|
on Risk Management |
| By: | Ron Anderson |
| Abstract: | In this paper we study the pricing of credit risk as re°ected in the market for credit default swaps (CDS) between 2003 and 2008. This market has newly emerged as the reference for credit risk pricing because of its use of standardized contract speci¯cations and has achieved a higher level of liquidity than typically prevails in the markets for the underlying notes and bonds of the named corporate issuers. We initiate our exploration by studying a particular case which allows us to set out some of the issues of CDS pricing in a simple way. We show that for the purposes of accounting for relatively short-term changes of CDS spreads, an approach based on the structural (or ¯rm-value based) models of credit risk faces an important obstacle in that reliable information about the ¯rm's liabilities required to calculate the \\distance to default¶ are available only quarterly or in some cases annually. Thus structural models account for short-term movements in credit spreads largely by changes in the issuer's equity price. In the case studied we show the e®ect of equity returns in explaining weekly changes of spreads is insigni¯cant and of the wrong sign. In examination of particular episodes when the CDS spread was particularly delinked from the ¯rm's equity series, we ¯nd that a likely explanation is changes in expectations about the ¯rm's planned capital market operations. Since these are hard to capture in an observed proxy variable, we argued that this motivates the use of latent variable models that have recently been employed in the credit risk literature. We further see that movements in the CDS spreads for the particlar name chosen are highly correlated with an index of CDS spreads for industrial Blue-chip names. |
| Date: | 2008–06 |
| URL: | http://d.repec.org/n?u=RePEc:fmg:fmgdps:dp615&r=rmg |
| By: | Alejandro Reveiz; Carlos Eduardo León |
| Abstract: | First developed by Markowitz (1952), the mean-variance framework is the most widespread theoretical approximation to the portfolio problem. Nevertheless, successful application in the investment community has been limited. Assumptions such as normality of returns and a static correlation matrix could partially account for this. To overcome some of the limitations of the mean-variance framework, mainly the choice of the risk metric and the inconvenience of using an estimated correlation matrix typical of tranquil or euphoria periods, this paper proposes an alternative risk measure: the maximum drawdown (MDD), and combines it with a wealth creation measure to define a new portfolio optimization space. Like other market practitioners’ measures, MDD lacks of a complete and solid theoretical foundation. In an effort to contribute to its theoretical foundation, this paper uses common sense and financial intuition to introduce such measure, followed by a review of its technical advantages and coherence for risk management. Finally, an application of a MDD risk metric based portfolio optimization model is presented. The main findings indicate this proposal may effectively help overcome some of the traditional mean-variance shortcomings and provide some useful tools for portfolio optimization in practice. For long-term performance driven portfolios, such as pension funds, this approach may yield interesting results because it focuses on wealth creation over the long run. |
| Date: | 2008–06–22 |
| URL: | http://d.repec.org/n?u=RePEc:col:000094:004732&r=rmg |
| By: | Wolfgang Härdle; Ostap Okhrin; Yarema Okhrin |
| Abstract: | In this paper we provide a review of copula theory with applications to finance. We illustrate the idea on the bivariate framework and discuss the simple, elliptical and Archimedean classes of copulae. Since the cop- ulae model the dependency structure between random variables, next we explain the link between the copulae and common dependency measures, such as Kendall's tau and Spearman's rho. In the next section the copulae are generalized to the multivariate case. In this general setup we discuss and provide an intensive literature review of estimation and simulation techniques. Separate section is devoted to the goodness-of-fit tests. The importance of copulae in finance we illustrate on the example of asset allocation problems, Value-at-Risk and time series models. The paper is complemented with an extensive simulation study and an application to financial data. |
| Keywords: | Distribution functions, Dimension Reduction, Risk management, Statistical models |
| JEL: | C00 C14 C51 |
| Date: | 2008–06 |
| URL: | http://d.repec.org/n?u=RePEc:hum:wpaper:sfb649dp2008-043&r=rmg |