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  Issue 11 | Archive May 2012

RMI Joint Seminars
March – April 2012

On 5 April 2012, Dr. Yamazaki Kazutoshi, assistant professor at the Center for the Study of Finance and Insurance at Osaka University, gave a talk on his paper named “Toward a Generalization of the Leland-Toft Optimal Capital Structure Model”. The talk was a joint event organized by RMI and the Department of Mathematics. This paper generalized the problem by allowing the values of bankruptcy costs, coupon rates and tax benefits dependent on the firm's asset value. By using the fluctuation identities for the spectrally negative process, he and his co-author obtained a candidate bankruptcy level as well as a sufficient condition for optimality. The optimality held in particular when, with respect to the asset value, the coupon rate was decreasing, the value of tax benefits was increasing, and the loss amount at bankruptcy was increasing and concave. They argued that this solution admitted a semi-explicit form, and this allowed for instant computation of the optimal bankruptcy levels, equity/debt values and optimal leverage ratios.

Earlier on 14 March 2012, Prof. Rafał Weron from Poland’s Wrocław University of Technology discussed his paper titled “Inference for Markov Regime-Switching Models of Electricity Spot Prices” at a joint seminar held by RMI and Department of Statistics and Applied Probability. In the first part of the talk, he presented motivation for using certain types of Markov Regime-Switching (MRS) models in electricity markets and provided some illustrative empirical examples. In the second part he covered the calibration of such models, in particular, a new estimation method that greatly reduced the computational burden induced by the introduction of independent regimes. He then constructed a goodness-of-fit testing scheme for the marginal distribution of regime-switching models. The test was based on the Kolmogorov-Smirnov supremum-distance statistic. While the existence of distinct regimes in electricity spot prices was generally unquestionable (due to the supply stack structure), the actual goodness-of-fit of the models required statistical validation. He applied the new methods to a sample series of electricity spot prices from various power markets. He then argued that the proposed MRS models fit these datasets well and replicated the major stylized facts of electricity spot price dynamics.

On 27 March 2012, Prof. Asger Lunde, Professor at Department of Economics and Business from Denmark’s Aarhus University presented a paper on “Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and Covolatility” at a joint seminar co-organized by the RMI and the Department of Economics. In his talk, Prof. Lunde introduced a multivariate GARCH model that incorporates realized measures of volatility and covolatility. The realized measures extract information about the current level of volatility and covolatility from high-frequency data, which is particularly useful for the modeling of return volatility during periods with rapid changes in volatility and covolatility. When applied to market returns in conjunction with returns on an individual asset, the model yielded a dynamic model of the conditional regression coefficient that is known as the beta. He and his co-authors applied the model to a large set of assets and found the conditional betas to be far more variable than what are usually found with rolling-window regressions based exclusively on daily returns. In the empirical part, they examined the cross-sectional as well as the time variation of the conditional beta series during the financial crises.

RMI Research Seminar
23 March 2012

An RMI research seminar saw Prof. Yukio Muromachi, professor of the Graduate School of Social Sciences, Tokyo Metropolitan University, presenting on “Risk Evaluation of A Portfolio Including Forward-looking Stress Events with Probabilities”.  Prof. Muromachi and his co-authors proposed a risk evaluation model for a portfolio including stress events with probabilities implied from market data. Their model is based on the implied copula proposed by Hull and White (2006) for pricing Collateralized Debt Obligations (CDOs), especially synthetic CDOs. Hull and White (2006) showed that even in prosperous periods there existed small probability masses in the extremely high default probability regions, which implied the latent fear of the market participants against catastrophic default events.

Calling such events “market-implied stress scenarios”, the authors showed that the loss distributions of CDO tranches and a bond portfolio could be constructed numerically to include the effects of such events, and that they had strong influences on the risk measures such as VaR. Additionally, their numerical example showed when the extreme losses were incurred in the CDO tranches, most of the losses came from the crash of the CDO prices, not from the actual default losses. They concluded that their method was one of the possible ways to connect the existing statistical models with stress tests and to obtain useful information.

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Published quarterly by Risk Management Institute, NUS
Editor: Ivy Wang (rmiwy@nus.edu.sg)