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Table of Content

    30 March 2018, Volume 6 Issue 1
    Incorporating Convexity in Bond Portfolio Immunization Using Multifactor Model: A Semidefinite Programming Approach
    Wei Zhu, Cai-Hong Zhang, Qian Liu, Shu-Shang Zhu
    2018, 6(1):  3-23.  doi:10.1007/s40305-018-0196-4
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    Bond portfolio immunization is a classical issue in finance. Since Macaulay gave the concept of duration in 1938, many scholars proposed different kinds of duration immunization models. In the literature of bond portfolio immunization using multifactor model, to the best of our knowledge, researchers only use the first-order immunization, which is usually called as duration immunization, and no one has considered second-order effects in immunization, which is well known as “convexity” in the case of single-factor model. In this paper, we introduce the second-order information associated with multifactor model into bond portfolio immunization and reformulate the corresponding problems as tractable semidefinite programs. Both simulation analysis and empirical study show that the second-order immunization strategies exhibit more accurate approximation to the value change of bonds and thus result in better immunization performance.

    Valuation of American Strangles Through an Optimized Lower–Upper Bound Approach
    Jing-Tang Ma, Wen-Yuan Li, Zhen-Yu Cui
    2018, 6(1):  25-47.  doi:https://doi.org/10.1007/s40305-017-0174-2
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    In this paper, we construct tight lower and upper bounds for the price of an American strangle, which is a special type of strangle consisting of long positions in an American put and an American call, where the early exercise of one side of the position will knock out the remaining side. This contract was studied in Chiarella and Ziogas (J Econ Dyn Control 29:31–62, 2005) with the corresponding nonlinear integral equations derived, which are hard to be solved efficiently through numerical methods. We extend the approach in the paper of Broadie and Detemple (RevFinance Stud 9:1211–1250, 1996) from the case of American call options to the case of American strangles. We establish theoretical properties of the lower and upper bounds, and propose a sequential optimization algorithm in approximating the early exercise boundary of the American strangle. The theoretical bounds obtained can be easily evaluated, and numerical examples confirm the accuracy of the approximations compared to the literature.

    Core of the Reinsurance Market with Dependent Risks
    Jia-Hua Zhang, Shu-Cherng Fang, Yi-Fan Xu
    2018, 6(1):  49-57.  doi:https://doi.org/10.1007/s40305-017-0173-3
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    Baton and Lemaire (Astin Bull 12:57–71, 1981) proved the nonemptiness of the core of a reinsurance market in which the risks of companies are independent. However, cases involving dependent risks have received increasing concerns in modern actuarial science. In this paper, we investigate the nonemptiness of the core of a reinsurance market where the risks of different companies may be dependent. When the exponential utility function is employed, we find an important property on risk premium and show that the core of the market is always nonempty.

    Robust Valuation, Arbitrage Ambiguity and Profit & Loss Analysis
    Yu-Hong Xu
    2018, 6(1):  59-83.  doi:https://doi.org/10.1007/s40305-017-0181-3
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    Model uncertainty is a type of inevitable financial risk. Mistakes on the choice of pricing model may cause great financial losses. In this paper we investigate financial markets with mean-volatility uncertainty. Models for stock market and option market with uncertain prior distributions are established by Peng’s G-stochastic calculus. On the hedging market, the upper price of an (exotic) option is derived following the Black–Scholes–Barenblatt equation. It is interesting that the corresponding Barenblatt equation does not depend on mean uncertainty of the underlying stocks.Appropriate definitions of arbitrage for super- and sub-hedging strategies are presented such that the super- and sub-hedging prices are reasonable. In particular, the condition of arbitrage for sub-hedging strategy fills the gap of the theory of arbitrage under model uncertainty. Finally we show that the term K of finite variance arising in the superhedging strategy is interpreted as the max Profit & Loss (P&L) of shorting a delta-hedged option. The ask-bid spread is in fact an accumulation of the superhedging P&L and the sub-hedging P&L.

