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on Risk Management |
| By: | Hamerle, Alfred; Knapp, Michael; Liebig, Thilo; Wildenauer, Nicole |
| Abstract: | In this paper we focus on the analysis of the effect of prediction and estimation risk on the loss distribution, risk measures and economic capital. When variables for the determination of probability of default and loss distribution have to be predicted because they are not available at the time the prediction is made, the prediction is prone to errors. The model parameters for the estimation of probability of default or asset correlation are not available, and usually have to be estimated using historical data. The incorporation of prediction and estimation risk generally leads to broader loss distributions and therefore to rising values of risk parameters such as Value at Risk or Expected Shortfall. The level of economic capital required may be strongly underestimated if prediction and estimation risk are ignored. |
| Keywords: | probability of default, PD, credit risk, default correlation, asset correlation, point in time, value at risk, estimation risk |
| JEL: | C1 G21 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdp2:4268&r=rmg |
| By: | Memmel, Christoph; Wehn, Carsten |
| Abstract: | The Value at Risk of a portfolio differs from the sum of the Values at Risk of the portfolio’s components. In this paper, we analyze the problem of how a single economic risk figure for the Value at Risk of a hypothetical portfolio composed of different commercial banks might be obtained for a supervisor. Using the daily profits and losses and the daily Value at Risk figures of twelve German banks for the period from 2001 to 2003, we estimate the Value at Risk of the entire portfolio. We assume a reduced-form model and neglect the effects of a potential bankruptcy of one of the banks. We analyze different models for the cross-correlation of the banks’ profits and losses. In an empirical study, we apply backtesting methods to determine which aggregation model leads to the best out-of-sample estimates for the portfolio’s economic risk figure. Our main findings can be summarized in three statements. (i) The portfolio’s Value at Risk can be estimated from time series data very well. (ii) During ‘normal’ times, the portfolio’s Value at Risk is much lower than the sum of the single Values at Risk. (iii) The relative marginal risk contribution depends on the bank in question and is between 0.05 and 0.62. |
| Keywords: | Value at Risk, portfolio, cross-correlation, market risk regulation, risk forecast, model validation |
| JEL: | C52 G11 G21 G28 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdp2:4257&r=rmg |
| By: | Yinqiu Lu; Jorge A. Chan-Lau |
| Abstract: | Systemic risk remains a major concern to policymakers since widespread defaults in the corporate and financial sectors could pose substantial costs to society. Forward-looking measures and/or indicators of systemic default risk are thus needed to identify potential buildups of vulnerability in advance. In this paper, we explain how to construct idiosyncratic and systemic default risk indicators using the information embedded in single-tranche standardized collateralized debt obligations (STCDOs) referencing credit derivatives indices. As an illustration, both risk indicators are constructed for the European corporate sector using midprice quotes for STCDOs referencing the iTraxx Europe index. |
| Keywords: | Financial risk , Europe , Credit risk , Risk management , Financial sector , Debt , Credit tranches , Asset prices , International capital markets , |
| Date: | 2006–05–10 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:06/107&r=rmg |
| By: | Tobias Adrian; Joshua Rosenberg |
| Abstract: | We decompose the time series of equity market risk into short- and long-run volatility components. Both components have negative and highly significant prices of risk in the cross section of equity returns. A three-factor model with the market return and the two volatility components compares favorably to benchmark models. We show that the short-run component captures market skewness risk, while the long-run component captures business cycle risk. Furthermore, short-run volatility is the more important cross-sectional risk factor, even though its average risk premium is smaller than the premium of the long-run component. |
| Keywords: | Stocks - Rate of return ; Risk |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:254&r=rmg |
| By: | Düllmann, Klaus |
| Abstract: | Results from portfolio models for credit risk tell us that loan concentration in certain industry sectors can substantially increase the value-at-risk (VaR). The purpose of this paper is to analyze whether a tractable “infection model” can provide a meaningful estimate of the impact of concentration risk on the VaR. I apply rather parsimonious data requirements, which are comparable to those for Moody’s Binomial Expansion Technique (BET) and considerably lower than for a multi-factor model. The infection model extends the BET model by introducing default infection into the hypothetical portfolio on which the real portfolio is mapped in order to obtain a simple solution for the VaR. The infection probability is calibrated for a range of typical values of input parameters, which capture the concentration of a portfolio in industry sectors, default dependencies between exposures and their credit quality. The accuracy of the new model is measured for test portfolios with a realistic industry-sector composition, obtained from the German central credit register. I find that a carefully calibrated infection model provides a reasonably close approximation to the VaR obtained from a multi-factor model and outperforms by far the BET model. The simulation results suggest that the calibrated infection model promises to provide a fit-for-purpose tool to measure concentration risk in business sectors that could be useful for risk managers and banking supervisors alike. |
| Keywords: | asset correlation, concentration risk, credit risk, multi-factor model, value-at-risk |
| JEL: | C15 C20 G21 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdp2:4359&r=rmg |
