Hybrid Strategy for Stock Trading

International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue VII, July 2018 | ISSN 2321–2705

Hybrid Strategy for Stock Trading

Tania Anna Baby^#

^#Research Scholar, APJ Abdul Kalam Technological University, College of Engineering, Trivandrum, Kerala, India

Abstract – Trading Strategies provide a set of trading rules defining the conditions that must be occurred for a trade entry and exit to occur. Profit Gain is the final aim of a trader competing in financial markets. In order to earn profits, traders find the help of new decision support systems. Nowadays, investors started adopting technical indicators for trading in stock markets. The trading decision prediction is one of the problems faced by many traders. The trading decision prediction is considered as a categorization problem. Integration of technical indicators with trading rules helps traders to decide when to buy, sell and hold stocks. The use of artificial neural networks with the technical indicators conquered the world of stock trading prediction. These are now able to predict the market trend.
In this project, a new decision prediction system which involves the use of Computational efficient functional link artificial neural network learned by back propagation algorithm is studied to understand the behavior of stock trading signal of equity stocks. This strategy is then compared with the Simple Moving Average strategy.

Keywords: Trading Strategies, Technical indicators, Computational Efficient Functional link Artificial Neural Network, Back Propagation algorithm, Simple Moving Average Strategy

I. INTRODUCTION

A Stock Market plays an important role in every economy and it is the most critical aspect of every growing economy. It is a powerful system for every company in the economy for building capital and a best investment method for all classes of people. With the increasing rate of generation of financial data, capability of human to examine them manually became difficult. The crucial problem lies in the prediction of stocks as it depends on variety of market variables. There are a large number of environmental, political, financial and other related factors which can influence price variations on global scale. The political rule of a nation can influence the movement of stock prices directly. However the impact is mainly influenced and occurred due to only those companies which are directly or indirectly related to the concerned variable in one or other way. Due to these challenges, traders have to invent and establish different techniques to predict the stock market accurately and correctly.

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