nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒02‒26
fifteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Risk Measure Estimates in Quiet and Turbulent Times:An Empirical Study By Rosnan, Chotard; Michel, Dacorogna; Marie, Kratz
  2. CDS spreads as an independent measure of credit risk By Kiesel, F.; Spohnholtz, J.
  3. FRM: a Financial Risk Meter based on penalizing tail events occurrence By Lining Yu; Wolfgang Karl Härdle; Lukas Borke; Thijs Benschop
  4. Optimal capital, regulatory requirements and bank performance in times of crisis: Evidence from France By O. de Bandt; B. Camara; A. Maitre; P. Pessarossi
  5. Dynamic Valuation of Weather Derivatives under Default Risk By CMaria Osipenko; Wolfgang Karl Härdle; ;
  6. Support for the SME Supporting Factor - Multi-country empirical evidence on systematic risk factor for SME loans By M. Dietsch; K. Düllmann; H. Fraisse; P. Koziol; C. Ott
  7. Capital Regulation: Less Really Can Be More When Incentives Are Socially Aligned By Joseph P. Hughes
  8. RiskAnalytics: an R package for real time processing of Nasdaq and Yahoo finance data and parallelized quantile lasso regression methods By Lukas Borke; ; ;
  9. The Anatomy of Financial Vulnerabilities and Crises By Seung Jung Lee; Kelly E. Posenau; Viktors Stebunovs
  10. Global Risk and Demand for Gold by Central Banks By Gopalakrishnan, Balagopal; Mohapatra, Sanket
  11. Firm-Related Risk and Precautionary Saving Response By Andreas Fagereng; Luigi Guiso; Luigi Pistaferri
  12. A self-calibrating method for heavy tailed data modeling : Application in neuroscience and finance By Nehla, Debbabi; Marie, Kratz; Mamadou , Mboup
  13. The Impact of Interest Rate Risk on Bank Lending By Toni Beutler; Robert Bichsel; Adrian Bruhin; Jayson Danton
  14. A Risk Economic Approach to Nuclear Power Generation:From Daniel Bernoulli to Keynes and Knight By Yasuhiro Sakai
  15. Earnings Volatility and Stock Returns: Event Study Evidence By Robson Glasscock; Korenok Oleg

  1. By: Rosnan, Chotard (CREAR - Center of Research in Econo-finance and Actuarial sciences on Risk / Centre de Recherche Econo-financière et Actuarielle sur le Risque); Michel, Dacorogna (SCOR SE); Marie, Kratz (Essec Business School)
    Abstract: In this study we empirically explore the capacity of historical VaR to correctly predict the future risk of a financial institution. We observe that rolling samples are better able to capture the dynamics of future risks. We thus introduce another risk measure, the Sample Quantile Process, which is a generalization of the VaR calculated on a rolling sample, and study its behavior as a predictor by varying its parameters. Moreover, we study the behavior of the future risk as a function of past volatility. We show that if the past volatility is low, the historical computation of the risk measure underestimates the future risk, while in period of high volatility, the risk measure overestimates the risk, confirming that the current way financial institutions measure their risk is highly procyclical.
    Keywords: backtest; risk measure; sample quantile process; stochastic model; VaR; volatility
    JEL: C13 C22 C52 C53 G01 G33
    Date: 2016–11
  2. By: Kiesel, F.; Spohnholtz, J.
    Abstract: Purpose The creditworthiness of corporates is most visible in credit ratings. This paper presents an alternative credit rating measure independently of credit rating agencies. The credit rating score is based on the CDS market trading. Design/methodology/approach A credit rating score is developed which is a linear function of logarithmized credit default swap (CDS) spreads. This new credit rating score is the first one completely independent of rating agency. The estimated ratings are compared with ratings provided by Fitch Ratings for 310 European and US non-financial corporates. Findings The empirical analysis shows that logarithmized CDS spreads and issuer credit ratings by agencies have a linear relationship. The new credit rating score provides market participants with an alternative risk assessment, which is solely based on market factors, and does not rely on credit rating analysts. The results indicate that our credit rating score is able to anticipate agency ratings in advance. Moreover, the analysis demonstrates that the trading volume has only limited influence in the anticipation of rating changes. Originality/value This study shows a new approach to measure the creditworthiness of firms by analyzing CDS spreads. This is highly relevant for regulation, firm monitoring, and investors.
