nep-rmg New Economics Papers
on Risk Management
Issue of 2011‒04‒30
sixteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Are realized volatility models good candidates for alternative Value at Risk prediction strategies? By Louzis, Dimitrios P.; Xanthopoulos-Sisinis, Spyros; Refenes, Apostolos P.
  2. Multivariate VaRs for Operational Risk Capital Computation : a Vine Structure Approach By Dominique Guegan; Bertrand Hassani
  3. Shadow banking and the dynamics of aggregate leverage: An application of the Kalman filter to cyclical leverage measures By Christian Calmès; Raymond Théoret
  4. Dynamic factor value-at-risk for large, heteroskedastic portfolios By Sirio Aramonte; Marius del Giudice Rodriguez; Jason J. Wu
  5. The Riskiness of Risk Models By Christophe Boucher; Bertrand Maillet
  6. Risk Management and Managerial Efficiency in Chinese Banks: A Network DEA Framework By Kent Matthews
  7. Robust capital regulation By Viral Acharya; Hamid Mehran; Til Schuermann; Anjan Thakor
  8. Macroeconomic Stress Testing and the Resilience of the Indian Banking System: A Focus on Credit Risk By Niyogi Sinha Roy, Tanima; Bhattacharya, Basabi
  9. Securitization, bank lending and credit quality: the case of Spain By Santiago Carbó-Valverde; David Marqués-Ibáñez; Francisco Rodríguez Fernández
  10. Stock Volatility During the Recent Financial Crisis By G. William Schwert
  11. Continuous Workout Mortgages By Robert J. Shiller; Rafal M. Wojakowski; M. Shahid Ebrahim; Mark B. Shackleton
  12. Modellierung von Aktienkursen im Lichte der Komplexitätsforschung By Benjamin Kauper; Karl-Kuno Kunze
  13. Use of put options as insurance By Bell, Peter
  14. The Variance Profile By Luati, Alessandra; Proietti, Tommaso; Reale, Marco
  15. Root's Barrier: Construction, Optimality and Applications to Variance Options By Alexander M. G. Cox; Jiajie Wang
  16. forecasting stochastic Volatility using the Kalman filter: An Application to Canadian Interest Rates and Price-Earnings Ratio By Francois-Éric Racicot; Raymond Théoret

  1. By: Louzis, Dimitrios P.; Xanthopoulos-Sisinis, Spyros; Refenes, Apostolos P.
    Abstract: In this paper, we assess the Value at Risk (VaR) prediction accuracy and efficiency of six ARCH-type models, six realized volatility models and two GARCH models augmented with realized volatility regressors. The α-th quantile of the innovation’s distribution is estimated with the fully parametric method using either the normal or the skewed student distributions and also with the Filtered Historical Simulation (FHS), or the Extreme Value Theory (EVT) methods. Our analysis is based on two S&P 500 cash index out-of-sample forecasting periods, one of which covers exclusively the recent 2007-2009 financial crisis. Using an extensive array of statistical and regulatory risk management loss functions, we find that the realized volatility and the augmented GARCH models with the FHS or the EVT quantile estimation methods produce superior VaR forecasts and allow for more efficient regulatory capital allocations. The skewed student distribution is also an attractive alternative, especially during periods of high market volatility.
    Keywords: High frequency intraday data; Filtered Historical Simulation; Extreme Value Theory; Value-at-Risk forecasting; Financial crisis.
    JEL: C13 C53 G32 G21
    Date: 2011–04–18
  2. By: Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Bertrand Hassani (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, BPCE - BPCE)
    Abstract: The Basel Advanced Measurement Approach requires financial institutions to compute capital requirements on internal data sets. In this paper we introduce a new methodology permitting capital requirements to be linked with operational risks. The data are arranged in a matrix of 56 cells. Constructing a vine architecture, which is a bivariate decomposition of a n-dimensional structure (n > 2), we present a novel approach to compute multivariate operational risk VaRs. We discuss multivariate results regarding the impact of the dependence structure on the one hand, and of LDF modeling on the other. Our method is simple to carry out, easy to interpret and complies with the new Basel Committee requirements.
    Keywords: Operational risks, vine copula, loss distribution function, nested structure, VaR.
