nep-rmg New Economics Papers
on Risk Management
Issue of 2008‒04‒15
twelve papers chosen by
Stan Miles
Thompson Rivers University

  1. Modeling International Financial Returns with a Multivariate Regime Switching Copula By Chollete, Loran; Heinen, Andreas; Valdesogo, Alfonso
  2. A Corrected Value-at-Risk Predictor By Lönnbark, Carl
  3. O Spread de Incumprimento dos Empréstimos Bancários By Paulo Horta
  4. Impact of Political News on the Baltic State Stock Markets By Soultanaeva, Albina
  5. Managerial Risk Accounting and Control – A German perspective By Winter, Peter
  6. Real-Time Measurement of Business Conditions, Second Version By S. Boragan Aruoba; Francis X. Diebold; Chiara Scotti
  7. A multi-horizon scale for volatility. By Alexander Subbotin
  8. Forecasting Realized Volatility: A Bayesian Model Averaging Approach By Chun Liu; John M Maheu
  9. Credit Rationing with Symmetric Information By Fioretti, Guido
  10. Gambling in the New Year? The January Idiosyncratic Volatility Puzzle By Doran, James; Jiang, Danling; Peterson, David
  11. Calendar anomalies in Athens Exchange Stock Market By Giovanis, Eleftherios
  12. Credit scoring with boosted decision trees By Bastos, Joao