    Extra Resource Allocation: A DEA Approach in the View of Efficiencies
    Meng Zhang, Li-Li Wang,Jin-Chuan Cui
    2018, 6(1):  85-106.  doi:https://doi.org/10.1007/s40305-017-0187-x
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    Data envelopment analysis has been successfully used in resource allocation problems. However, to the best of our knowledge, there are no allocation models proposed in the literature that simultaneously take both the global efficiency and growing potential into account. Hence, this research aims at developing an allocation model for extra input resources, which maximizes the global technical efficiency and scale efficiency of a decision-making unit (DMU) set while maintaining the pure technical efficiency (i.e., growing potential) of each DMU. To this purpose, we first discuss the optimal resources required by each DMU. We prove that the optimal inputs for the DMU are actually the inputs of some most productive scale size (MPSS). We then propose the allocation model based on the discussion on the case of one DMU. The allocation model is illustrated using two numerical examples.

    Optimal Portfolio and Consumption Rule with a CIR Model Under HARA Utility
    Chun-Feng Wang, Hao Chang, Zhen-Ming Fang
    2018, 6(1):  107-137.  doi:https://doi.org/10.1007/s40305-017-0189-8
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    In the real-world environments, different individuals have different risk preferences. This paper investigates the optimal portfolio and consumption rule with a Cox–Ingersoll–Ross (CIR) model in a more general utility framework. After consumption, an individual invests his wealth into the financial market with one risk-free asset and multiple risky assets, where the short-term rate is driven by the CIR model and stock price dynamics are simultaneously influenced by random sources from both stochastic interest rate and stock market itself. The individual hopes to optimize their portfolios and consumption rules to maximize expected utility of terminal wealth and intermediate consumption. Risk preference of individual is assumed to satisfy hyperbolic absolute risk aversion (HARA) utility, which contains power utility, logarithm utility, and exponential utility as special cases. By using the principle of stochastic optimality and Legendre transform-dual theory, the explicit expressions of the optimal portfolio and consumption rule are obtained. The sensitivity of the optimal strategies to main parameters is analysed by a numerical example. In addition, economic implications are also presented. Our research results show that Legendre transform-dual theory is an effective methodology in dealing with the portfolio selection problems with HARA utility and interest rate risk can be completely hedged by constructing specific portfolios.

    Time Consistent Multi-period Worst-Case Risk Measure in Robust Portfolio Selection
    Jia Liu, Zhi-Ping Chen, Yong-Chang Hui
    2018, 6(1):  138-158.  doi:https://doi.org/10.1007/s40305-017-0188-9
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    In this paper, we first construct a time consistent multi-period worst-case risk measure, which measures the dynamic investment risk period-wise from a distributionally robust perspective. Under the usually adopted uncertainty set, we derive the explicit optimal investment strategy for the multi-period robust portfolio selection problem under the multi-period worst-case risk measure. Empirical results demonstrate that the portfolio selection model under the proposed risk measure is a good complement to existing multi-period robust portfolio selection models using the adjustable robust approach.

    Explicit Solution for Constrained Optimal Execution Problem with General Correlated Market Depth
    Wei-Ping Wu, Jian-Jun Gao
    2018, 6(1):  159-174.  doi:https://doi.org/10.1007/s40305-018-0197-3
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    This work studies the constrained optimal execution problem with a random market depth in the limit order market. Motivated from the real trading activities, our execution model considers the execution bounds and allows the random market depth to be statistically correlated in different periods. Usually, it is difficult to achieve the analytical solution for this class of constrained dynamic decision problem. Thanks to the special structure of this model, by applying the proposed state separation theorem and dynamic programming, we successfully obtain the analytical execution policy. The revealed policy is of feedback nature. Examples are provided to illustrate our solution methods. Simulation results demonstrate the advantages of our model comparing with the classical execution policy.

    Time-Consistent Portfolio Policy for Asset-Liability Mean-Variance Model with State-Dependent Risk Aversion
    Liu-Meng Peng, Xiang-Yu Cui, Yun Shi
    2018, 6(1):  175-188.  doi:https://doi.org/10.1007/s40305-018-0191-9
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    In reality, when facing a multi-period asset-liability portfolio selection problem, the risk aversion attitude of a mean-variance investor may depend on the wealth level and liability level. Thus, in this paper, we propose a state-dependent risk aversion model for the investor, in which risk aversion is a linear function of current wealth level and current liability level. Due to the time inconsistency of the resulting multi-period asset-liability mean-variance model, we investigate its time-consistent portfolio policy by solving a nested mean-variance game formulation. We derive the analytical time-consistent portfolio policy, which takes a linear form of current wealth level and current liability level. We also analyze the influence of the risk aversion coefficients on the time-consistent portfolio policy and the investment performance via a numerical example.