    Date: 2017–02–15
  3. By: Lining Yu; Wolfgang Karl Härdle; Lukas Borke; Thijs Benschop
    Abstract: In this paper we propose a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter () of a linear quantile lasso regression. The FRM is calculated by taking the average of the penalization parameters over the 100 largest US publicly traded financial institutions. We demonstrate the suitability of this risk measure by comparing the proposed FRM to other measures for systemic risk, such as VIX, SRISK and Google Trends. We find that mutual Granger causality exists between the FRM and these measures, which indicates the validity of the FRM as a systemic risk measure. The implementation of this project is carried out using parallel computing, the codes are published on with keyword FRM. The R package RiskAnalytics is another tool with the purpose of integrating and facilitating the research, calculation and analysis methods around the FRM project. The visualization and the up-to-date FRM can be found on
    Keywords: Systemic Risk, Quantile Regression, Value at Risk, Lasso, Parallel Computing
    JEL: C21 C51 G01 G18 G32 G38
    Date: 2017–01
  4. By: O. de Bandt; B. Camara; A. Maitre; P. Pessarossi
    Abstract: The recent implementation of the Basel III framework has re-ignited the debate around the link between capital, performance and capital requirements in the banking sector. There is a dominant view in the earlier empirical literature in favor of a positive effect of capital on banking performance. Using panel data gathered for the supervision of French banks, we also find evidence of the beneficial effect of higher capital, but try to go one step further by distinguishing between regulatory and voluntary capital. Using a two-step estimation procedure, taking advantage of the variability of data since the crisis, and controlling for many factors (risk, asset composition, etc), we show that voluntary capital, i.e. capital held by banks irrespective of their regulatory requirements, turns out to be the sole component of capital that positively affects performance, as measured by the return on asset (ROA). In contrast, the effect of regulatory capital on the ROA appears insignificant, indicating that over the 2007-2014 period increasing capital requirements have not been detrimental to banking performance in France.
    Keywords: Bank capital; Performance; ROA, Capital requirements; Financial crisis.
    JEL: G01 G21 G28 G32
    Date: 2016
  5. By: CMaria Osipenko; Wolfgang Karl Härdle; ;
    Abstract: Weather derivatives are contingent claims with payo based on a pre-speci ed weather index. Firms exposed to weather risk can transfer it to nancial markets via weather derivatives. We develop a utility-based model for pricing baskets of weather derivatives in over-the-counter markets under counterparty default risk. In our model, agents maximise the expected utility of their terminal wealth, while they dynamically rebalance their weather portfolios over a nite investment horizon. Via partial market clearing, we obtain semi-closed forms for the equilibrium prices of weather derivatives and for the optimal strategies of the agents. We give an example on how to price rainfall derivatives on selected stations in China in the universe of a nancial investor and a weather exposed crop insurer.
    Keywords: derivative securities, asset pricing models
    Date: 2017–02
  6. By: M. Dietsch; K. Düllmann; H. Fraisse; P. Koziol; C. Ott
    Abstract: Using a unique and comprehensive data set on the two largest economies of the Eurozone – France and Germany – this paper first proceeds to a computation of the Gordy formula relaxing the ad hoc size-dependent constraints of the Basel formulas. Our study contributes to Article 501 of the Capital Requirements Regulation (CRR) requesting analysis the consistency of own funds requirements with the riskiness of SMEs. In both the French and the German sample, results suggest that the relative differences between the capital requirements for large corporates and those for SMEs (in other words the capital relief for SMEs) are lower in the Basel III framework than implied by empirically estimated asset correlations. Results show that the SME Supporting Factor in the CRR/CRDIV is able to compensate the difference between estimated and CRR/CRDIV capital requirements for loans in the corporate portfolio.
    Keywords: SME Supporting Factor, Asset correlation, Basel III, Minimum Capital requirements, Asymptotic Single Risk factor Model, SME finance.
    JEL: G21 G33 C13
    Date: 2016
  7. By: Joseph P. Hughes (Rutgers University)
    Abstract: Capital regulation has become increasingly complex as the largest financial institutions arbitrage differences in requirements across financial products to increase expected return for any given amount of regulatory capital, as financial regulators amend regulations to reduce arbitrage opportunities, and as financial institutions innovate to escape revised regulations – a regulatory dialectic. This increasing complexity makes monitoring bank risk-taking by markets and regulators more difficult and does not necessarily improve the risk sensitivity of measures of capital adequacy. Explaining the arbitrage incentive of some banks, several studies have found evidence of dichotomous capital strategies for maximizing value: a relatively low-risk strategy that minimizes the potential for financial distress to protect valuable investment opportunities and a relatively high-risk strategy that, in the absence distress costs due to valuable investment opportunities, “reaches for yield” to exploit the option value of implicit and explicit deposit insurance. In the latter case, market discipline rewards risk-taking and, in doing so, tends to undermine financial stability. The largest financial institutions, belonging to the latter category, maximize value by arbitraging capital regulations to “reach for yield.” This incentive can be curtailed by imposing “pre-financial-distress” costs that make less risky capital strategies optimal for large institutions. Such potential costs can be created by requiring institutions to issue contingent convertible debt (COCOs) that converts to equity to recapitalize the institution well before insolvency. The conversion rate significantly dilutes existing shareholders and makes issuing new equity a better than than conversion. The trigger for conversion is a particular market-value capital ratio. Thus, the threat of conversion tends to reverse risk-taking incentives – in particular, the incentive to increase financial leverage and to arbitrage differences in capital requirement across investments.
