Optimal Multiplier of Portfolio Insurance Strategies

Portfolio insurance strategies control the risk of a portfolio within a certain level. While protecting the asset value from being below a predefined bottom, portfolio insurance strategies also engage in aggressive profiting. Portfolio insurance strategies can be categorized into Option Based Portfolio Insurance and dynamic portfolio insurance such as Constant Proportion Portfolio Insurance (CPPI) and Time-Invariant Portfolio Protection (TIPP). The simplicity and flexibility of CPPI and TIPP have made them representative of contemporary portfolio insurance strategy. In the decision-making of a portfolio insurance problem, the investor must select the target asset or portfolio before determining the multiplier and in turn the risk position. Obviously, an optimal multiplier exists for the problem and is intimately related to the risk-free rate, floor and asset performance. Although the multiplier determination strongly influences the performances of CPPI and TIPP-based portfolio insurance, of which related studies appear insufficient. This studies uses the standard deviation of return rate as the risk measure and develops a decision support model for determining the optimal multiplier of CPPI and TIPP through Monte Carlo simulation and neural network learning. Given risk-free rate, floor, and the mean and standard deviation of return rate, the model is capable of estimating the probability distribution of the optimal multiplier. The investor can then select the multiplier based on the distribution and even change it by testing if it has significantly changed when the portfolio performance changes. Also, this study investigates the relationship between the multiplier and portfolio selection.

Project ID:PF9907-5815
External Project ID:NSC99-2410-H182-021-MY2