The stock evaluation process plays an important role in portfolio selection because it is the prerequisite for investment and directly influences on the stock allocation. This paper presents a methodology based on Data Envelopment Analysis for portfolio selection, decision making units which can be stocks or other financial assets. First, DMUs efficiencies are computed based on input/output com...

The central message of this paper is that nobody should be using the sample covariance matrix for the purpose of portfolio optimization. It contains estimation error of the kind most likely to perturb a mean-variance optimizer. In its place, we suggest using the matrix obtained from the sample covariance matrix through a transformation called shrinkage. This tends to pull the most extreme coeff...

The de nition of universal portfolio was introduced in the nancial literature in order to describe the class of portfolios which are constructed directly from the available observations of the stocks behavior without any assumptions about their statistical properties. Cover [6] has shown that one can construct such portfolio using only observations of the past stock prices which generates the s...

This study aimed to present a model for portfolio risk premium assessment of companies listed in Tehran Stock Exchange. In order to achieve this purpose, monthly data of 150 companies listed in Tehran Stock Exchange during 2007-2017 was used. In this study, the predictive powers of FamaFrench three-factor model [11], Carhart four-factor model [1], Fama - French five-factor model [24], Brousseau...

In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...

We survey some recent developments in the area of continuous-time portfolio optimization. These will include the use of options and of defaultable assets as investment classes and the presentation of a worst-case investment approach that takes the possibility of stock market crashes into account.

The purpose of this paper is to examine the application LSTM and mean variance portfolio optimization in Chinese stock market. 20 stocks are selected from CSI 300 components, we collect their High, Low, Open, Adjust Close trade volume June 16th 2020 2022. Then use model forecast price. results used construct 2 portfolios. One maximize Sharpe ratio, other minimize variance. From April 6th 2022, ...

We consider a continuous-time stochastic optimization problem with infinite horizon, linear dynamics, and cone constraintswhich includes as a particular case portfolio selection problems under transaction costs for models of stock and currency markets. Using an appropriate geometric formalism we show that the Bellman function is the unique viscosity solution of a HJB equation.

return maximization or risk minimization is goal in portfolio optimization based on mean variance theory. the structure of correlation matrices and individual variance of each asset are two main factors in optimization with risk minimization object. it’s necessary to use appropriate variance and correlation coefficient for time series with clustering volatilities feature, too. in this research,...