New Economics Papers
on Risk Management
Issue of 2010‒03‒13
ten papers chosen by

  1. Risk analysis in the evaluation of the international investment opportunities. Advances in modelling and forecasting volatility for risk assessment purposes By Matei, Marius
  2. Productivity Changes and Risk Management in Indonesian Banking: An Application of a New Approach to Constructing Malmquist Indices By Muliaman D. Hadad; Maximilian J. B. Hall; Wimboh Santoso; Karligash Kenjegalieva; Richard Simper
  3. Flexible and Robust Modelling of Volatility Comovements: A Comparison of Two Multifractal Models By Ruipeng Liu; Thomas Lux
  4. Optimal capital allocation principles. By Dhaene, Jan; Tsanakas, Andreas; Valdez, Emiliano; Vanduffel, Steven
  5. Regulating Systemic Risk By Kawai, Masahiro; Pomerleano, Michael
  6. Subprime mortgage lending in New York City: prevalence and performance By Ebiere Okah; James Orr
  7. "Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets" By Chialin Chang; Michael McAleer; Roengchai Tansuchat
  8. Rethinking market discipline in banking : lessons from the financial crisis By Stephanou, Constantinos
  9. A General Index of Inherent Risk By Adi Schnytzer; Sara Westreich
  10. Inequalities for the De Pril approximation to the distribution of the number of policies with claims. By Vernic, Raluca; Dhaene, Jan; Sundt, Bjorn

  1. By: Matei, Marius (Ph.D. Student at ESADE Business School, Department of Finance, Barcelona and at National Institute of Economic Research, Romanian Academy, Bucharest)
    Abstract: The thesis proposes to assess the risk topic in the context of foreign investment decisions. In identifying two main risk-related concepts, I have split risks in two categories using a unique criterion: the ratio between the endogenous and exogenous content of the problem. According to it, I have built a pool of risks that the company may have entirely or partially under control (forming the endogenous part of the problem), and a pool with exogenous risks that the company cannot control at all, but can assess and build strategies for their management (forming the exogenous part of the problem). In each category I have identified one source of risk, representing the most important of all risks belonging to the same pool. For the endogenous risks part, credit risk (in its extensive version counterparty risk) was selected. Related to this, there have been additionally discussed the topics of systemic risk and of the risk associated to the impact of the activity of the international rating agencies on the firm financing problem when a company proceeded to debt issuance. The other half of the problem involves the risk of the sector the company activates in. I have found that the risk assessment in this category became an econometric problem of volatility forecasting for a portfolio of a number of selected returns. The discussion complicates given the following factors: 1. The scientific world has not reached yet to a consensus on the superiority of a certain model or group of models that measures volatility. As such, forecasted volatility estimates may depend on the model or methodologies to be used, type of data frequency (high or low), selection of the error statistics etc. As such, decision making as regards the opportunity of the investment becomes highly dependent on econometric choices to be made. 2. Multivariate models are computationally intensive due to the parameter estimation problem. If a large number of stocks are included in the portfolio, the number of estimations to be done would be so high that the problem would be extremely difficult to be technically undertaken. 3. Due to high correlation of stocks, the estimation problem becomes particularly imprecise and computationally difficult. As a solution to such problems, I have justified the superiority of one autoregressive heteroskedastic model (PC-GARCH) considering not only estimation performance but also cost saving component. For this purpose, I have run an empirical exercise with a portfolio formed of seven stocks belonging to the US IT sector (Adobe, Apple, Autodesk, Cisco, Dell, Microsoft and 3M) in order to evidentiate advantages of this model. They may be summarized as it follows: PC-GARCH • Minimizes computational efforts (by transforming multivariate GARCH models into univariate ones), by reducing significantly the computational time and getting rid of any problem that may arise from complex data manipulations; • Ensures a tight control of the amount of “noise” due to reducing the number of variables to fewer principal components. This may prove benefic since it may result in more stable correlation estimates; • Produces volatilities and correlations for all variables in the system, including those for which direct GARCH estimation is computationally difficult. As such, I’ve concluded that when using large portfolios formed of hundreds or thousands of stocks, for the scope of volatility (and therefore risk) forecasting, PCGARCH is the most appropriate model to be used.
