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Variance-Optimal Hedging for the Process Based on Non-Extensive Statistical Mechanics and Poisson Jumps

100%

Zhao P., Xiao Q.

Acta Physica Polonica A

2016

vol. 129

issue 6

1252-1256

In this study, we consider a minimum-variance hedging problem in an incomplete market, in which the risky asset is driven by the process based on non-extensive statistical mechanics and Poisson jumps. Using the stochastic control theory and backward stochastic differential equation method, we obtain a closed-form solution for the minimum-variance hedging policy.

Optimal Portfolio under Non-Extensive Statistical Mechanics and Value-at-Risk Constraints

81%

Zhao P., Wang J., Song Y.

Acta Physica Polonica A

2018

vol. 133

issue 5

1170-1173

In this study, we consider the optimal portfolio selection problem with a value-at-risk constraint in the non-extensive statistical mechanics framework. We propose a portfolio selection model, which is suitable not only for normal return distributions, but also for non-normal return distributions. Using Chinese stock data, under the normal and q-Gaussian return distributions, we provide empirical results. The results indicate that portfolio selections under the q-Gaussian return distributions are considerably different from those under the normal return distributions. Moreover, by using the q-Gaussian distribution, the underestimated portfolio risk can be effectively avoided.

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2 Acta Physica Polonica A

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1 2016

2 Zhao P.

1 Song Y.

1 Wang J.

1 Xiao Q.

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Variance-Optimal Hedging for the Process Based on Non-Extensive Statistical Mechanics and Poisson Jumps

Optimal Portfolio under Non-Extensive Statistical Mechanics and Value-at-Risk Constraints