954] for ranking possible outcomes by probability, which allows to extend back-testing to a setting of multiple rating classes. The new joint tests are compared to the most established one-sided multiple test and are further shown to outperform this benchmark in terms of power and size of the acceptance region. JEL Classification: C12, C52, G21, G24 |
| Keywords: | back-testing, credit ratings, one-sided, probability of default |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20161885&r=rmg |
| By: | Alejandro Balbás; Beatriz Balbás; Raquel Balbás |
| Abstract: | VaR minimization is a complex problem playing a critical role in many actuarial and financial applications of mathematical programming. The usual methods of convex programming do not apply due to the lack of sub-additivity. The usual methods of diferentiable programming do not apply either, due to the lack of continuity. Taking into account that the CVaR may be given as an integral of VaR, one has that VaR becomes a first order mathematical derivative of CVaR. This property will enable us to give accurate approximations in VaR optimization, since the optimization VaR and CVaR will become quite closely related topics. Applications in both finance and insurance will be given. |
| Keywords: | VaR Optimization , CVaR Sensitivity , Approximation Methods , Optimality Conditions , Actuarial and Financial Applications |
| JEL: | C02 C61 G11 G22 |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:cte:idrepe:id-16-01&r=rmg |
| By: | Delphine Lautier (DRM - Dauphine Recherches en Management - Université Paris IX - Paris Dauphine - CNRS - Centre National de la Recherche Scientifique); Julien Ling (DRM - Dauphine Recherches en Management - Université Paris IX - Paris Dauphine - CNRS - Centre National de la Recherche Scientifique); Franck Raynaud (EPFL - Ecole Polytechnique Fédérale de Lausanne - EPFL - Ecole Polytechnique Fédérale de Lausanne) |
| Abstract: | We examine the impact, on commodity derivative markets, of two financial crises: the Subprime crisis and the bankruptcy of Lehman Brothers. These crises are "external" for commodity markets: they appeared in the financial sphere. Still, because now commodity markets are highly integrated, between themselves and with other financial markets, such events could have had an impact. In order to fully comprehend this possible impact, we examine prices fluctuations in three dimensions: the observation time, the space dimension – the same underlying asset can be traded simultaneously in two different places – and the maturity of the transactions. We first focus on the efficiency of the shocks propagation: does it improve during crises? Then we concentrate on the paths of shocks propagation: are they modified? How? Finally we focus on the centrality of the prices system: does it change? Does it increase? |
| Keywords: | Commodity markets,Financial markets,Derivative markets,Market integration,Crises,Graph theory,Minimum spanning tree,Centrality |
| Date: | 2014–05 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01275562&r=rmg |
| By: | Santiago Gamba Santamaría; Oscar Fernando Jaulín Méndez; Luis Fernando Melo Velandia; Carlos Andrés Quicazán Moreno |
| Abstract: | Value at Risk (VaR) is a market risk measure widely used by risk managers and market regulatory authorities. There is a variety of methodologies proposed in the literature for the estimation of VaR. However, few of them get to say something about its distribution or its confidence intervals. This paper compares different methodologies for computing such intervals. Several methods, based on asymptotic normality, extreme value theory and subsample bootstrap, are used. Using Monte Carlo simulations, it is found that these approaches are only valid for high quantiles. In particular, there is a good performance for VaR (99%), in terms of coverage rates, and bad performance for VaR (95%) and VaR (90%). The results are confirmed by an empirical application for the stock market index returns of G7 countries. |
| Keywords: | Value at Risk, confidence intervals, data tilting, subsample bootstrap. |
| JEL: | C51 C52 C53 G32 |
| Date: | 2016–02–24 |
| URL: | http://d.repec.org/n?u=RePEc:col:000094:014263&r=rmg |
| By: | Martin Bruns; Tigran Poghosyan |
| Abstract: | Early warning systems (EWS) are widely used for assessing countries’ vulnerability to fiscal distress. Most EWS employ a specific set of only fiscal leading indicators predetermined by the researchers, which casts doubt on their robustness. We revisit this issue by using the Extreme Bound Analysis, which allows identifying robust leading indicators of fiscal distress from a large set. Consistent with the theoretical predictions of latest generation crisis models, we find that both fiscal (e.g., fiscal balance, foreign exchange debt) and non-fiscal leading indicators (e.g., output, FX reserves, current account balance, and openness) are robust. In addition, we find that a fiscal vulnerability indicator based on fiscal and non-fiscal leading indicators offers a 29% gain in predictive power compared to a traditional one based on fiscal leading indicators only. It also has good predictive power out of sample, with 78 percent of crises predicted correctly and only 34 percent false alarms issued for the period 2008–15. This suggests that both fiscal and non-fiscal leading indicators should be taken into account when assessing country’s vulnerability to fiscal distress. |
