The Effects of Credit Risk on Dynamic Portfolio Management: A New Computational Approach
The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.
|Date of creation:||Jan 2009|
|Date of revision:||Feb 2009|
|Contact details of provider:|| Postal: University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063|
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- Hakansson, Nils H, 1970. "Optimal Investment and Consumption Strategies Under Risk for a Class of Utility Functions," Econometrica, Econometric Society, vol. 38(5), pages 587-607, September.
- Kwamie Dunbar, 2007.
"US Corporate Default Swap Valuation: The Market Liquidity Hypothesis and Autonomous Credit Risk,"
2007-08, University of Connecticut, Department of Economics.
- Kwamie Dunbar, 2008. "US corporate default swap valuation: the market liquidity hypothesis and autonomous credit risk," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 321-334.
- Samuelson, Paul A, 1969. "Lifetime Portfolio Selection by Dynamic Stochastic Programming," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 239-46, August.
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