| By: | Brooks, Robin; Del Negro, Marco |
| Abstract: | We explore the link between international stock market comovement and the degree to which firms operate globally. Using stock returns and balance sheet data for companies in 20 countries, we estimate a factor model that decomposes stock returns into global, country-specific and industry-specific shocks. We find a large and highly significant link: on average, a firm raising its international sales by 10 percent raises the exposure of its stock return to global shocks by 2 percent and reduces its exposure to countryspecific shocks by 1.5 percent. This link has grown stronger since the mid-1980s. |
| Keywords: | Diversification, risk, international financial markets, industrial structure |
| JEL: | G11 G15 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdp1:3370&r=rmg |
| By: | Campbell, John Y.; Hilscher, Jens; Szilagyi, Jan |
| Abstract: | This paper explores the determinants of corporate failure and the pricing of financially distressed stocks using US data over the period 1963 to 2003. Firms with higher leverage, lower profitability, lower market capitalization, lower past stock returns, more volatile past stock returns, lower cash holdings, higher market-book ratios, and lower prices per share are more likely to file for bankruptcy, be delisted, or receive a D rating. When predicting failure at longer horizons, the most persistent firm characteristics, market capitalization, the market-book ratio, and equity volatility become relatively more significant. Our model captures much of the time variation in the aggregate failure rate. Since 1981, financially distressed stocks have delivered anomalously low returns. They have lower returns but much higher standard deviations, market betas, and loadings on value and small-cap risk factors than stocks with a low risk of failure. These patterns hold in all size quintiles but are particularly strong in smaller stocks. They are inconsistent with the conjecture that the value and size effects are compensation for the risk of financial distress. |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdp1:4221&r=rmg |
| By: | Li L. Ong; Jorge A. Chan-Lau |
| Abstract: | The increasing ability to trade credit risk in financial markets has facilitated its dispersion across the financial and other sectors. However, specific risks attached to credit risk transfer (CRT) instruments in a market with still-limited liquidity means that its rapid expansion may actually pose problems for financial sector stability in the event of a major negative shock to credit markets. This paper attempts to quantify the exposure of major U.K. financial groups to credit derivatives, by applying a vector autoregression (VAR) model to publicly available market prices. Our results indicate that use of credit derivatives does not pose a substantial threat to financial sector stability in the United Kingdom. Exposures across major financial institutions appear sufficiently diversified to limit the impact of any shock to the market, while major insurance companies are largely exposed to the "safer" senior tranches. |
| Keywords: | Credit risk , United Kingdom , Capital markets , Financial stability , |
| Date: | 2006–06–12 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:06/139&r=rmg |
| By: | Jorge A. Chan-Lau |
| Abstract: | This paper finds that systematic default risk, or the event of widespread defaults in the corporate sector, is an important determinant of equity returns. Moreover, the market price of systematic default risk is one order of magnitude higher than the market price of other risk factors. In contrast to studies by Fama and French (1993, 1996 ) and Vassalou and Xing (2004), this paper uses a market-based measure of systematic default risk. The measure is constructed using price information from credit derivatives prices, namely the spreads of standardized single-tranche collateralized debt obligations on credit derivatives indices. |
| Date: | 2006–06–22 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:06/148&r=rmg |
| By: | Renzo G. Avesani; Kexue Liu; Alin Mirestean; Jean Salvati |
| Abstract: | The paper presents the basic Credit Risk+ model, and proposes some modifications. This model could be useful in the stress-testing financial sector assesments process as a benchmark for credit risk evaluations. First, we present the setting and basic definitions common to all the model specifications used in this paper. Then, we proceed from the simplest model based on Bernoulli-distributed default events and known default probabilities to the fully-fledged Credit Risk+ implementation. The latter is based on the Poisson approximation and uncertain default probabilities determined by mutually independent risk factors. As an extension we present a Credit Risk+ specification with correlated risk factors as in Giese (2003). Finally, we illustrate the characteristics and the results obtained from the different models using a specific portfolio of obligors. |
| Date: | 2006–06–06 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:06/134&r=rmg |
| By: | von Kalckreuth, Ulf |
| Abstract: | In recent years, a number of papers have established a new empirical regularity. Stocks of distressed firms vastly underperform those of financially healthy firms. It is not necessary to attribute the negative excess returns of distressed firms to inefficient or irrational markets. We show that negative excess returns are the equilibrium outcome when a subset of participants is able to draw returns "in kind" from distressed companies. For firms close to bankruptcy, non-cash returns to ownership will be the dominant form of return to equity. If markets expect a contest for control, these returns will show up in stock valuation. The governance problem described here creates a link between the financial position of a firm and real allocation that may amplify macroeconomic real or financial shocks. |
| Keywords: | stock market anomalies, default risk, private benefits, moral hazard, limited liability |
| JEL: | G12 G14 G33 G34 |
| Date: | 2005 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdp1:4234&r=rmg |