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on Risk Management |
| By: | Ronald Hochreiter; David Wozabal |
| Abstract: | We apply a Coupled Markov Chain approach to model rating transitions and thereby default probabilities of companies. We estimate parameters by applying a maximum likelihood estimation using a large set of historical ratings. Given the parameters the model can be used to simulate scenarios for joint rating changes of a set of companies, enabling the use of contemporary risk management techniques. We obtain scenarios for the payment streams generated by CDX contracts and portfolios of such contracts. This allows for assessing the risk of the current position held and design portfolios which are optimal relative to the risk preferences of the investor. |
| Date: | 2009–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:0911.3802&r=rmg |
| By: | Ana-Maria Gavril |
| Abstract: | More than forty years ago researchers started to reconsider the behavior of financial data. Since then, stylized facts about financial returns have become common knowledge in economics. Characteristics as fat-tailedness, leptokurtosis and serial dependence have been extensively analyzed. As the financial world became focused on risk management and prudential supervision, various risk models have been developed. However, the first generation of risk models is highly dependent on rough assumptions, empirically contradicted, but embraced by practitioners as they benefit from a fairly easy implementation. In the context of market risk, such a proxy was developed under the name of Value at Risk, which rapidly became a standard measure for both risk managers and supervisors. The current state of affairs brings us one step closer to the death of VaR. The need for a new approach is imperative. This paper aims to bring new evidence to the limited performance of Value at Risk and test the fit of Extreme Value Theory as a complementary risk management tool for stressed market conditions, in the context of exchange rate risk. We use exchange rate returns of four currencies against the Euro and analyze the relative performance of several VaR models and Extreme Value Theory, respectively. We show that in extreme market conditions, extreme measures are required, and that no single measure can perform proper for both the centre and the tails of an exchange rate distribution. |
| Keywords: | Extreme Value Theory, VaR |
| Date: | 2009–11 |
| URL: | http://d.repec.org/n?u=RePEc:cab:wpaefr:35&r=rmg |
| By: | Xin Huang; Hao Zhou; Haibin Zhu |
| Abstract: | This paper extends the approach of measuring and stress-testing the systemic risk of a banking sector in Huang, Zhou, and Zhu (2009) to identifying various sources of financial instability and to allocating systemic risk to individual financial institutions. The systemic risk measure, defined as the insurance cost to protect against distressed losses in a banking system, is a risk-neutral concept of capital based on publicly available information that can be appropriately aggregated across different subsets. An application of our methodology to a portfolio of twenty-two major banks in Asia and the Pacific illustrates the dynamics of the spillover effects of the global financial crisis to the region. The increase in the perceived systemic risk, particularly after the failure of Lehman Brothers, was mainly driven by the heightened risk aversion and the squeezed liquidity. The analysis on the marginal contribution of individual banks to the systemic risk suggests that ``too-big-to-fail" is a valid concern from a macroprudential perspective of bank regulation. |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2009-44&r=rmg |
| By: | Cristina Belciuganu |
| Abstract: | In this paper we focus our attention on the tail risk and how different capital markets are influencing each other. Previous studies have detected return and volatility across countries during crises periods. Using the well-know Value at Risk (VaR) measure for heavy tailed financial returns, our objective is to detect if the information for a negative shock in a foreign market helps the forecast of the behavior of another market. We calculate 1 day, 95% and 99% Value at Risk for major US stock indices- S&P 500, NASDAQ 100, DJ INDUSTRIALS, major European stock indices – CAC 40, FTSE100, DAX30 and for Romanian stock index-BET. The VaR for each index is calculated the following techniques: Historical Simulation, Variance Approach and Extreme Value Theory. Spillover effects being the influence of one market on others, is examined using the Granger causality, for daily changes of the VAR series. |
| Keywords: | spillover effects, capital market |
| Date: | 2009–10 |
| URL: | http://d.repec.org/n?u=RePEc:cab:wpaefr:29&r=rmg |
| By: | Alejandro García; Andrei Prokopiw |