    Keywords: risk, endogeneity, exogeneity, credit risk, systemic risk, counterparty risk,rating, volatility, forecasting, GARCH, PC-GARCH, principal components, autocorrelation, heteroskedasticity, orthogonality
    JEL: C3 C53 D81
    Date: 2010–02
  2. By: Muliaman D. Hadad (Bank Indonesia, Jakarta, Indonesia); Maximilian J. B. Hall (Dept of Economics, Loughborough University); Wimboh Santoso (Bank Indonesia, Jakarta, Indonesia); Karligash Kenjegalieva (Dept of Economics, Loughborough University); Richard Simper (Dept of Economics, Loughborough University)
    Abstract: In this study, we utilise a new, non-parametric efficiency measurement approach which combines the semi-oriented radial measure data envelopment analysis (SORM-SBM-DEA) approach for dealing with negative data (Emrouznejad et al., 2010) with the slacks-based efficiency measures of Tone (2001, 2002) to analyse productivity changes for Indonesian banks over the period Quarter I 2003 to Quarter II 2007. Having constructed the Malmquist indices, using data provided by Bank Indonesia (the Indonesian central bank), for the banking industry and different bank types (i.e., listed and Islamic) and groupings, we then decomposed the industry’s Malmquist into its technical efficiency change and frontier shift components. Finally, we analysed the banks’ risk management performance, using Simar and Wilson’s (2007) truncated regression approach, before assessing its impact on productivity growth. The first part of the Malmquist analysis showed that average productivity changes for the Indonesian banking industry tended to be driven, over the sample period, by technological progress rather than by frontier shift, although a relatively stable pattern was exhibited for most of the period. However, at the beginning of the considered period, state-owned and foreign banks, as well as Islamic banks, exhibited volatile productivity movements, mainly caused by shifts in the technological frontier. With respect to the risk management analysis, most of the balance sheet variables were shown to have had the expected impact on risk management efficiency. While the risk management decomposition of technical efficiency change and frontier risk components demonstrated that, by the end of the sample period, the change in risk management efficiency and risk management effects had the same dynamic pattern, resulting in the analogous dynamics for technical efficiency changes. Therefore, a strategy based on the gradual adoption of newer technology, with a particular focus on internal risk management enhancement, seems to offer the highest potential for boosting the productivity of the financial intermediary operations of Indonesian banks.
    Keywords: Indonesian Finance and Banking; Productivity; Efficiency.
    JEL: C23 C52 G21
    Date: 2010–02
  3. By: Ruipeng Liu; Thomas Lux
    Abstract: Long memory (long-term dependence) of volatility counts as one of the ubiquitous stylized facts of financial data. Inspired by the long memory property, multifractal processes have recently been introduced as a new tool for modeling financial time series. In this paper, we propose a parsimonious version of a bivariate multifractal model and estimate its parameters via both maximum likelihood and simulation based inference approaches. In order to explore its practical performance, we apply the model for computing value-at-risk and expected shortfall statistics for various portfolios and compare the results with those from an alternative bivariate multifractal model proposed by Calvet et al. (2006) and the bivariate CC-GARCH of Bollerslev (1990). As it turns out, the multifractal models provide much more reliable results than CC-GARCH, and our new model compares well with the one of Calvet et al. although it has an even smaller number of parameters
    Keywords: Long memory, multifractal models, simulation based inference, value-at-risk, expected shortfall
    JEL: C11 C13 G15
    Date: 2010–02
  4. By: Dhaene, Jan; Tsanakas, Andreas; Valdez, Emiliano; Vanduffel, Steven
    Abstract: This paper develops a unifying framework for allocating the aggregate capital of a financial firm to its business units. The approach relies on an optimisation argument, requiring that the weighted sum of measures for the deviations of the business unit’s losses from their respective allocated capitals be minimised. This enables the association of alternative allocation rules to specific decision criteria and thus provides the risk manager with flexibility to meet specific target objectives. The underlying general framework reproduces many capital allocation methods that have appeared in the literature and allows for several possible extensions. An application to an insurance market with policyholder protection is additionally provided as an illustration.
