Selecting Valuable Stock Using Genetic Algorithm
نویسندگان
چکیده
In this study, we utilize the genetic algorithm (GA) to select high quality stocks with investment value. Given the fundamental financial and price information of stocks trading, we attempt to use GA to identify stocks that are likely to outperform the market by having excess returns. To evaluate the efficiency of the GA for stock selection, the return of equally weighted portfolio formed by the stocks selected by GA is used as evaluation criterion. Experiment results reveal that the proposed GA for stock selection provides a very flexible and useful tool to assist the investors in selecting valuable stocks.
منابع مشابه
Using Genetic Algorithm in Solving Stochastic Programming for Multi-Objective Portfolio Selection in Tehran Stock Exchange
Investor decision making has always been affected by two factors: risk and returns. Considering risk, the investor expects an acceptable return on the investment decision horizon. Accordingly, defining goals and constraints for each investor can have unique prioritization. This paper develops several approaches to multi criteria portfolio optimization. The maximization of stock returns, the pow...
متن کاملOptimal Feature Extraction for Discriminating Raman Spectra of Different Skin Samples using Statistical Methods and Genetic Algorithm
Introduction: Raman spectroscopy, that is a spectroscopic technique based on inelastic scattering of monochromatic light, can provide valuable information about molecular vibrations, so using this technique we can study molecular changes in a sample. Material and Methods: In this research, 153 Raman spectra obtained from normal and dried skin samples. Baseline and electrical noise were eliminat...
متن کاملUsing the Imperialistic Competitive Algorithm Model in Bankruptcy Prediction and Comparison with Genetic Algorithm Model in Listed Companies of Tehran Stock Exchange
Bankruptcy prediction is a major issue in classification of companies. Since bankruptcy is extremely costly, investors, owners, managers, creditors, and government agencies are interested in evaluating the financial status of companies. This study tried to predict bankruptcy among companies registered in Tehran Stock Exchange (Iran) by designing imperialist competitive algorithm and genetic alg...
متن کاملForecasting Stock Market Using Wavelet Transforms and Neural Networks: An integrated system based on Fuzzy Genetic algorithm (Case study of price index of Tehran Stock Exchange)
The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...
متن کاملOptimizing the Prediction Model of Stock Price in Pharmaceutical Companies Using Multiple Objective Particle Swarm Optimization Algorithm (MOPSO)
The purpose of this study is to optimize the stock price forecasting model with meta-innovation method in pharmaceutical companies.In this research, stock portfolio optimization has been done in two separate phases.The first phase is related to forecasting stock futures based on past stock information, which is forecasting the stock price using artificial neural network.The neural network used ...
متن کامل