  1. By: Chollete, Loran; Heinen, Andreas; Valdesogo, Alfonso
    Abstract: In order to capture observed asymmetric dependence in international financial returns, we construct a multivariate regime-switching model of copulas. We model dependence with one Gaussian and one canonical vine copula regime. Canonical vines are constructed from bivariate conditional copulas and provide a very flexible way of characterizing dependence in multivariate settings. We apply the model to returns from the G5 and Latin American regions, and document two main findings. First, we discover that models with canonical vines generally dominate alternative dependence structures. Second, the choice of copula is important for risk management, because it modifies the Value at Risk (VaR) of international portfolio returns.
    Keywords: Asymmetric dependence; Canonical vine copula; International returns; Regime-Switching; Risk Management; Value-at-Risk.
    JEL: C32 G1 C35
    Date: 2008–02
  2. By: Lönnbark, Carl (Department of Economics, Umeå University)
    Abstract: In this note it is argued that the estimation error in Value-at-Risk predictors gives rise to underestimation of portfolio risk. We propose a simple correction and find in an empirical illustration that it is economically relevant.
    Keywords: Estimation Error; Finance; Garch; Prediction; Risk Management
    JEL: C32 C51 C53 G10
    Date: 2008–03–26
  3. By: Paulo Horta
    Abstract: In this paper we propose a discrete time model to measure the default spread for Bank loans. The model provides a closed-form solution for the short and medium term default spread, which we assume to be dependent on the default probabilities, the losses given default, the risk grades transition probabilities, seen in a Markov chain, the prime rate and the economic cycle phases. The model is tested with real data provided by a Bank, and allows one to conclude that the actual spread is, on the one hand, insufficient to cover the whole credit risk for low-risk clients and, on the other hand, excessive for high-risk clients. We believe that this study may contribute to improve the pricing for Bank loans.
    Keywords: Bank loans, default spread, credit risk, probability of default, loss given default, prime rate, risk grade transition, Markov chain, economic cycle
    JEL: G12 G21
    Date: 2008
  4. By: Soultanaeva, Albina (Department of Economics, Umeå University)
    Abstract: This paper studies the link between political news releases, and the returns and volatilities in the stock markets of Riga, Tallinn and Vilnius. Political news releases are viewed as proxies for political risk. The results indicate that political news events regarding domestic and foreign, excluding Russia, political issues led, on average, to lower uncertainty in the stock markets of Riga and Tallinn in 2001-2003. At the same time, political risk from Russia increased the volatility of the stock market in Tallinn. We found that there is only a weak relationship between political risks of different origins and the stock market volatility in the Baltic states in 2004-2007. In addition, we found a significant Monday effect, consistent with the trading behavior of institutional investors.
    Keywords: Public information arrival; political risk; volatility; multivariate GARCH
    JEL: C32 G10 G14 G15
    Date: 2008–03–27
  5. By: Winter, Peter
    Abstract: Recent developments have sparked a renewed interest concerning risk related topics in nonfinancial companies. Risk management issues directly touch the domain of management accounting and control. In Germany, topics related to the support of corporate or enterprise risk management are commonly discussed under the label of “Risikocontrolling”, which will be translated as Managerial Risk Accounting and Control. However, the conceptual foundation of a risk oriented management accounting respectively managerial accounting for the purpose of decision-facilitation and decision-influence pertaining to risk management is neither well developed nor well diffused and integrated. Therefore, the development of special risk oriented management accounting instruments is considered necessary. The paper aims at giving an overview of the subject and development of “Risikocontrolling” in Germany as well as discussing the necessity and (measurement and behavioural) problems of managerial risk accounting. Finally, a proposal for the design of managerial risk accounting systems will be presented.
    Keywords: Controlling; Germany; Management Accounting; Risk; Risk Management; Risk Measurement
    JEL: M41
    Date: 2007–08–21
  6. By: S. Boragan Aruoba (Department of Economics, University of Maryland); Francis X. Diebold (Department of Economics, University of Pennsylvania and NBER); Chiara Scotti (Federal Reserve Board, Division of International Finance)
    Abstract: We construct a framework for measuring economic activity at high frequency, potentially in real time. We use a variety of stock and flow data observed at mixed frequencies (including very high frequencies), and we use a dynamic factor model that permits exact filtering. We illustrate the framework in a prototype empirical example and a simulation study calibrated to the example.
    Keywords: Business cycle, Expansion, Recession, State space model, Macroeconomic forecasting, Dynamic factor model, Contraction, Turning point
    JEL: E32 E37 C01 C22
    Date: 2007–03–01
  7. By: Alexander Subbotin (Centre d'Economie de la Sorbonne et Higher School of Economics (Moscow))
    Abstract: We decompose volatility of a stock market index both in time and scale using wavelet filters and design a probabilistic indicator for valatilities, analogous to the Richter scale in geophysics. The peak-over-threshold method is used to fit the generalized Pareto probability distribution for the extreme values in the realized variances of wavelet coefficients. The indicator is computed for the daily Dow Jones Industrial Averages index data from 1986 to 2007 and for the intraday CAC 40 data from 1995 to 2006. The results are used for comparison and structural multi-resolution analysis of extreme events on the stock market and for the detection of financial crises.
    Keywords: Stock market, volatility, wavelets, multi-resolution analysis, financial crisis.
    JEL: G10 G14
    Date: 2008–03
  8. By: Chun Liu; John M Maheu
    Abstract: How to measure and model volatility is an important issue in finance. Recent research uses high frequency intraday data to construct ex post measures of daily volatility. This paper uses a Bayesian model averaging approach to forecast realized volatility. Candidate models include autoregressive and heterogeneous autoregressive (HAR) specifications based on the logarithm of realized volatility, realized power variation, realized bipower variation, a jump and an asymmetric term. Applied to equity and exchange rate volatility over several forecast horizons, Bayesian model averaging provides very competitive density forecasts and modest improvements in point forecasts compared to benchmark models. We discuss the reasons for this, including the importance of using realized power variation as a predictor. Bayesian model averaging provides further improvements to density forecasts when we move away from linear models and average over specifications that allow for GARCH effects in the innovations to log-volatility.
    Keywords: power variation, bipower variation, Gibbs sampling, model risk
    JEL: C11 C22 G12
    Date: 2008–04–03
  9. By: Fioretti, Guido
    Abstract: Without denying the importance of asymmetric information, this article purports the view that credit rationing may also originate from a lender's inability to classify loan applicants in proper risk categories. This effect is particularly strong when novel technologies are involved. Furthermore, its relevance may increase with the importance assigned to internal rating systems by the Basel accord. This article presents a measure of the inadequacy of a lender's classification criteria to the qualitative features of prospective borrowers. Even without information asymmetries, credit rationing may occur if this quantity reaches too high a value. Furthermore, some general principles are outlined, that may be used by lenders in order to change their classification criteria.
    Keywords: Credit Rationing; Risk Categories; Internal Rating Systems; Deciding not to Decide; Problem Decomposition
    JEL: D89 E41
    Date: 2008–04–09
  10. By: Doran, James; Jiang, Danling; Peterson, David
    Abstract: In January high idiosyncratic volatility stocks on average outperform low volatility stocks regardless of firm size, book-to-market equity, past returns, and institutional trading, while in other months they underperform. This positive January relation is concentrated among low-price stocks that also exhibit negative mean, but highly skewed, returns for the remaining months of the year. We suggest these findings are driven by investor preference for stocks with lottery features at the start of the New Year. Similarly, gambling activities in Las Vegas exhibit January seasonality. Also, Chinese stock markets as a whole and highly volatile Chinese stocks in particular outperform at the turn of the Chinese New Year, but not in January.
    Keywords: Idiosyncratic Volatility, January Effect, Mental Accounting, Preference for Skewness, Gambling
    JEL: G14 G11 G12
    Date: 2008–04–08
  11. By: Giovanis, Eleftherios
    Abstract: The purpose of this paper is to examine if there are calendar anomalies in the Greek Stock market and to confirm the findings of other researches . Specifically two models are presented, one for the day of the week effect test and other for the month of the year effect.
    Keywords: day of the week effect, month effect, January and Monday effect, rolling regression, ARCH, GARCH
    JEL: C10 G12
    Date: 2008–01–18
  12. By: Bastos, Joao
    Abstract: The enormous growth experienced by the credit industry has led researchers to develop sophisticated credit scoring models that help lenders decide whether to grant or reject credit to applicants. This paper proposes a credit scoring model based on boosted decision trees, a powerful learning technique that aggregates several decision trees to form a classifier given by a weighted majority vote of classifications predicted by individual decision trees. The performance of boosted decision trees is evaluated using two publicly available credit card application datasets. The prediction accuracy of boosted decision trees is benchmarked against two alternative data mining techniques: the multilayer perceptron and support vector machines. The results show that boosted decision trees are a competitive technique for implementing credit scoring models.
    Keywords: Credit scoring; Boosting; Decision tree; neural network; support vector machine
    JEL: C44 G32
    Date: 2008–04–01

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