    Date: 2009–01–23
  5. By: Kawai, Masahiro (Asian Development Bank Institute); Pomerleano, Michael (Asian Development Bank Institute)
    Abstract: The failure to spot emerging systemic risk and prevent the current global financial crisis warrants a reexamination of the approach taken so far to crisis prevention. The paper argues that financial crises can be prevented, as they build up over time due to policy mistakes and eventually erupt in "slow motion." While one cannot predict the precise timing of crises, one can avert them by identifying and dealing with sources of instability. For this purpose, policymakers need to strengthen top-down macroprudential supervision, complemented by bottom-up microprudential supervision. The paper explores such a strategy and the institutional setting required to implement it at the national level. Given that the recent regulatory reforms that have been undertaken to address systemic risks are inadequate to prevent and combat future crises, the paper argues that national measures to promote financial stability are crucial and that the Westphalian principles governing international financial oversight should be rejected. The paper proposes that while an effective national systemic regulator should be established, strong international cooperation is indispensable for financial stability.
    Keywords: global financial crisis; systemic risk; macroprudential supervision; systemic stability regulation; regulating systemic risk
    JEL: G21 G28
    Date: 2010–01–27
  6. By: Ebiere Okah; James Orr
    Abstract: Subprime mortgage lending expanded in New York City between 2004 and mid-2007, and delinquencies on these subprime loans have been rising sharply. We use a rich, loan-level data set of the city's outstanding subprime loans as of January 2009 to describe the main features of this lending and to model the performance of these loans. These subprime loans represent a smaller share of total housing units in the city than is true nationwide. In addition, they are found to be clustered in neighborhoods where average borrower credit quality is low and, unlike prime mortgage loans, where African-Americans and Hispanics constitute relatively large shares of the population. We estimate a model of the likelihood that these loans will become seriously delinquent and find a significant role for credit quality of borrowers, debt-to-income and loan-to-value ratios at the time of loan origination, and estimates of the loss of home equity.
    Keywords: Subprime mortgage ; Financial risk management ; Consumer credit ; Demography
    Date: 2010
  7. By: Chialin Chang (Department of Applied Economics, National Chung Hsing University); Michael McAleer (Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute); Roengchai Tansuchat (Faculty of Economics, Maejo University)
    Abstract: Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover and asymmetric effects across and within the four markets, using three multivariate GARCH models, namely the constant conditional correlation (CCC), vector ARMA-GARCH (VARMA-GARCH) and vector ARMA-asymmetric GARCH (VARMA-AGARCH) models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecast conditional correlations between pairs of crude oil returns have both positive and negative trends. Moreover, the optimal hedge ratios and optimal portfolio weights of crude oil across different assets and market portfolios are evaluated in order to provide important policy implications for risk management in crude oil markets.
    Date: 2010–02
  8. By: Stephanou, Constantinos
    Abstract: The main objective of this paper is to rethink the use of market discipline for prudential purposes in light of lessons from the financial crisis. The paper develops the main building blocks of a market discipline framework, and argues for the need to take an expansive view of the concept. It also illustrates using actual bank case studies from the United States its apparent failures in the crisis, particularly the failure to prevent the buildup of systemic, as opposed to idiosyncratic, risks. However, while the role of market discipline in the design of macro-prudential regulation appears to be largely constrained, more can be done on the micro-prudential side to promote clearer market signals of bank riskiness and to encourage their use in the supervisory process.
    Keywords: Banks&Banking Reform,Debt Markets,Markets and Market Access,Emerging Markets,Access to Finance
    Date: 2010–03–01
  9. By: Adi Schnytzer (Department of Economics and Logistics,respectively,Bar Ilan University,Israel); Sara Westreich
    Abstract: We extend the pioneering work of Aumann and Serrano by presenting an index of inherent riskiness of a gamble having the desirable properties of their index, while being applicable to gambles with either positive or negative expectations. As such, our index provides a measure of riskiness which is of use for both risk lovers and risk aversive gamblers, and is defined for all discrete and a large class of continuous gambles. We analyze abstract properties of our index, and present in addition three empirical applications - roulette, horse betting market and US options traded on financial stocks between 2005 and 2007.
    Date: 2009–04
  10. By: Vernic, Raluca; Dhaene, Jan; Sundt, Bjorn
    Abstract: In the present paper, we give su¢ cient conditions for an ordering of De Pril approximations of the distribution of the number of claims in an insurance portfolio of independent policies. Possible extensions are discussed, both for the De Pril approximation and the Kornya approximation. A numerical example is given.
    Date: 2009–02–03

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