A hybrid stock trading system using genetic network programming and mean conditional value-at-risk

نویسندگان

  • Yan Chen
  • Xuancheng Wang
چکیده

This paper describes a hybrid stock trading system based on Genetic Network Programming (GNP) and Mean Conditional Value-at-Risk Model (GNP–CVaR). The proposed method, combining the advantages of evolutionary algorithms and statistical model, has provided useful tools to construct portfolios and generate effective stock trading strategies for investors with different risk-attitudes. Simulation results on five stock indices show that model based on GNP and maximum Sharpe Ratio portfolio performs the best in bull market, and that based on GNP and the global minimum risk portfolio performs the best in bear market. The portfolios constructed by Markowitz’s mean–variance model performs the same as mean-CVaR model. It is clarified that the proposed system significantly improves the function and efficiency of original GNP, which can help investors make profitable decisions. 2014 Elsevier B.V. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimal Portfolio Selection for Tehran Stock Exchange Using Conditional, Partitioned and Worst-case Value at Risk Measures

This paper presents an optimal portfolio selection approach based on value at risk (VaR), conditional value at risk (CVaR), worst-case value at risk (WVaR) and partitioned value at risk (PVaR) measures as well as calculating these risk measures. Mathematical solution methods for solving these optimization problems are inadequate and very complex for a portfolio with high number of assets. For t...

متن کامل

Optimizing 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

A genetic network programming model for portfolio optimization by generating risk-adjusted trading rules

Genetic network programming (GNP) as an evolutionary computation method has been used for stock trading recently. Former researches confirm the efficiency of trading rules which are created by GNP. In this paper, GNP has been applied for stock portfolio optimization by generating risk-adjusted trading rules. There are two main novelties in this paper: 1) we use conditional Sharp ratio as a risk...

متن کامل

Optimal Portfolio Allocation based on two Novel Risk Measures and Genetic Algorithm

The problem of optimal portfolio selection has attracted a great attention in the finance and optimization field. The future stock price should be predicted in an acceptable precision, and a suitable model and criterion for risk and the expected return of the stock portfolio should be proposed in order to solve the optimization problem. In this paper, two new criterions for the risk of stock pr...

متن کامل

Global Supply Chain Management under Carbon Emission Trading Program Using Mixed Integer Programming and Genetic Algorithm

In this paper, the transportation problem under the carbon emission trading program ismodelled by mathematical programming and genetic algorithm. Since green supply chain issuesbecome important and new legislations are taken into account, carbon emissions costs are included inthe total costs of the supply chain. The optimisation model has the ability to minimise the total costsand provides the ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • European Journal of Operational Research

دوره 240  شماره 

صفحات  -

تاریخ انتشار 2015