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on Risk Management |
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Issue of 2006‒09‒11
four papers chosen by |
| By: | Jan Pieter Krahnen (Imperial College, London); Berc Rustem (Imperial College, London); Volker Wieland (University of Frankfurt); Stan Zakovic (Imperial College London) |
| Abstract: | Large banks often sell part of their loan portfolio in the form of collateralized debt obligations (CDO) to investors. In this paper we raise the question whether credit asset securitization affects the cyclicality (or commonality) of bank equity values. The commonality of bank equity values reflects a major component of systemic risks in the banking market, caused by correlated defaults of loans in the banks’ loan books. Our simulations take into account the major stylized fact of CDO transactions, the nonproportional nature of risk sharing that goes along with tranching. We provide a theoretical framework for the risk transfer through securitization that builds on a macro risk factor and an idiosyncratic risk factor, allowing an identification of the types of risk that the individual tranche holders bear. This allows conclusions about the risk positions of issuing banks after risk transfer. Building on the strict subordination of tranches, we first evaluate the correlation properties both within and across risk classes. We then determine the effect of securitization on the systematic risk of all tranches, and derive its effect on the issuing bank’s equity beta. The simulation results show that under plausible assumptions concerning bank reinvestment behaviour and capital structure choice, the issuing intermediary’s systematic risk tends to rise. We discuss the implications of our findings for financial stability supervision. |
| JEL: | G28 |
| Date: | 2006–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cfs:cfswop:wp2000604&r=rmg |
| By: | Bohl, Martin; Döpke, Jörg; Pierdzioch, Christian |
| Abstract: | Using monthly data for the period 1953–2003, we apply a real-time modeling approach to investigate the implications of U.S. political stock market anomalies for forecasting excess stock returns. Our empirical findings show that political variables, selected on the basis of widely used model selection criteria, are often included in real-time forecasting models. However, they do not contribute to systematically improving the performance of simple trading rules. For this reason, political stock market anomalies are not necessarily an indication of market inefficiency. |
| Keywords: | Political stock market anomalies, predictability of stock returns, efficient markets hypothesis, real-time forecasting |
| JEL: | G11 G14 |
| Date: | 2006 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdp1:4723&r=rmg |
| By: | Tilke, Stephan |
| Abstract: | The objective of this paper is to study the effect of importance sampling (IS) techniques on stochastic credit portfolio optimization methods. I introduce a framework that leads to a reduction of volatility of resulting optimal portfolio asset weights. Performance of the method is documented in terms of implementation simplicity and accuracy. It is shown that the incorporated methods make solutions more precise given a limited computer performance by means of a reduced size of the initially necessary optimization model. For a presented example variance reduction of risk measures and asset weights by a factor of at least 350 was achieved. I finally outline how results can be mapped into business practice by utilizing readily available software such as RiskMetrics’ CreditManager as basis for constructing a portfolio optimization model that is enhanced by means of IS. |
| Keywords: | CVaR, credit risk, stochastic portfolio optimization, importance sampling, CreditMetrics, CreditManager |
| JEL: | C15 C61 G11 G28 |
| Date: | 2006–08–31 |
| URL: | http://d.repec.org/n?u=RePEc:bay:rdwiwi:706&r=rmg |
| By: | Verbeek, M. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University) |
| Abstract: | The use of advanced econometric techniques is becoming more and more standard in risk management and investments. Empirical results are important for, e.g., deriving and evaluating asset pricing models, determining attractive investment strategies or the evaluation of the performance of mutual funds. On the basis of a number of examples, the author illustrates the power of empirical evidence, paying particular attention to cases where statistical evidence can be highly misleading. |
| Keywords: | data snooping;look-ahead bias;mutual funds;predictability;efficient market hypothesis; |
| Date: | 2002–06–21 |
| URL: | http://d.repec.org/n?u=RePEc:dgr:euriar:3000349&r=rmg |