New Economics Papers
on Risk Management
Issue of 2008‒02‒09
thirteen papers chosen by

  1. Dynamic Risk Exposure in Hedge Funds By Monica Billio; Mila Getmansky; Loriana Pelizzon
  2. Default Dependence: The Equity Default Relationship By Stuart M. Turnbull; Jun Yang
  3. Estimating probabilities of default with support vector machines By Härdle, Wolfgang; Moro, Rouslan A.; Schäfer, Dorothea
  4. A Review of Correction Techniques for Inherent Biases in External Operational Risk Loss Data By Shane Wilson
  5. Endogenous credit derivatives and bank behavior By Pausch, Thilo
  6. Asset prices and monetary policy: booms and fat tails in East Asia By Maria Socorro Gochoco-Bautista
  7. APRA’s Expert Judgement Ratings and Solvency cover of Australian general Insurers By Ian Sharpe and Andre Stadnik
  8. International evidence for return predictability and the implications for long-run covariation of the G7 stock markets By Thomas Nitschka
  9. Support Vector Regression Based GARCH Model with Application to Forecasting Volatility of Financial Returns By Shiyi Chen; Kiho Jeong; Wolfgang Härdle
  10. Towards an understanding approach of the insurance linked securities market By Mathieu Gatumel; Dominique Guegan
  11. A non-parametric investigation of risk premia By Peroni, Chiara
  12. Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators Under Real-Time Conditions By Jonas Dovern; Christina Ziegler
  13. Global monitoring with the BIS international banking statistics By Patrick McGuire; Ilhyock Nikola Tarashev

