本文延續Huang(2004, 2008)的研究，將單期與多期挹注資金的資產負債管理議題專化於DC確定提撥退休金制度上，其研究將問題化成二次函數，以一般化最小平方法(Generalized least square, GLS)求出具有唯一解特性的決策變數，利用的軟體求解速度相當快，能有效率地一次找出多項資產配置比例。
本研究引入三種投資模型及其薪資模型，分別是Wilkie(1995)模型、MacDonald and Cairns(2007)模型、Huang and Cairns(2006)及Li(2009)，以蒙地卡羅模型模擬出各投資標的年報酬率與薪資水準，並利用這些預期的模擬值在負債目標控制為隨機成長或固定比例成長下，找出最適投資比例、每期挹注的額度與提撥比例。
最適配置為了解決下方風險(downside risk)問題，在允許限定風險容忍度下去最大化投資績效，本研究將目標函數加入衡量報酬項，依據員工希望的報酬，討論此項權重如何最適。亦加入交易成本項以反映實務情況，此投資總交易成本為權重的函數，於足夠支付交易成本的前提下找出權重最小值。

In this study, the simulation of the return for each investment and wage pattern is via introduction of three investment model and their wage model, namely, Wilkie (1995) model, MacDonald and Cairns (2007) model, Huang and Cairns (2006) model and Li (2009), by using Monte Carlo simulation. The optimal contribution rate of investments, the amount of injection of each period, and income replacement ratio are determined when simulation is targeted in the balance control for the random growth or growth under a fixed rate of liabilities.
The asset-liability management of single-period and multi-period injection of funds is specialized in the Defined contribution plan (DC), which is the extension of Huang’s (2004, 2008) study. Huang’s research transforming his argument into a quadratic function to generalized least squares method (GLS) having a unique solution to derive the decision-making variables. This method can efficiently find a set of allocation by software at a fairly rapid speed.
The optimal allocation is to maximize investment performance subject to a limited risk had to tolerance for deal with downside risk. This study ameliorates the objective function by adding a constant term, which does not affect the investment decision-making variable. This new generalized least squares method use a constant represented as a weight, which is based on the desire asset of the employee. This study also takes transaction costs into consideration to reflect the practical situation. The total transaction costs are the function of the weight introduced into the new objective function. The minimum of weight can be reached when the goal is set to be sufficient to cover the transaction costs

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