Application of Support Vector Machine Model to Forecast Nigerian Stock Exchange Market for Zenith Bank
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Abstract
Support Vector Machine (SVM) model is applied virtually in every sphere in life. The Nigerian stock exchange (NSE) is not an exception and therefore this study is aimed at applying the model to the NSE in the study. The challenge of stock forecasting is attractive since a small forecasting can enhance the profit significantly. However, the volatile nature of the stock market makes it difficult to apply linear models such as simple time-series or regression techniques. Consequently, support vector machine (SVM) has become a good alternative. It is a popular tool in time series forecasting for the capital investment industry. This machine learning technique which is based on a discriminative classifier algorithm, forecasts more accurately the financial data. The paper discussed the functions and problems of the NSE market. The study of the application of SVM model revealed that it is a good model to forecast the Nigerian stock exchange market effectively.
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