    Keywords: banking, capital regulation, contingent convertible debt
    JEL: G21 G28
    Date: 2017–02–22
  8. By: Lukas Borke; ; ;
    Abstract: In order to integrate and facilitate the research, calculation and analysis methods around the Financial Risk Meter (FRM) project, the R package RiskAnalytics has been developed. Its main goal is to provide data processing and parallelized quantile lasso regression methods for risk analysis based on NASDAQ data, Yahoo Finance data and some macro variables. The derived “Risk Analytics” can help to forecast and evaluate the systemic risk for the corresponding markets. The visualization and the up-to-date FRM can be found on Supplementary R codes are published on with the keyword FRM. The RiskAnalytics package is a convenient tool with the purpose of integrating lasso penalized quantile regression methods with full solution paths and cluster computing support around the topic “Risk Analytics and FRM”.
    Keywords: Risk Analytics, FRM, Data Analytics, Systemic Risk, Quantile Regression, Lasso, Value at Risk, Parallel and Cluster Computing, EDA, Data Visualization
    JEL: C21 C51 G01 G18 G32 G38
    Date: 2017–02
  9. By: Seung Jung Lee; Kelly E. Posenau; Viktors Stebunovs
    Abstract: We extend the framework used in Aikman, Kiley, Lee, Palumbo, and Warusawitharana (2015) that maps vulnerabilities in the U.S. financial system to a broader set of advanced and emerging economies. Our extension tracks a broader set of vulnerabilities and, therefore, captures signs of different types of crises. The typical anatomy of the evolution of vulnerabilities before and after a financial crisis is as follows. Pressures in asset valuations materialize, and a build-up of imbalances in the external, financial, and nonfinancial sectors follows. A financial crisis is typically followed by a build-up of sovereign debt imbalances as the government tries to deal with the consequences of the crisis. Our early warnings indicators which aggregate these vulnerabilities predict banking crises better than the Credit-to-GDP gap at long horizons. Our indicators also predict the severity of banking crises and the duration of recessions, as they take into account possible spill-over and amplification channels of financial stress to from one to another sector in the economy. Our indicators are of relevance for macroprudential and crisis management, in part, because they perform better than the Credit-to-GDP gap and do not suffer from the gaps econometric flaws.
    Keywords: Credit-to-GDP gap ; Crisis management ; Financial vulnerabilities ; Early warning system ; Financial crises ; Banking crises ; Currency crises ; Macroprudential policy
    JEL: C82 D14 G01 G12 G21 G23 G32 H63
    Date: 2017–02
  10. By: Gopalakrishnan, Balagopal; Mohapatra, Sanket
    Abstract: This paper examines the influence of global risk on the holding of gold by central banks based on annual data for 100 countries during 1990-2015. We use a dynamic panel generalized method of moments (GMM) model to estimate this effect, controlling for a variety of domestic factors. Consistent with portfolio diversification and perception of gold as a safe asset, we find that the gold holdings of central banks increase in response to higher global risk. This effect is larger for high-income countries than for developing countries. Moreover, greater capital account openness is associated with a stronger response of central banks’ gold holding to global risk, while a higher ratio of overall reserves to imports is associated with a weaker response. We also find evidence that the sensitivity depends on whether the currency regime followed is fixed or floating, with higher responsiveness in the case of fixed rate regimes. The baseline results are robust to alternate estimation methods, exclusion of crisis years, active and passive management of gold reserves and additional controls. These findings suggest that central banks adjust their gold holdings in response to changes in global risk conditions, with the magnitude of response depending on reserve management capacity and country-specific vulnerabilities.
  11. By: Andreas Fagereng; Luigi Guiso; Luigi Pistaferri
    Abstract: We propose a new approach to identify the strength of the precautionary motive and the extent of self-insurance in response to earnings risk based on Euler equation estimates. To address endogeneity problems, we use Norwegian administrative data and instrument consumption and earnings volatility with the variance of firm-specific shocks. The instrument is valid because firms pass some of their productivity shocks onto wages; moreover, for most workers firm shocks are hard to avoid. Our estimates suggest a coefficient of relative prudence of 2, in a very plausible range.