    Date: 2011–04
  3. By: Christian Calmès (Département des sciences administratives, Université du Québec (Outaouais), Chaire d'information financière et organisationnelle, ESG-UQAM, and Laboratory for Research in Statistics and Probability); Raymond Théoret (Département de stratégie des affaires, Université du Québec (Montréal), Chaire d'information financière et organisationnelle, ESG-UQAM, and Université du Québec (Outaouais))
    Abstract: During the last decades, banks off-balance sheet (OBS) activities (e.g. securitization, trading and fee-based activities) have greatly contributed to the increase in bank risk. However, the standard financial indicators such as the Value-at-Risk and the accounting leverage, exclude these non-traditional activities, and neglect the increased risk market-oriented banking generates. In this paper, we study various measures of leverage in the context of shadow banking, relying on a dynamic setting, which features Kalman filter procedures and different detrending methods. Applying this framework to Canadian data, we can detect the increase in risk associated to banks new business lines years before what the conventional risk measures predict. We also find that the elasticity measures of leverage, compared to the simple balance sheet ratios like the ratio of assets to equity or the mandatory leverage measure, are generally more forward-looking indicators of bank risk, and better capture the cyclical pattern of bank leverage. The main contribution of this paper is to show that OBS activities exert a stronger influence on these leverage measures during expansion periods.
    Keywords: Leverage, Banking, Off-balance sheet activities, Liquidity, Kalman Filter.
    JEL: C13 C22 C51 G21 G32
    Date: 2011–01–14
  4. By: Sirio Aramonte; Marius del Giudice Rodriguez; Jason J. Wu
    Abstract: Trading portfolios at Financial institutions are typically driven by a large number of financial variables. These variables are often correlated with each other and exhibit by time-varying volatilities. We propose a computationally efficient Value-at-Risk (VaR) methodology based on Dynamic Factor Models (DFM) that can be applied to portfolios with time-varying weights, and that, unlike the popular Historical Simulation (HS) and Filtered Historical Simulation (FHS) methodologies, can handle time-varying volatilities and correlations for a large set of financial variables. We test the DFM-VaR on three stock portfolios that cover the 2007-2009 financial crisis, and find that it reduces the number and average size of back-testing breaches relative to HS-VaR and FHS-VaR. DFM-VaR also outperforms HS-VaR when applied risk measurement of individual stocks that are exposed to systematic risk.
    Date: 2011
  5. By: Christophe Boucher (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, A.A.Advisors-QCG - ABN AMRO); Bertrand Maillet (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, A.A.Advisors-QCG - ABN AMRO, EIF - Europlace Institute of Finance)
    Abstract: We provide an economic valuation of the riskiness of risk models by directly measuring the impact of model risks (specification and estimation risks) on VaR estimates. We find that integrating the model risk into the VaR computations implies a substantial minimum correction of the order of 10-40% of VaR levels. We also present results of a practical method - based on a backtesting framework - for incorporating the model risk into the VaR estimates.
    Keywords: Model risk, quantile estimation, VaR, Basel II validation test.
    Date: 2011–03
  6. By: Kent Matthews (Cardiff University and Hong Kong Institute for Monetary Research)
    Abstract: Risk Management in Chinese banks has traditionally been the Cinderella of its internal functions. Political stricture and developmental imperative have often overridden standard practice of risk management resulting in large non-performing loan (NPL) ratios. One of the stated aims of opening up the Chinese banks to foreign strategic investment is the development of risk management functions. In recent years NPL ratios have declined through a mixture of recovery, asset management operation and expanded balance sheets. However, the training and practice of risk managers remain second class compared with foreign banks operating in China. This paper evaluates bank performance using a Network DEA approach where an index of risk management practice and an index of risk management organisation are used as intermediate inputs in the production process. The two indices are constructed from a survey of risk managers in domestic banks and foreign banks operating in China. The use of network DEA can aid the manager in identifying the stages of production that need attention.
    Keywords: Risk Management, Risk Organisation, Managerial Efficiency, Network DEA
    JEL: D23 G21 G28
    Date: 2011–03
  7. By: Viral Acharya; Hamid Mehran; Til Schuermann; Anjan Thakor
    Abstract: Banks’ leverage choices represent a delicate balancing act. Credit discipline argues for more leverage, while balance-sheet opacity and ease of asset substitution argue for less. Meanwhile, regulatory safety nets promote ex post financial stability, but also create perverse incentives for banks to engage in correlated asset choices and to hold little equity capital. As a way to cope with these distorted incentives, we outline a two-tier capital framework for banks. The first tier is a regular core capital requirement that helps deter excessive risk-taking incentives. The second tier, a novel aspect of our framework, is a special capital account that limits risk taking but preserves creditors’ monitoring incentives.
