In this study, a double-stage genetic optimization algorithm is proposed for portfolio selection. In the first stage, a genetic algorithm is used to identify good quality assets in terms of asset ranking. In the second stage, investment allocation in the selected good quality assets is optimized using a genetic algorithm based on Markowitz’s theory. Through the two-stage genetic optimization pr...

Portfolio optimization using private equity is typically based on one of three indices: listed private equity, transaction-based private equity, or appraisal value-based private equity indices. However, we show that none of these indices is fully suitable for portfolio optimization. We introduce here a new benchmark index for venture capital and buyouts, which is updated monthly, adjusted for a...

in order to use an islamic financial instrument, this paper intends to measure and evaluate negative and positive deviations from target rate of return in investment opportunity evaluation,that leads to presenting an upside potential- adjusted risk measure. this risk measure named upside potential adjusted risk measure (alpm) is generally applicable and provides assumptions of variance, downsid...

investors use different approaches to select optimal portfolio. so, optimal investment choices according to return can be interpreted in different models. the traditional approach to allocate portfolio selection called a mean - variance explains. another approach is markov chain. markov chain is a random process without memory. this means that the conditional probability distribution of the nex...

Although the use of real options for valuation of information technology (IT) investments has been well-documented, little research has been conducted to examine its relevance for prioritizing a portfolio of projects. When the effect of project interdependencies is considered, the complexity of optimally prioritizing even a small number of projects poses several challenges in applying real opti...

This study investigates the performance of Bitcoin as a diversifier under different constraining portfolio optimization frameworks. The employs frameworks that seek to maximize risk-adjusted returns (Sharpe ratio) by optimizing allocations each asset class (asset allocation). attributes are evaluated comparing portfolios both with and without ranging from equal-weighted, risk-parity, semi-const...

The Markowitz model for single period portfolio optimization quantifies the problem by means of only two criteria: the mean, representing the expected outcome, and the risk, a scalar measure of the variability of outcomes. The classical Markowitz model uses the variance as the risk measure, thus resulting in a quadratic optimization problem. Following Sharpe’s work on linear approximation to th...