This paper explores the selection of optimal portfolio by replacing the standard\nMean-Variance model by Mean-Minimum Return Level (MRL) framework\nand adding one important dimension-expectation of bounded First\nPassage Time (FPT) towards the MRL. To measure how much a given portfolio\nis exposed to risk, the new model can capture both, the amount of the\nlargest possible loss at a certain confidence level and time to such an event\noccurring. The novelty of this paper is the introduction of bounded first passage\ntime towards MRL and taking its expectation into consideration as an\nadditional factor in portfolio selection decision making. Assuming that the\nasset price dynamics follow multi-dimensional Geometric Brownian Motion\nwith drift, we obtain a portfolio wealth process for multiple assets and we\nevaluate the lowest possible value to which it can drop by a high confidence\nlevel. Then we extend our examination of the optimal portfolio selection by\nultimately obtaining the efficient surface of risky portfolios. As a result, the\npaper shows that the third dimension can make a significant difference while\nchoosing the asset weights compared to classical models ignoring the portfolio\nreturn paths as long as they achieve a desired combination of risk and return.
Loading....