
on Risk Management 
By:  Esposito, Francesco Paolo 
Abstract:  This document presents several Credit Risk tools which have been developed for the Credit Derivatives Risk Management. The models used in this context are suitable for the pricing, sensitivity/scenario analysis and the derivation of risk measures for plain vanilla credit default swaps (CDS), standardized and bespoke collateralized debt obligations (CDO) and, in general, for any credit risk exposed A/L portfolio.\\ In this brief work we compute the market implied probability of default (PD) from market spreads and the theoretical CDS spreads from historical default frequencies. The loss given default (LGD) probability distribution has been constructed for a large pool portfolio of credit obligations exploiting a singlefactor gaussian copula with a direct convolution algorithm computed at several default correlation parameters. Theoretical CDO tranche prices have been calculated. We finally design stochastic cashflow stream model simulations to test fair pricing, compute credit value at risk (CV@R) and to evaluate the one year total future potential exposure (FPE) and derive the value at risk (V@R) for a CDO equity tranche exposure. 
Keywords:  interest rate swap; spot rate term structure; credit default swap; probability of default; copula function; direct convolution; loss given default; collateralized debt obligation; exposure at default; stochastic cashflow stream model; value at risk; credit value at risk; future potential exposure; Monte Carlo simulation. 
JEL:  C0 C15 G0 
Date:  2010–12–10 
URL:  http://d.repec.org/n?u=RePEc:pra:mprapa:28045&r=rmg 
By:  Michael McAleer (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, and Institute of Economic Research, Kyoto University); JuanÁngel JiménezMartín (Department of Quantitative Economics, Complutense University of Madrid); Teodosio PérezAmaral (Department of Quantitative Economics, Complutense University of Madrid) 
Abstract:  A risk management strategy that is designed to be robust to the Global Financial Crisis (GFC), in the sense of selecting a ValueatRisk (VaR) forecast that combines the forecasts of different VaR models, was proposed in McAleer et al. (2010c). The robust forecast is based on the median of the point VaR forecasts of a set of conditional volatility models. Such a risk management strategy is robust to the GFC in the sense that, while maintaining the same risk management strategy before, during and after a financial crisis, it will lead to comparatively low daily capital charges and violation penalties for the entire period. This paper presents evidence to support the claim that the median point forecast of VaR is generally GFCrobust. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria. In the empirical analysis, we choose several major indexes, namely French CAC, German DAX, US Dow Jones, UK FTSE100, Hong Kong Hang Seng, Spanish Ibex35, Japanese Nikkei, Swiss SMI and US S&P500. The GARCH, EGARCH, GJR and Riskmetrics models, as well as several other strategies, are used in the comparison. Backtesting is performed on each of these indexes using the Basel II Accord regulations for 200810 to examine the performance of the Median strategy in terms of the number of violations and daily capital charges, among other criteria. The Median is shown to be a profitable and safe strategy for risk management, both in calm and turbulent periods, as it provides a reasonable number of violations and daily capital charges. The Median also performs well when both total losses and the asymmetric linear tick loss function are considered 
Keywords:  Median strategy, ValueatRisk (VaR), daily capital charges, robust forecasts, violation penalties, optimizing strategy, aggressive risk management, conservative risk management, Basel II Accord, global financial crisis (GFC). 
JEL:  G32 G11 C53 C22 
Date:  2011–01 
URL:  http://d.repec.org/n?u=RePEc:kyo:wpaper:757&r=rmg 
By:  Marcella Lucchetta 
Abstract:  This paper explores theoretically the implications of bank market structure and banking system risks concentration for the functioning of interbank markets. It employs a simple model where banks are exposed to both credit and liquidity risk, there is no asymmetric information, no market power, no friction in secondary markets and deposit contracts are fully contingent. We show that (a) the concentration of risks induced by changes in bank market structure makes interbank market breakdowns more likely; (b) welfare monotonically decreases in risk concentration; and (c) risk concentration and a high probability of interbank market breakdowns can be driven by risk control diseconomies of scale and scope and increases in financial firms’ size. As banking systems become more concentrated, improvement of risk control technologies in financial institutions and in regulatory bodies appear as important as other policies considered in the literature to minimize the probability of interbank market breakdowns. 
Keywords:  bank market structure; systemic risk; interbank markets 
Date:  2010–10–01 
URL:  http://d.repec.org/n?u=RePEc:rsc:rsceui:2010/76&r=rmg 
By:  Dario Focarelli (ANIA.); David MarquesIbanez (European Central Bank, Kaiserstrasse 29, D60311 Frankfurt am Main, Germany.); Alberto Franco Pozzolo (Università del Molise.) 
Abstract:  It has often been argued during the recent credit crisis that commercial banks’ involvement in investment banking activities might have had an impact on the intensity of their underwriting standards. We turn to evidence from the period prior to the complete revocation of the GlassSteagall Act in the United States and analyze whether investment banks or – section 20 subsidiaries of – commercial banks underwrote riskier securities. We compare actual defaults of these deals for an extensive sample of about 4,000 corporate debt securities underwritten during the period of the de facto softening of the Act’s restrictions. Securities underwritten by commercial banks’ subsidiaries have a higher probability of default than those underwritten by investment houses. This evidence is stronger in the case of exante riskier and more competitive issues, and during the first years of bank securities’ subsidiaries’ entry into the market. Based on our results, it is not possible to reject that the repeal of the GlassSteagall led to looser credit screening by broad (universal) banking companies trying to gain market share and/or to the lower initial ability of these banks to correctly evaluate default risk. JEL Classification: G21, G24, N22. 
Keywords:  GlassSteagall Act, securities underwriting, default, investment banking. 
