Parallel Implementation of Moving Averages and Stock Market Prediction
نویسنده
چکیده
In recent years, graphics processing units have made parallel processing affordable with the price of personal desktop computers. This report investigates the computational aspects of calculating simple moving average and exponential moving average operations, two of the most popular financial indicators. In this report, we also investigate the usage of GPU to run artificial neural network as a mean of predicting stock market pricing. Feedforward and Backpropagation artificial neural network was used for this study. Financial data including major stock indices, volumes, pricing, and moving average of stocks were used as input. The future stock prices can be predicted as the output. The speedup factor by adopting GPU and CPU together over traditional CPU alone implementation was not significant. The computation of compute moving averages on GPU was also discussed.
منابع مشابه
Short-term Prediction of Tehran Stock Exchange Price Index (TEPIX): Using Artificial Neural Network (ANN)
The main objective of this study is to find out whether an Artificial Neural Network (ANN) will be useful to predict stock market price, which is highly non-linear and uncertain. Specifically, this study will focus on forecasting TSE Price Index (TEPIX) as the most significant index of Iran Stock Market. Many data have been used as inputs to the network. These data are observations of 2000 day...
متن کاملProfitability of Iranian Stock Market Based on Technical Analysis Trading Rules
In this study, we focused on Tehran stock exchange market analysis based on applying moving average rules. The Tehran stock exchange in the Middle East has evolved into an exciting and growing marketplace where individual and institutional investor trade securities of over 420 companies. In an attempt to examine the ability to earn excess return by exploiting moving average rules, the average a...
متن کاملStock Market Modeling Using Artificial Neural Network and Comparison with Classical Linear Models
Stock market plays an important role in the world economy. Stock market customers are interested in predicting the stock market general index price, since their income depends on this financial factor; Therefore, a reliable forecast in stock market can be extremely profitable for stockholders. Stock market prediction for financial markets has been one of the main challenges in forecasting finan...
متن کاملDesigning a Bankruptcy Prediction Model Based on Account, Market and Macroeconomic Variables (Case Study: Cyprus Stock Exchange)
The development of the Cyprus Stock Exchange together with the increasing trend of investors’ presence in financing activities has led to the importance of this market. In such circumstances, the first step towards a sustainable development of the Exchange is to support the investors. Risk of bankruptcy for the investee is a major challenge that an inexperienced stock investor encounters. In th...
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 کامل