A Literature Review: Modelling Dynamic Portfolio Strategy under Defaultable Assets with Stochastic Rate of Return, Rate of Inflation and Credit Spread Rate

Rizal N. A, Wiryono S.K


This research aims to find an optimal solution for dynamic portfolio in finite-time horizon under defaultable assets, which means that the assets has a chance to be liquidated in a finite time horizon, e.g corporate bond. Besides investing on those assets, investors will also have benefit in the form of consumption. As a reference in making investment decisions the concept of utility functions and volatility will play a role. Optimal portfolio composition will be obtained by maximizing the total expected discounted utility of consumption in the time span during the investment is executed and also to minimize the risk, the volatility of the investment. Further the reduced form model is applied since the assets prices can be linked with the market risk and the credit risk. The interest rate and the rate of inflation will be allowed as a representation of market risk, while the credit spread will be used as a representation of credit risk. 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. Furthermore, this problem will be solved using the stochastic dynamic programming method by assuming that market is incomplete. Depending on the chosen utility function, the optimal solution of the portfolio composition and the consumption 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. To apply dynamic programming as well as to find solutions we use Backward Stochastic Differential Equation (BSDE) where the solution can be solved explicitly, especially where the terminal value of the investment target is chosen random. Further, it will be modeled with Monte Carlo simulation and, calibrated using Indonesia data of stock and corporate bond.


Optimal Portofolio, Defaultable Assets, Dynamic Programming, Optimal Stochastic Control.

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