    Keywords: Bank assets ; Credit ; Bank capital ; Banks and banking - Regulations ; Systemic risk
    Date: 2011
  8. By: Niyogi Sinha Roy, Tanima; Bhattacharya, Basabi
    Abstract: The paper undertakes a macroprudential analysis of the credit risk of Public Sector Banks during the liberalization period. Using the Vector Autoregression methodology, the paper investigates the dynamic impact of changes in the macroeconomic variables on the default rate, the Financial Stability Indicator of banks by simulating interactions among all the variables included in the model. Feedback effects from the banking sector to the real economy are also estimated. The impact of variations in different Monetary Policy Instruments such as Bank Rate, Repo Rate and Reverse Repo Rate on the asset quality of banks is examined using three alternative baseline models. Impulse Response Functions of the estimated models are augmented by conducting sensitivity and scenario stress testing exercises to assess the banking sector’s vulnerability to credit risk in the face of hypothetically generated adverse macroeconomic shocks. Results indicate the absence of cyclicality and pro-cyclicality of the default rate. Adverse shocks to output gap, Real Effective Exchange Rate appreciation above its trend value, inflation rate and policy-induced monetary tightening significantly affect bank asset quality. Of the three policy rates, Bank Rate affects bank soundness with a lag and is more persistent while the two short-term rates impact default rate instantaneously but is much less persistent. Scenario stress tests reveal default rate of Public Sector Banks could increase on an average from 4% to 7% depending on the type of hypothetical macroeconomic scenario generated. An average buffer capital of 3% accumulated during the period under consideration could thus be inadequate for nearly twice the amount of Non-Performing Assets generated if macroeconomic conditions worsened. An important policy implication of the paper is that as the Indian economy moves gradually to Full Capital Account Convertibility, the banking sector is likely to come under increased stress in view of the exchange rate volatility with adverse repercussions on interest rates and bank default rates. In this emerging scenario, monetary policy stance thus emerges as an important precondition for banking stability. The study also highlights the inadequacy of existing capital reserves should macroeconomic conditions deteriorate and the urgency to strengthen the buffer capital position.
    Keywords: Banks; Macro Prudential analysis; Stress test
    JEL: E52 G21
    Date: 2011–03–16
  9. By: Santiago Carbó-Valverde (University of Granada and Federal Reserve Bank of Chicago, USA.); David Marqués-Ibáñez (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, Germany.); Francisco Rodríguez Fernández (University of Granada, Spain.)
    Abstract: While the 2007-2010 financial crisis has hit a variety of countries asymmetrically, the case of Spain is particularly illustrative: this country experienced a pronounced housing bubble partly funded via spectacular developments in its securitization markets leading to looser credit standards and subsequent financial stability problems. We analyze the sequential deterioration of credit in this country considering rating changes in individual securitized deals and on balance sheet bank conditions. Using a sample of 20,286 observations on securities and rating changes from 2000Q1 to 2010Q1 we build a model in which loan growth, on balancesheet credit quality and rating changes are estimated simultaneously. Our results suggest that loan growth significantly affects on balance-sheet loan performance with a lag of at least two years. Additionally, loan performance is found to lead rating changes with a lag of four quarters. Importantly, bank characteristics (in particular, observed solvency, cash flow generation and cost efficiency) also affect ratings considerably. Additionally, these other bank characteristics seem to have a higher weight in the rating changes of securities issued by savings banks as compared to those issued by commercial banks. JEL Classification: G21, G12.
    Keywords: securitization, lending, risk, financial instability.
    Date: 2011–04
  10. By: G. William Schwert
    Abstract: This paper uses monthly returns from 1802-2010, daily returns from 1885-2010, and intraday returns from 1982-2010 in the United States to show how stock volatility has changed over time. It also uses various measures of volatility implied by option prices to infer what the market was expecting to happen in the months following the financial crisis in late 2008. This episode was associated with historically high levels of stock market volatility, particularly among financial sector stocks, but the market did not expect volatility to remain high for long and it did not. This is in sharp contrast to the prolonged periods of high volatility during the Great Depression. Similar analysis of stock volatility in the United Kingdom and Japan reinforces the notion that the volatility seen in the 2008 crisis was relatively short-lived. While there is a link between stock volatility and real economic activity, such as unemployment rates, it can be misleading.
    JEL: G11 G12
    Date: 2011–04
  11. By: Robert J. Shiller (Cowles Foundation, Yale University); Rafal M. Wojakowski (Lancaster University Management School, Accounting and Finance); M. Shahid Ebrahim (Bangor Business School, Bangor University); Mark B. Shackleton (Lancaster University Management School)
    Abstract: This paper models Continuous Workout Mortgages (CWMs) in an economic environment with refinancings and prepayments by employing a market-observable variable such as the house price index of the pertaining locality. Our main results include: (a) explicit modelling of repayment and interest-only CWMs; (b) closed form formulae for mortgage payment and mortgage balance of a repayment CWM; (c) a closed form formula for the actuarially fair mortgage rate of an interest-only CWM. For repayment CWMs we extend our analysis to include two negotiable parameters: adjustable "workout proportion" and adjustable "workout threshold." These results are of importance as they not only help understanding the mechanics of CWMs and estimating key contract parameters. These results are of importance as they not only help in the understanding of the mechanics of CWMs and estimating key contract parameters, but they also provide guidance on how to enhance the resilience of the financial architecture and mitigate systemic risk.
