The paper presents an idea of using an MLP neural network for determining the optimal buy and sell time on a stock exchange. The inputs in the training set consist of past stock prices and a number of technical indicators. The buy and sell moments on the training data that will become the output to the neural network can be determined either automatically or manually by a user on past data. We ...

A very important research topic is describing the way in which different asset price movements are correlated. Modern portfolio theory methods are based on observed correlations between returns at daily or larger time scales. One expects that coarse scale correlations originate from intraday movements that are strongly correlated. This implies the important question of how to obtain better esti...

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price will maximize investor’s gains. This paper proposes a machine learning model to predict stock market price. The proposed algorithm integrates Particle swarm optimization (PSO) and least squ...

In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators...

This paper aims at testing the influence of Subprime Crisis on Chinese stock market returns. By means of newly proposed time series spatial analysis methodology, we investigate the dominance behavior of daily returns on both Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index between before and after the crisis. Little spatial dominance could be found, even consi...

The purpose of this study is to compare the impacts of momentum on stock returns of companies listed in Tehran Stock Exchange in different market conditions. For this purpose, the sample size is 120 months from 2008 to 2017. The research hypotheses are estimated using multivariate linear regression using time series method. Based on the results of the hypotheses test, the momentum in each of th...

in this research, role of accruals in elaboration of quality of earning of the companies accepted in mumbai stock exchange has been studied and relationship between quality of earning through accruals and its constituents and abnormal stock return has been studied. the studied sample includes 35 companies in group a of mumbai stock exchange in 2009-2013.fordata analysisandhypothesistesting mult...

Previously security market research had been focused mainly on developed economies with no attention paid to the security markets of developing countries of South East Asia. In an attempt to fill this gap in the literature, this paper conducts an empirical investigation of the random walk of security prices in Pakistani stock markets. The Augmented Dickey fuller test, Ljung Box Q test, Variance...