| Date: | 2016–02–15 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:16/28&r=rmg |
| By: | Tariq Aziz (Department of Business Administration, Aligarh Muslim University); Valeed Ahmad Ansari (Department of Business Administration, Aligarh Muslim University) |
| Abstract: | The relation between idiosyncratic risk and stock returns is currently a topic of debate in the academic literature. So far the evidence regarding the relation is mixed. This study aims to investigate the cross-sectional relation between idiosyncratic risk and stock returns in the Indian stock market employing quantile regressions. Using quantile regressions, this study demonstrates that idiosyncratic volatility and stock returns relation is quantile dependent. The relation between idiosyncratic volatility and stock returns is parabolic. The high idiosyncratic risk is associated with high (low) excess returns at the upper (lower) quantile of the conditional distribution. This partially explains the inconclusive evidence on the idiosyncratic volatility and the stock returns relation in the literature. |
| Keywords: | idiosyncratic volatility; quantile regression; asset pricing; emerging markets; India, |
| JEL: | G12 C14 C21 |
| URL: | http://d.repec.org/n?u=RePEc:sek:iefpro:3205769&r=rmg |
| By: | Ashraf Khan |
| Abstract: | This paper argues that nonfinancial risk management is an essential element of good governance of central banks. It provides a funnelled analysis, on the basis of selected literature, by (i) presenting an outline of central bank governance in general; (ii) zooming in on internal governance and organization issues of central banks; (iii) highlighting the main issues with nonfinancial risk management; and (iv) ending with recommendations for future work. It shows how attention for nonfinancial risk management has been growing, and how this has amplified the call for better governance of central banks. It stresses that in the area of nonfinancial risk management there are no crucial differences between commercial and central banks: both have people, processes, procedures, and structures. It highlights policy areas to be explored. |
| Date: | 2016–02–23 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:16/34&r=rmg |
| By: | Jacopo Corbetta; Ilaria Peri |
| Abstract: | A new risk measure, the lambda value at risk (Lambda VaR), has been recently proposed from a theoretical point of view as a generalization of the value at risk (VaR). The Lambda VaR appears attractive for its potential ability to solve several problems of the VaR. In this paper we propose three nonparametric backtesting methodologies for the Lambda VaR which exploit different features. Two of these tests directly assess the correctness of the level of coverage predicted by the model. One of these tests is bilateral and provides an asymptotic result. A third test assess the accuracy of the Lambda VaR that depends on the choice of the P&L distribution. However, this test requires the storage of more information. Finally, we perform a backtesting exercise and we compare our results with the ones from Hitaj and Peri (2015) |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1602.07599&r=rmg |
| By: | Justine Pedrono (Aix-Marseille University (AMSE), CNRS & EHESS); Aurélien Violon (Banque de France - ACPR) |
| Abstract: | Multinational Corporation (MNCs) should gain advantage from international diversification by lowering their systemic risk and reducing their bankruptcy cost. Hence, internationalization should induce larger leverage. However, it may imply additional agency costs due to wider informal gaps and higher cost of investigation induced by the multiplication of markets. To examine how currency diversification of asset may change the bank’s systemic risk, we provide a theoretical framework based on relative CAPM by introducing explicitly the exchange rate risk. Due to exchange rate dynamics asset diversification may reduce systemic risk even through the two assets are perfectly correlated. Using innovative micro data on credit institutions located in France between 1999 and 2014 we expand our analysis to the net effect of US dollar diversification of assets. Contrary to past studies, this measure of financial internationalization take into consideration the exchange rate risk. Although our results highlight the two opposite effects of diversification, they posit the importance of international agency costs in the capital structure decision. |
| Keywords: | Bank, Capital structure, Leverage, Currency, Diversification, Internationalization. |
| JEL: | F3 F4 G15 |
| Date: | 2016–01–28 |
| URL: | http://d.repec.org/n?u=RePEc:aim:wpaimx:1610&r=rmg |
| By: | Santiago Gamba Santamaría (Universidad Javeriana); Oscar Fernando Jaulín Méndez (Banco de la República de Colombia); Luis Fernando Melo Velandia (Banco de la República de Colombia); Carlos Andrés Quicazán Moreno (Banco de la República de Colombia) |