  1. By: Monica Billio (Department of Economics, University Of Venice Cà Foscari); Mila Getmansky (Isenberg School of Management, University of Massachusetts); Loriana Pelizzon (Department of Economics, University Of Venice Cà Foscari)
    Abstract: We measure dynamic risk exposure of hedge funds to various risk factors during different market volatility conditions using the regime-switching beta model. We find that in the high-volatility regime (when the market is rolling-down) most of the strategies are negatively and significantly exposed to the Large-Small and Credit Spread risk factors. This suggests that liquidity risk and credit risk are potentially common factors for different hedge fund strategies in the down-state of the market, when volatility is high and returns are very low. We further explore the possibility that all hedge fund strategies exhibit idiosyncratic risk in a high volatility regime and find that the joint probability jumps from approximately 0% to almost 100% only during the Long-Term Capital Management (LTCM) crisis. Out-of-sample forecasting tests confirm the economic importance of accounting for the presence of market volatility regimes in determining hedge funds risk exposure.
    Keywords: Hedge Funds; Risk Management; Regime-Switching Models, Liquidity
    JEL: G12 G29 C51
    Date: 2007
  2. By: Stuart M. Turnbull; Jun Yang
    Abstract: The paper examines three equity-based structural models to study the nonlinear relationship between equity and credit default swap (CDS) prices. These models differ in the specification of the default barrier. With cross-firm CDS premia and equity information, we are able to estimate and compare the three models. We find that the stochastic barrier model performs better than the constant and uncertain barrier models in terms of both in-sample fit and out-of-sample forecasting of CDS premia. In addition, we demonstrate a linkage between the default barrier, jump intensity, and barrier volatility estimated from our models and firm-specific variables related to default risk, such as credit ratings, equity volatility, and leverage ratios.
    Keywords: Econometric and statistical methods; Financial markets
    JEL: G12 G13
    Date: 2008
  3. By: Härdle, Wolfgang; Moro, Rouslan A.; Schäfer, Dorothea
    Abstract: This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data. In particular we discuss the selection of variables and give a comparison with more traditional approaches such as discriminant analysis and the logit regression. The results demonstrate that the SVM has clear advantages over these methods for all variables tested.
    Keywords: Bankruptcy, Company rating, Default probability, Support vector machines
    JEL: C14 C45 G33
    Date: 2007
  4. By: Shane Wilson (Australian Prudential Regulation Authority)
    Abstract: Banks wishing to implement the Advanced Measurement Approach (AMA) to calculate their Operational Risk Regulatory Capital (ORRC), must incorporate either implicitly or explicitly, internal and external loss data (ILD and ELD), scenario analysis (SA) and business environment and internal control factors (BEICFs) into their operational risk measurement system. Through the collection of ILD, banks are able to ascertain information on commonly occurring low impact operational risk losses. However, to complete their loss profile, both ELD and SA are used to supplement the bank’s internal loss experience with the infrequent yet potentially severe operational risk loss events not usually experienced in a banks loss history. The main limitation of utilising ELD for such a purpose is the inherent biases apparent in the data. This paper explores the reporting, control and scale bias that are inherent in ELD and the subsequent problems faced when incorporating external data into the AMA.
    Keywords: Operational Risk, External, Loss, ELD, Bias, Reporting, Control, Scale, AMA, Data, Regulatory, Capital
    Date: 2007–11–29
  5. By: Pausch, Thilo
    Abstract: Instruments for credit risk transfer arise endogenously from and interact with optimizing behavior of their users. This is particularly true with credit derivatives which are usually OTC contracts between banks as buyers and sellers of credit risk. Recent literature, however, does not account for this fact when analyzing the effects of these instruments on banking. The present paper closes this gap by explicitly modelling the market for credit derivatives and its interaction with banks’ loan granting and deposit taking activities.
    Keywords: credit risk, credit derivatives, bargaining
    JEL: D53 D82 G11 G14 G21
    Date: 2007
  6. By: Maria Socorro Gochoco-Bautista
    Abstract: Do housing and equity booms significantly raise the probability of extremely bad outcomes at the margin? This study addresses this question for a group of 8 East Asian countries. The main findings are the following: (i) Asset price booms in housing and equity markets, either separately or jointly but especially in housing, significantly raise the probability at the margin that (a) the real output gap will be in the left tail of its distribution, in which output is significantly below trend, and (b) the price-level gap will be in the right tail of its distribution, in which the price level is significantly above trend. At the margin, the risk of the occurrence of these particular tail events due to asset price booms is largely asymmetric and does not apply to the tails of good outcomes; and (ii) Expected real output and price level outcomes that are either obtained without conditioning on asset price booms or are obtained conditional on asset price booms using the normal approximation underestimate the risk of tail events and lead to less pessimistic but misleading inferences. One implication for monetary policy is that an approach that is ex-ante more compatible with risk management may be appropriate.
    Keywords: asset price booms, tails, GDP-at-risk, CPI-at-risk, risk management
    Date: 2008–01
  7. By: Ian Sharpe and Andre Stadnik (Australian Prudential Regulation Authority)
    Abstract: The Australian Prudential Regulation Authority’s (APRA’s) supervisors use expert judgement to rate risk of failure (ROF) of General Insurers (GIs). Using statistical data we model the determinants of GI ratings and solvency cover and find: (i) sufficient predictive power in statistical data to identify GIs for earlier review and assist in quality assurance of APRA’s ratings; and (ii) profitability, solvency cover, investment and underwriting risk play different roles in rating foreign branch and Australian incorporated GIs. We conclude that supervisors generally correctly incorporate our a priori expectations of the effects of risk indicators on GI risk into their ratings.
    Date: 2008–01–18
  8. By: Thomas Nitschka
    Abstract: Temporary fluctuations of the U.S. consumption-wealth ratio, cay, predict excess returns on international stock markets at the business cycle frequency. This finding is the reflection of a common, temporary component in national stock markets. Exposure to this common component explains up to 60 percent of the covariation among long-horizon returns on the G7 stock markets for the time period from 1973 to 2005. The impact of the common component on stock market comovement is particularly pronounced in the period from 1990 to 2005.
    Keywords: U.S. consumption-wealth ratio, stock market comovement, stock return predictability
    JEL: E21 G12
    Date: 2007–11
  9. By: Shiyi Chen; Kiho Jeong; Wolfgang Härdle
    Abstract: In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving average (MA), a recurrent NN and a parametric GACH in terms of their ability to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange rates from July 2, 2003 to June 30, 2005 and New York Stock Exchange (NYSE) daily composite index from July 3, 2003 to June 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms the MA, the recurrent NN and the parametric GARCH based on the criteria of mean absolute error (MAE) and directional accuracy (DA). No structured way being available to choose the free parameters of SVR, the sensitivity of performance is also examined to the free parameters.
    Keywords: recurrent support vector regression, GARCH model, volatility forecasting
    JEL: C45 C53 G32
    Date: 2008–01
  10. By: Mathieu Gatumel (Axa - AXA); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, Ecole d'économie de Paris - Paris School of Economics - Université Panthéon-Sorbonne - Paris I)
    Abstract: The paper aims to present the insurance linked securities market behaviour, that has changed a lot the past three years, both in terms of structure and in terms of ceded risks. After having introduced some stylized facts characterizing the insurance linked securities we capture their market price of risk, following the methodologies of Wang (2004), Lane (2000) and Fermat Capital Management (2005). A dynamical study of the insurance linked securities is also provided in order to understand the elements driving the spreads : the consequences of the catastrophic events, the seasonality and the diversification effects between some different risks are highlighted.
    Keywords: Insurance linked securities, cat. bonds, market price of risk.
    Date: 2008–01
  11. By: Peroni, Chiara
    Abstract: This paper investigates features of credit risk using non-parametric techniques, studying determinants of risk premia using a non-parametric term-structure model of the corporate spread. The model, which measures the extra return of defaultable corporate bonds on their government counterparts, involves the rate of inflation, a key macroeconomic variable that is found to explain the spread non-linearly. This approach demonstrates the usefulness of non-linear approaches in contrast with standard linear approaches. The model is also useful to forecast the future course of the spread.
    Keywords: Risk premium; affine models; non-parametric regression
    JEL: G12 C14
    Date: 2007–06–01
  12. By: Jonas Dovern; Christina Ziegler
    Abstract: In this paper we analyze the power of various indicators to predict growth rates of aggregate production using real-time data. In addition, we assess their ability to predict turning points of the economy. We consider four groups of indicators: survey data, composite indicators, real economic indicators, and financial data. Almost all indicators are found to improve short-run growth forecasts whereas the results for four-quarter-ahead growth forecasts and the prediction of recession probabilities in general are mixed. We can confirm the result that an indicator suited to improve growth forecasts does not necessarily help to produce more accurate recession forecasts. Only composite leading indicators perform generally well in both forecasting exercises.
    Keywords: leading indicators, forecasting, recessions
    JEL: C25 C32 E32 E37
    Date: 2008–01
  13. By: Patrick McGuire; Ilhyock Nikola Tarashev
    Abstract: This paper illustrates various applications of the BIS international banking statistics. We first compare international bank flows to measures of real activity and liquidity and show that the international banking system is becoming a more important conduit for the transfer of capital across countries. We then use network analysis tools to construct a bird's eye view of the structure of the international banking market and to identify key financial hubs. Linking this information with balance of payments statistics helps to better understand the role of banks in the financing of current account flows, for example the recycling of petrodollars and Asian surpluses. Finally, the paper illustrates how the BIS statistics can be used to analyse internationally active banks' foreign exposures to credit risk and, thus, spot vulnerabilities in the international banking market.
    Date: 2008–02

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