| Abstract: | Understanding the nature of credit risk has important implications for financial stability. Since authorities—notably, central banks—focus on risks that have systemic implications, it is crucial to develop ways to measure these risks. The difficulty lies in finding reliable measures of aggregate credit risk in the economy, as opposed to firmlevel credit risk. In this paper, the authors examine two models recently developed for this purpose: a reduced-form model applied to credit default swap index tranches, and a structural model applied to the spread on U.S. corporate bond indexes. The authors find that these models provide information on the nature of credit events—that is, whether the event is systemic or not—and on the type of risk priced in corporate bonds (i.e., credit or liquidity risk). However, although the two models provide potentially useful information for policy-makers, at this stage it is difficult to corroborate the accuracy of the information obtained from them. Further work is needed before authorities can include conclusions drawn from the two models into their policy decisions. |
| Keywords: | Credit and credit aggregates; Financial markets; Financial stability |
| JEL: | G10 G12 G13 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocadp:09-12&r=rmg |
| By: | Jokivuolle, Esa (Bank of Finland Research); Kiema, Ilkka (University of Helsinki); Vesala, Timo (Tapiola Group) |
| Abstract: | Although beneficial allocational effects have been a central motivator for the Basel II capital adequacy reform, the interaction of these effects with Basel II’s procyclical impact has been less discussed. In this paper, we investigate the effect of capital requirements on the allocation of credit and its interaction with procyclicality, and compare Basel I and Basel II type capital requirements. We consider competitive credit markets where entrepreneurs of varying ability can apply for loans for one-period investment projects of two different risk types. The risk of a project further depends on the state of the economy, modelled as a two-state Markov process. In this type of setting, excessive risk taking typically arises because higher-type borrowers cross-subsidize lower-type borrowers via a pricing regime based on average success rates. We find that risk-based capital requirements (such as Basel II) alleviate the cross-subsidization effect and can be chosen so as to implement first-best allocation. This implies that the ensuing reduction in the proportion of high-risk investments may mitigate the procyclical effect of Basel II on economic activity. Moreover, we find that optimal risk-based capital requirements should be set lower in recessions than in normal times. Our simulations show that when measured by either cumulative output or output variation, Basel II type capital requirements may actual be slightly less procyclical than flat capital requirements. The biggest reduction in procyclicality is however achieved with optimal risk-based capital requirements which are considerably higher than Basel II requirements and which are adjusted downwards in recession periods. |
| Keywords: | Basel II; bank regulation; capital requirements; credit risk; procyclicality |
| JEL: | D41 D82 G14 G21 |
| Date: | 2009–09–22 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:bofrdp:2009_023&r=rmg |
| By: | Damiano Brigo; Andrea Pallavicini; Vasileios Papatheodorou |
| Abstract: | The purpose of this paper is introducing rigorous methods and formulas for bilateral counterparty risk credit valuation adjustments (CVA's) on interest-rate portfolios. In doing so, we summarize the general arbitrage-free valuation framework for counterparty risk adjustments in presence of bilateral default risk, as developed more in detail in Brigo and Capponi (2008), including the default of the investor. We illustrate the symmetry in the valuation and show that the adjustment involves a long position in a put option plus a short position in a call option, both with zero strike and written on the residual net present value of the contract at the relevant default times. We allow for correlation between the default times of the investor and counterparty, and for correlation of each with the underlying risk factor, namely interest rates. We also analyze the often neglected impact of credit spread volatility. We include Netting in our examples, although other agreements such as Margining and Collateral are left for future work. |
| Date: | 2009–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:0911.3331&r=rmg |
| By: | Xin Huang; Hao Zhou; Haibin Zhu |
| Abstract: | In this paper we propose a framework for measuring and stress testing the systemic risk of a group of major financial institutions. The systemic risk is measured by the price of insurance against financial distress, which is based on ex ante measures of default probabilities of individual banks and forecasted asset return correlations. Importantly, using realized correlations estimated from high-frequency equity return data can significantly improve the accuracy of forecasted correlations. Our stress testing methodology, using an integrated micro-macro model, takes into account dynamic linkages between the health of major U.S. banks and macrofinancial conditions. Our results suggest that the theoretical insurance premium that would be charged to protect against losses that equal or exceed 15 percent of total liabilities of 12 major U.S. financial firms stood at $110 billion in March 2008 and had a projected upper bound of $250 billion in July 2008. |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2009-37&r=rmg |
| By: | Robert Ślepaczuk (Faculty of Economic Sciences, University of Warsaw); Grzegorz Zakrzewski (Deutsche Bank PBC S.A.) |
