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雷达卡
《Analysis of Portfolio Selection with Background Risk》
Chonghui Jiang
School of Management and Economics, University of Electronic Science and Technology of China
Yongkai Ma
School of Management and Economics, University of Electronic Science and Technology of China
Yunbi An Odette School of Business, University of Windsor
This paper investigates the impacts of background risk on an investor’s portfolio choice in a mean-variance framework and analyzes the properties of the selected portfolio and the investor’s hedging behaviour in the presence of background risk. Our model implies that the optimal portfolio with background risk can be separated into two independent components: the traditional mean-variance optimal portfolio and a self-financing portfolio constructed to hedge against background risk. Our results show that both the composition and risk of the optimal portfolio are greatly affected by a number of background risk factors, including the quantity and the risk of the assets that are exposed to background risk, as well as the correlation between background assets and those in the portfolio.
《Applying Linear Realization Theory to HJM Markovian Representation》
Xiaoxia Ye
The Wang Yanan Institute for Studies in Economics, Xiamen University
Abstract This paper deals with constructing Finite Dimensional Realization (FDR) of HJM with time-invariant hump shape volatility by applying Linear Realization Theory. Two realization algorithms, Standard Observable Canonical Realization and Jordan Canonical Realization, are introduced. The equivalence between Jordan Canonical Realization algorithm and commonly adopted method of constructing FDR is shown by concrete example. At the same time, simulation results indicate that Standard Observable Canonical Realization is better choice for constructing FDR than Jordan Canonical Realization in terms of more precisely capturing the state variables.
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