Stock and Futures Market Prediction Using Deep Learning Approach

Min-Hsuan Fan, Jing-Long Huang and Mu-Yen Chen

A chapter in Investment Strategies - New Advances and Challenges from IntechOpen

Abstract: In recent years, numerous studies have been devoted to predict the price fluctuations of financial markets. Taiwan 50 Exchange Traded Funds (ETF) is one of the important indicators to measure the volatility of the component stocks of the Taiwan 50 Index. With the development of the financial market, the trading volume of Taiwan Stock Index Futures is also increasing. The three markets play the important roles of economic development in the Taiwan. This study predicts the trend of Taiwan 50 ETF and Taiwan index futures applying machine learning and deep learning approaches which have excellent data exploration capabilities. This study applies the support vector regression (SVR), artificial neural networks (ANN), recurrent neural network (RNN), and long short-term memory network (LSTM) to predict the trend of the Taiwan stock market. This study uses various financial and technical factors as inputs, and extract variables from the factors affecting Taiwan's economy to build models, and compares the benefits between models to explore future market.

Keywords: deep learning; machine learning; stock market; foreign exchange market; technical indices (search for similar items in EconPapers)
JEL-codes: M21 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:311385

DOI: 10.5772/intechopen.114116

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