DYNAMIC PORTFOLIO UNDER DEFAULTY ASSETS

• Main Author: Amelda Rizal, Nora
• Format: Dissertations
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/86876
• Institution: Institut Teknologi Bandung

This research aims to ?nd an optimal solution for dynamic portfolio in ?nite-time horizon under defaulty assets. Defaulty assets mean that the assets has a chance to be liquidated in a ?nite time horizon, e.g corporate bond. As a reference in making investment decisions, the concept of utility functions will play a role. Optimal portfolio composition will be obtained by maximizing the total expected discounted utility in the time span during the investment is executed. To determine the ?nancial defaulty assets, there are two methods that can be used, namely the reduced form and the structural methods. The ?rst method is more applicable because the assets price can be linked with the market risk and credit risk than the latter method. The interest rate and the rate of in?ation will be allowed as a representation of market risk, while the credit spread will be used as a representation of credit risk. Furthermore, the dynamic of asset prices can be derived analytically by using Ito Calculus in the form of the movement of the three risk factors above. The dynamic process of investor wealth will be derived from the dynamics of asset pricing model which will be inbounded into portfolio composition model This problem will be solved using the stochastic dynamic programming method. Depending on the chosen utility function, the optimal solution of the portfolio composition can be found explicitly in the form of feedback control. This is possible since the dynamic of the wealth process of the control variable is linear. The closed form solution will give the proportion of assets between equity, bond and money account. The complicated equation of bond pricing will follow recovery market value (RMV) methods. The result later will be calibrated and simulated with the random chosen values that closed to Indonesian market. The simulation shows that the asset composition will change not only because of the risks, mean and volatility that belong as common parameters on assets, but also moved by the change of the correlation values, investor types and also recovery rate.