Investigating the Performance of Portfolio Insurance Strategies under a Regime Switching Markov Model in Tehran Stock Exchange

Document Type : Research Paper


1 PhD Candidate, Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.

2 Associate Prof., Department of Mathematics, Faculty of Mathematics, Zanjan University of Graduate Studies, Zanjan, Iran.

3 Associate Prof., Department of Accounting, Faculty of Economics and Management, Urmia University, Urmia, Iran.


Objective: Portfolio insurance strategies are structural methods that provide a certain level of certainty by setting a floor value. In other words, using these strategies can achieve a predetermined minimum return. PI strategies, while maintaining the potential for capital growth in bull markets, provide downside protection in the bear market and at the end of the investment horizon provide a guaranteed minimum return. This study explains how to construct a portfolio and allocate assets by using these strategies, and also examines the performance of a constant proportion portfolio insurance (CPPI) strategy and value at risk based portfolio insurance (VBPI).
Methods: In order to evaluate the performance of constant proportion portfolio insurance strategy and value at risk based portfolio insurance, first the mathematical model of the Constrained Constant Proportion portfolio insurance is presented. In the Constrained case risk-free borrowing is not possible which makes the model more realistic. By using the Fourier transform of the characteristic function, the density function of returns has been extracted. By using the Density Function, the value at risk is calculated at the desired confidence levels, and finally, the mathematical model of the risk-based approach is presented. A variable-rate model is used to estimate the risk-taking movement of the asset, which is closer to reality. To estimate the dynamic of the risky asset regime-switching model has been used to make the model closer to reality.
Results: The results show that both strategies have been successful in controlling risk, and this performance improves with increasing confidence level and frequency of portfolio rebalancing. Omega measure shows that the performance of the constant proportion portfolio insurance is better at low thresholds. Also, the dispersion of the simulated results for the final value of the portfolios showed that the constant proportion portfolio insurance works better in protecting the floor.
Conclusion: Portfolio insurance strategies can dramatically improve the controlling of downside risk relative to buy and hold strategy and the performance of CPPI strategy is better than VBPI according to the performance measures.


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