A Scenario Generation Method with Heteroskedasticity and Moment Matching

Erhan Deniz and James Luxhøj

The Engineering Economist, 2011, vol. 56, issue 3, 231-253

Abstract: We present a portfolio management framework composed of a new scenario generation algorithm and a stochastic programming (SP) model. The algorithm is built on heteroskedastic models and a moment matching approach to construct a scenario tree that is a calibrated representation of the randomness in risky asset returns. We also present a multistage SP model that maximizes the expected final wealth and controls the risk exposure through limiting conditional value-at-risk (CVaR) at each decision epoch over the scenario tree generated by the algorithm.

Date: 2011
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DOI: 10.1080/0013791X.2011.599918

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