| Abstract: | Value at Risk (VaR) is a market risk measure widely used by risk managers and market regulatory authorities. There is a variety of methodologies proposed in the literature for the estimation of VaR. However, few of them get to say something about its distribution or its confidence intervals. This paper compares different methodologies for computing such intervals. Several methods, based on asymptotic normality, extreme value theory and subsample bootstrap, are used. Using Monte Carlo simulations, it is found that these approaches are only valid for high quantiles. In particular, there is a good performance for VaR (99%), in terms of coverage rates, and bad performance for VaR (95%) and VaR (90%). The results are confirmed by an empirical application for the stock market index returns of G7 countries. Classification JEL:C51, C52, C53, G32. |
| Keywords: | Value at Risk, confidence intervals, data tilting, subsample bootstrap. |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:bdr:borrec:927&r=rmg |
| By: | Frédéric Teulon; Khaled Guesmi; Salma Fattoum |
| Date: | 2016–02–18 |
| URL: | http://d.repec.org/n?u=RePEc:ipg:wpaper:2014-89&r=rmg |
| By: | Natalya Martynova; Lev Ratnovski; Razvan Vlahu |
| Abstract: | Traditional theory suggests that more profitable banks should have lower risk-taking incentives. Then why did many profitable banks choose to invest in untested financial instruments before the crisis, realizing significant losses? We attempt to reconcile theory and evidence. In our setup, banks are endowed with a fixed core business. They take risk by levering up to engage in risky ‘side activities’(such as market-based investments) alongside the core business. A more profitable core business allows a bank to borrow more and take side risks on a larger scale, offsetting lower incentives to take risk of given size. Consequently, more profitable banks may have higher risk-taking incentives. The framework is consistent with cross-sectional patterns of bank risk-taking in the run up to the recent financial crisis. |
| Keywords: | Bank capital;Profit margins;Profits;Financial risk;Debt;Banks;Risk-Taking, Repo Markets, Crises, bank, risk, bank risk, capital, Government Policy and Regulation, Crises., |
| Date: | 2015–11–25 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:15/249&r=rmg |
| By: | Anthony H. Tu; Cathy Yi-Hsuan Chen; ; |
| Abstract: | This paper first develops a new approach, which is based on the Nelson-Siegel term structure factor-augmented model, to compute the VaR of bond portfolios. We then applied the model to examine whether information contained on macroeconomic variables and financial shocks can help to explain the variations of VaR. A principal component analysis is used to incorporate the information contained in different variables. The empirical result shows that, including macroeconomic variables and financial shocks in the Nelson-Siegel term structure factor model, we can observe an obvious tendency towards better VaR forecasting performance. Moreover, the impact of incorporating financial shocks seems to be stronger than that of incorporating macroeconomic variables. |
| Keywords: | Nelson-Siegel factor model; Value-at-risk; Encompassing test; Backtesting; Conditional predictive ability |
| JEL: | G11 |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2016-006&r=rmg |
| By: | Andr\'es Riquelme; Marcela Parada |
| Abstract: | In this paper I show how reliable estimates of the Value of a Statistical Life (VSL) can be obtained using cross sectional data using Garen's instrumental variable (IV) approach. The increase in the range confidence intervals due to the IV setup can be reduced by a factor of 3 by using a proxy to risk attitude. In order state the "precision" of the cross sectional VSL estimates I estimate the VSL using Chilean panel data and use them as benchmark for different cross sectional specifications. The use of the proxy eliminates need for using hard-to-find instruments for the job risk level and narrows the confidence intervals for the workers in the Chilean labor market for the year 2009. |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1603.00568&r=rmg |
| By: | Marek Zinecker (Brno University of Technology, Czech Republic); Adam P. Balcerzak (Nicolaus Copernicus University, Poland); Marcin Faldziñski (Nicolaus Copernicus University, Poland); Michal Bernad Pietrzak (Nicolaus Copernicus University, Poland); Tomáš Meluzín (Brno University of Technology, Czech Republic) |
| Abstract: | The phenomenon of growing capital market linkages is a significant exogenous factor affecting the effectiveness of national economic policies and risk management processes in enterprises. As a result the identification of interdependencies among capital markets is important both from the macro and microeconomic perspective. In this context the main aim of this article is to examine the relations among capital markets of Poland, Czech Republic and Germany. In the research DCC-GARCH model with the t-student conditional distribution was applied. The analysis was conducted for the years 1997-2015. The research findings confirmed significant interdependencies among analysed capital markets, which were evaluated here by conditional correlations. |
| Keywords: | interdependences among capital markets, conditional variance and correlations, DCC-GARCH model |
| JEL: | G15 C58 |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:pes:wpaper:2016:no4&r=rmg |