Nested Conditional Value-at-Risk portfolio selection: A model with temporal dependence driven by market-index volatility

Alessandro Staino and Emilio Russo

European Journal of Operational Research, 2020, vol. 280, issue 2, 741-753

Abstract: In a multistage stochastic programming framework, we develop a new method for finding an approximated portfolio allocation solution to the nested Conditional Value-at-Risk model when asset log returns are stagewise dependent. We describe asset log returns through a single-factor model where the driving factor is the market-index log return modeled by a Generalized Autoregressive Conditional Heteroskedasticity process to take into account the serial dependence usually observed. To solve the nested Conditional Value-at-Risk model, we implement a backward induction scheme coupled with cubic spline interpolation that reduces the computational complexity of the optimal portfolio allocation and allows to treat problems otherwise unmanageable.

Keywords: Stochastic programming; Portfolio selection; Time-consistency; Cubic spline interpolation; Conditional value-at-risk (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:280:y:2020:i:2:p:741-753

DOI: 10.1016/j.ejor.2019.07.032

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