    JEL: D91 E21 J24
    Date: 2017–02
  12. By: Nehla, Debbabi (SUP'COM - Ecole Supérieure des Communications de Tunis); Marie, Kratz (Essec Business School); Mamadou , Mboup (CRESTIC - Centre de Recherche en Sciences et Technologies de l'Information et de la Communication)
    Abstract: One of the main issues in the statistical literature of extremes concerns the tail index estimation, closely linked to the determination of a threshold above which a Generalized Pareto Distribution (GPD) can be fi tted. Approaches to this estimation may be classfii ed into two classes, one using standard Peak Over Threshold (POT) methods, in which the threshold to estimate the tail is chosen graphically according to the problem, the other suggesting self-calibrating methods, where the threshold is algorithmically determined. Our approach belongs to this second class proposing a hybrid distribution for heavy tailed data modeling, which links a normal (or lognormal) distribution to a GPD via an exponential distribution that bridges the gap between mean and asymptotic behaviors. A new unsupervised algorithm is then developed for estimating the parameters of this model. The effectiveness of our self-calibrating method is studied in terms of goodness-of-fi t on simulated data. Then, it is applied to real data from neuroscience and fi nance, respectively. A comparison with other more standard extreme approaches follows.
    Keywords: Algorithm; Extreme Value Theory; Gaussian distribution; Generalized Pareto Distribution; Heavy tailed data; Hybrid model; Least squares optimization; Levenberg Marquardt algorithm; Neural data; S&P 500 index
    JEL: C02
    Date: 2016–12–12
  13. By: Toni Beutler; Robert Bichsel; Adrian Bruhin; Jayson Danton
    Abstract: In this paper, we empirically analyze the transmission of realized interest rate risk - the gain or loss in a bank's economic capital caused by movements in interest rates - to bank lending. We exploit a unique panel data set that contains supervisory information on the repricing maturity profiles of Swiss banks and provides us with an individual measure of interest rate risk exposure net of hedging. Our analysis yields two main results. First, the impact of an interest rate shock on bank lending significantly depends on the individual exposure to interest rate risk. The higher a bank's exposure to interest rate risk, the higher the impact of an interest rate shock on its lending. Our estimates indicate that a year after a permanent 1 percentage point upward shock in nominal interest rates, the average bank in 2013Q3 would, ceteris paribus, reduce its cumulative loan growth by approximately 300 basis points. An estimated 12.5% of the impact would result from realized interest rate risk weakening the bank's economic capital. Second, bank lending appears to be mainly driven by capital rather than liquidity, suggesting that a higher capitalized banking system can better shield its creditors from shocks in interest rates.
    Keywords: Interest Rate Risk, Bank Lending, Monetary Policy Transmission
    JEL: E44 E51 E52 G21
    Date: 2017
  14. By: Yasuhiro Sakai (Faculty of Economics, Shiga University)
    Abstract: This paper aims to discuss the problem of nuclear power generation from the viewpoint of the economics of risk and uncertainty. Although we have experienced the two major nuclear disasters, Chernobyl and Fukushima, in recent times, it is quite unfortunate that risk-economic studies in nuclear power generation have been extremely rare so far. This may show intentional neglect in the academic circle. The purpose of this paper is to duly mend such a regrettable tendency. Before 11 March 2011, there were many people who more or less believed in the myth of absolute safety. The Great East Japan Earthquake, however, has completely changed their concept of risk for nuclear power generation, thus requiring the need to take a new risk-economic approach to nuclear energy. As saying goes, we can learn new lessons in old teachings: we have to reexamine the economics of J.M. Keynes and Frank Knight. There are many possibilities for future research.
    Keywords: Risk, uncertainty, nuclear power generation, Keynes, Knight
  15. By: Robson Glasscock (University of Wyoming.); Korenok Oleg (Virginia Commonwealth University)
    Abstract: Executives admit to being fearful of being penalized for reporting volatile earnings. Many executives also state their willingness to sacrifice future economic benefits in order to report ÒsmootherÓ earnings. However, McInnis (2010) provides convincing evidence that earnings volatility is not a priced risk factor. This suggests the market does not respond to earnings volatility in the manner that many CFOs suppose. We re-examine this discrepancy using an event study to determine if the market responds negatively to earnings volatility. Similar to McInnis (2010), we are unable to find convincing evidence th at the market punishes volatile earnings.
    Keywords: Earnings volatility, earnings smoothness, event study
    JEL: G14 M41
    Date: 2017–03

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