    Keywords: Continuous Workout Mortgage (CWM), Repayment, Interest-only, House price index, Prepayment intensity, Cap and floor on continuous flow
    JEL: C63 D11 D14 D92 G13 G21 R31
    Date: 2011–04
  12. By: Benjamin Kauper; Karl-Kuno Kunze
    Abstract: This paper offers empirical evidence on the power of Sornette et al's [2001] model of bubbles and crashes regarding the German stock market between 1960 and 2009. We identify relevant time periods and describe them with the function given by Sornette et al's model. Our results show some evidence in predicting crashes with the understanding of logarithmic periodic structures that are hidden in the stock price trajectories. It was shown that for the DAX most of the relevant parameters determining the shape of the logarithmic periodic structures are lying in the expected interval researched by Sornette et al. Further more the paper implicitly shows that the point of time of former crashes can be predicted with the presented formula. We conclude that the concept of financial time series conceived as purely random objects should be generalised as to admit complexity.
    Keywords: Bubble Theory, Complexity Sciences, Crash Prediction, Econophysics, Nonlinear Dynamics, System Theory
    JEL: C53 G11 G14
    Date: 2011–04
  13. By: Bell, Peter
    Abstract: An important question in insurance is the amount of coverage to purchase. A standard microeconomic model for insurance shows that full insurance is optimal. I present a different model where the decision variable is the number of put options and show that full insurance is still optimal, but the number of put options required to achieve this is larger than the endowment of risky assets. The model I present is based on a binomial model for a financial market, where the put option represents insurance.
    Keywords: Insurance; put option; binomial model; risk averse; risk neutral
    JEL: G11 G22 C60
    Date: 2011–04–23
  14. By: Luati, Alessandra; Proietti, Tommaso; Reale, Marco
    Abstract: The variance profile is defined as the power mean of the spectral density function of a stationary stochastic process. It is a continuous and non-decreasing function of the power parameter, p, which returns the minimum of the spectrum (p → −∞), the interpolation error variance (harmonic mean, p = −1), the prediction error variance (geometric mean, p = 0), the unconditional variance (arithmetic mean, p = 1) and the maximum of the spectrum (p → ∞). The variance profile provides a useful characterisation of a stochastic processes; we focus in particular on the class of fractionally integrated processes. Moreover, it enables a direct and immediate derivation of the Szego-Kolmogorov formula and the interpolation error variance formula. The paper proposes a non-parametric estimator of the variance profile based on the power mean of the smoothed sample spectrum, and proves its consistency and its asymptotic normality. From the empirical standpoint, we propose and illustrate the use of the variance profile for estimating the long memory parameter in climatological and financial time series and for assessing structural change.
    Keywords: Predictability; Interpolation; Non-parametric spectral estimation; Long memory.
    JEL: C13 C14 C22
    Date: 2011–04–19
  15. By: Alexander M. G. Cox; Jiajie Wang
    Abstract: Recent work of Dupire (2005) and Carr & Lee (2010) has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root (1969) for the model-independent hedging of variance options. Root's work shows that there exists a barrier from which one may define a stopping time which solves the Skorokhod embedding problem. This construction has the remarkable property, proved by Rost (1976), that it minimises the variance of the stopping time among all solutions. In this work, we prove a characterisation of Root's barrier in terms of the solution to a variational inequality, and we give an alternative proof of the optimality property which has an important consequence for the construction of subhedging strategies in the financial context.
    Date: 2011–04
  16. By: Francois-Éric Racicot (Département des sciences administratives, Université du Québec (Outaouais), LRSP et Chaire d'information financière et organisationnelle); Raymond Théoret (Département de stratégie des affaires, Université du Québec (Montréal), Université du Québec (Outaouais), et Chaire d'information financière et organisationnelle)
    Abstract: In this paper, we aim at forecasting the stochastic volatility of key financial market variables with the Kalman filter using stochastic models developed by Taylor (1986, 1994) and Nelson (1990). First, we compare a stochastic volatility model relying on the Kalman filter to the conditional volatility estimated with the GARCH model. We apply our models to Canadian short-term interest rates. When comparing the profile of the interest rate stochastic volatility to the conditional one, we find that the omission of a constant term in the stochastic volatility model might have a perverse effect leading to a scaling problem, a problem often overlooked in the literature. Stochastic volatility seems to be a better forecasting tool than GARCH(1,1) since it is less conditioned by autoregressive past information. Second, we filter the S&P500 price-earnings (P/E) ratio in order to forecast its value. To make this forecast, we postulate a rational expectations process but our method may accommodate other data generating processes. We find that our forecast is close to a GARCH(1,1) profile.
    Keywords: Stochastic volatility; Kalman filter; P/E ratio forecast; Interest rate forecast.
    JEL: C13 C19 C49 G12 G31
    Date: 2011–04–12

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