Date:  2011–01 
URL:  http://d.repec.org/n?u=RePEc:ecb:ecbwps:20111287&r=rmg 
By:  Kjell Bjørn Nordal (Norges Bank (Central Bank of Norway)); Randi Næs (Norwegian Ministry of Trade and Industr) 
Abstract:  We investigate the relationship between bankruptcy risk and expected future sales growth for Norwegian nonlisted firms for the period 19882007. We find that firms with high bankruptcy risk also have high expected future growth. Financial ratios characterizing firms with high bankruptcy risk also characterize firms with high future expected growth. Small firms, firms with low levels of equity and retained earnings, firms with low profitability and low levels of sales per unit of capital, have all higher expected future growth rates than other firms. These findings suggest a tradeoff between the upside potential of high growth and the downside risk of bankruptcy. 
Keywords:  Nonlisted firms, growth, bankruptcy risk 
JEL:  G10 G30 G33 
Date:  2010–12 
URL:  http://d.repec.org/n?u=RePEc:bno:worpap:2010_31&r=rmg 
By:  Dubravka Benaković; Petra Posedel 
Abstract:  Factor models observe the sensitivity of an asset return as a function of one or more factors. This paper analyzes returns on fourteen stocks of the Croatian capital market in the period from January 2004 to October 2009 using inflation, industrial production, interest rates, market index and oil prices as factors. Both the direction and strength of the relation between the change in factors and returns are investigated. The analyses included fourteen stocks and their sensitivities to factors were estimated. The results show that the market index has the largest statistical significance for all stocks and a positive relation to returns. Interest rates, oil prices and industrial production also marked a positive relation to returns, while inflation had a negative influence. Furthermore, crosssectional regression with the estimated sensitivities used as independent variables and returns in each month as dependent variables is performed. This analysis resulted in time series of risk premiums for each factor. The most important factor affecting stock prices proved to be the market index, which had a positive risk premium. A statistically significant factor in 2004 and 2008 was also inflation, marking a negative risk premium in 2004 and a positive one in 2008. The remaining three factors have not shown as significant. 
Keywords:  factor models, risk premium, stock returns, estimated sensitivities, regression analysis 
JEL:  C22 E22 G12 
Date:  2010–12–16 
URL:  http://d.repec.org/n?u=RePEc:zag:wpaper:1012&r=rmg 
By:  Della Corte, P.; Sarno, L.; Sestieri, G. 
Abstract:  This paper examines the exchange rate predictability stemming from the equilibrium model of international financial adjustment developed by Gourinchas and Rey (2007). Using predictive variables that measure cyclical external imbalances for country pairs, we assess the ability of this model to forecast outofsample four major US dollar exchange rates using various economic criteria of model evaluation. The analysis shows that the model provides economic value to a riskaverse investor, delivering substantial utility gains when switching from a portfolio strategy based on the random walk benchmark to one that conditions on cyclical external imbalances. 
Keywords:  foreign exchange; predictability; global imbalances; fundamentals. 
JEL:  F31 F37 G15 
Date:  2011 
URL:  http://d.repec.org/n?u=RePEc:bfr:banfra:313&r=rmg 
By:  Cristina Amado (Universidade do Minho  NIPE); Timo Teräsvirta (CREATES, School of Economics and Management, Aarhus University) 
Abstract:  In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth timevarying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the conditional and unconditional variances where the transition between regimes over time is smooth. The main focus is on the multiplicative decom position that decomposes the variance into an unconditional and conditional component. A modelling strategy for the timevarying GARCH model based on the multiplicative decomposition of the variance is developed. It is heavily dependent on Lagrange multiplier type misspeci.cation tests. Finitesample properties of the strategy and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice. The results show that the long memory type behaviour of the sample autocorrelation functions of the absolute returns can also be explained by deterministic changes in the unconditional variance. 
Keywords:  Conditional heteroskedasticity; Structural change; Lagrange multiplier test; Misspeci.cation test; Nonlinear time series; Timevarying parameter model. 
JEL:  C12 C22 C51 C52 
Date:  2011 
URL:  http://d.repec.org/n?u=RePEc:nip:nipewp:01/2011&r=rmg 
By:  Marin Bozic (The Institute of Economics, Zagreb) 
Abstract:  Options on agricultural futures are popular financial instruments used for agricultural price risk management and to speculate on future price movements. Poor performance of Black’s classical option pricing model has stimulated many researchers to introduce pricing models that are more consistent with observed option premiums. However, most models are motivated solely from the standpoint of the time series properties of futures prices and need for improvements in forecasting and hedging performance. In this paper I propose a novel arbitrage pricing model motivated from the economic theory of optimal storage and consistent with implications of plant physiology on the importance of weather stress. I introduce a pricing model for options on futures based on a generalized lambda distribution (GLD) that allows greater flexibility in higher moments of the expected terminal distribution of futures price. I use times and sales data for corn futures and options for the period 19952009 to estimate the implied skewness parameter separately for each trading day. An economic explanation is then presented for interyear variations in implied skewness based on the theory of storage. After controlling for changes in planned acreage, I find a statistically significant negative relationship between ending stockstouse and implied skewness, as predicted by the theory of storage. Furthermore, intrayear dynamics of implied skewness reflect the fact that uncertainty in corn supply is resolved between late June and early October, i.e., during corn growth phases that encompass corn silking and grain maturity. Impacts of storage and weather on the distribution of terminal futures price jointly explain upwardsloping implied volatility curves. 
Keywords:  arbitrage pricing model, options on futures, generalized lambda distribution, theory of storage, skewness 
JEL:  G13 Q11 Q14 
Date:  2010–12 
URL:  http://d.repec.org/n?u=RePEc:iez:wpaper:1003&r=rmg 