This thesis proposes an Artificial Neural Network (ANN) enhanced decision support system for financial risk management. The decision support system allows hedgers to maximise their expected return while practising the hedge against financial risks. The importance of the research stems from the fact that it can be used to reduce the risk associated with adverse price movements in the stock marke...

A novel method of stock portfolio management by using technical indicators is proposed in this paper. The method hybridizes the consensus trading signals generated by the gene expression programming (GEP) proposed by Lee et al., and the portfolio redemption scheme proposed by Tsai et al. with our stock ranking functions. The indicators were used not only for trading, but also for selecting prom...

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...

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...

This paper describes a portfolio optimization system by using Neuro-Fuzzy framework in order to manage stock portfolio. It is great importance to stock investors and applied researchers. The proposed portfolio optimization approach Neuro-Fuzzy System reasoning in order to make a more yields from the stock portfolio, and hence maximize return and minimize risk of a stock portfolio through divers...

Risk management in this paper is focused on multivariate risk-return decision making assuming time-varying estimation. Empirical research in risk management showed that the static "mean-variance" methodology in portfolio optimization is very restrictive with unrealistic assumptions. The objective of this paper is estimation of time-varying portfolio stocks weights by constraints on risk measure...

In the areas of investment research and applications, feasible quantitative models include methodologies stemming from soft computing for prediction of financial time series, multi-objective optimization of investment return and risk reduction, as well as selection of investment instruments for portfolio management, etc. Among all these, stock selection has long been identified as a challenging...

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, an...