| Abstract: | Modeling of financial markets volatility is one of the most significant issues of contemporary finance, especially with regard to analyzing high-frequency data. Accurate quantification and forecast of volatility are of immense importance in risk management (VaR models, stress testing and worst-case scenario), models of capital market and options valuation techniques. What we show in this paper is the methodology for calculating volatility index for Polish capital market (VIW20 – index anticipating expected volatility of WIG20 index). The methods presented are based on VIX index (VIX White Paper, 2003) and enriched with necessary modifications corresponding to the character of Polish options market. Quoted on CBOE, VIX index is currently known as the best measure of capital investment risk perfectly illustrating the level of fear and emotions of market participants. The conception of volatility index is based on the combination of realized volatility and implied volatility which, using methodology of Derman et al. (1999) and reconstructing volatility surface, reflects both volatility smile as well as its term structure. The research is carried out using high-frequency data (i.e. tick data) for index options on WIG20 index for the period November 2003 - May 2007, in other words, starting with the introduction of options by Warsaw Stock Exchange. All additional simulations are carried out using data gathered in years 1998-2008. Having analyzed VIW20 index in detail, we observed its characteristic behavior during the periods of strong market turmoils. What we also present is the analysis of the influence of VIW20 and VIX index-based instruments both on construction of minimum risk portfolio and on the quality of derivatives portfolio management in which volatility risk and liquidity risk play a key role. The main objective of this paper is to provide foundations for introducing appropriate volatility indices and volatility-based derivatives. This is done with paying attention to crucial methodology changes, necessary if one considers strong markets inefficiencies in emerging countries. As the introduction of appropriate instruments will enable active management of risks that are unhedgable nowadays it will significantly contribute to the development of the given markets in the course of time. In the summary we additionally point to the benefits Warsaw Stock Exchange might obtain from, being one of the few emerging markets possessing appropriately quantified investment risk as well as derivatives to manage it. |
| Keywords: | financial market volatility, high-frequency data, realized volatility, realized range, implied and historical volatility, volatility forecasting, option pricing models, investment strategies, portfolio optimization |
| JEL: | G11 G14 G15 G24 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:war:wpaper:2009-11&r=rmg |
| By: | Florian Heider (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.); Marie Hoerova (European Central Bank, Kaiserstrasse 29, 60311 Frankfurt am Main, Germany.) |
| Abstract: | We study the functioning of secured and unsecured interbank markets in the presence of credit risk. The model generates empirical predictions that are in line with developments during the 2007-2009 financial crises. Interest rates decouple across secured and unsecured markets following an adverse shock to credit risk. The scarcity of underlying collateral may amplify the volatility of interest rates in secured markets. We use the model to discuss various policy responses to the crisis. JEL Classification: G01, G21, E58. |
| Keywords: | Financial crisis, Interbank market, Liquidity, Credit risk, Collateral. |
| Date: | 2009–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091107&r=rmg |
| By: | Zhijie Xiao (Boston College); Roger Koenker (University of Illinois Urbana-Champaign) |
| Abstract: | Conditional quantile estimation is an essential ingredient in modern risk management. Although GARCH processes have proven highly successful in modeling financial data it is generally recognized that it would be useful to consider a broader class of processes capable of representing more flexibly both asymmetry and tail behavior of conditional returns distributions. In this paper, we study estimation of conditional quantiles for GARCH models using quantile regression. Quantile regression estimation of GARCH models is highly nonlinear; we propose a simple and effective two-step approach of quantile regression estimation for linear GARCH time series. In the first step, we employ a quan- tile autoregression sieve approximation for the GARCH model by combining information over different quantiles; second stage estimation for the GARCH model is then carried out based on the first stage minimum distance estimation of the scale process of the time series. Asymptotic properties of the sieve approximation, the minimum distance estimators, and the final quantile regression estimators employing generated regressors are studied. These results are of independent interest and have applications in other quantile regression settings. Monte Carlo and empirical application results indicate that the proposed estimation methods outperform some existing conditional quantile estimation methods. |
| Keywords: | Quantile Regression, GARCH, Value-at-Risk |
| JEL: | C13 C21 C22 |
| Date: | 2009–03–13 |
| URL: | http://d.repec.org/n?u=RePEc:boc:bocoec:725&r=rmg |