Predicting trends in future foreign exchange market prices
A Neural Network Model for Predicting Stock Market Prices
The Foreign Exchange Market Intervention and Exchange Rate Volatility
The Price Discovery and Efficiency of Indian Commodity Future Market
Can Commodity Futures Prices Forecast Future Spot Prices?
Indian Foreign Exchange Market
Exchange Rate Changes on Prices and Volume of Trade Flows in India
Volatility and Correlation of Foreign Exchange Market
Understanding the Foreign Exchange Markets
The Microfinance Market of Cameroon. Trends and future development
Can Market Volume Help In Predicting Share Market Volatility?
Foreign Exchange and Banking and Its Application in Ethiopia
Emerging Trends in Financial Markets Integration
The Foreign Exchange Market and Its Features
Companion to the Foreign Exchange Market
Stock exchanges are considered major players in the financial sector of many countries. In such exchanges, it is Stockbrokers who execute stock trade deals and advise clients on where to invest. Most of these Stockbrokers use technical, fundamental or time series analysis in trying to predict future stock prices, so as to advise clients on appropriate investments. However, these strategies do not usually guarantee good returns because they guide on trends and not the most likely trade price of a future date. It is therefore necessary to explore improved methods of prediction. The research uses Artificial Neural Network (ANN) that is feedforward multi-layer perceptron (MLP) with error backpropagation to develop a model ANN of configuration 5:21:21:1 using 80% data for training in 130,000 cycles. The research then develops a prototype and tests it using 2008-2012 data from various stock markets, such as the Nairobi Securities Exchange (NSE) and New York Stock Exchange (NYSE). Results showed that the model predicted prices with MAPE of 0.71% to 2.77%. Validation done using Neuroph & Encog showed close RMSE. The model can therefore be used in any typical stock market predict.