International Journal of Frontiers in Engineering Technology, 2021, 3(10); doi: 10.25236/IJFET.2021.031011.
Yuzhe Fang
School of Economics, Shanghai University, Shanghai, China
The four core financial technologies of Artificial Intelligence (AI), Blockchain, Cloud computing, and Big Data have laid a solid foundation for the financial industry to move towards large-scale "quantitative" and "automated" scenario applications. Nowadays, quantitative trading has been an important research direction in FinTech. This paper, based on the Deep Neural Network in machine learning, input data of opening price, closing price, high price, low price, volume, yield, first-order difference of yield, second-order difference of yield and MACD to predict the rise and fall of CSI 300 index on the next day.
Fintech, Quantitative Investment, Machine Learning, Deep Neural Network
Yuzhe Fang. A Deep Neural Network Based Quantitative Strategy for the CSI 300 Index. International Journal of Frontiers in Engineering Technology (2021), Vol. 3, Issue 10: 84-92. https://doi.org/10.25236/IJFET.2021.031011.
[1] Dixon M, Klabjan D, Bang J H. Classification-based Financial Markets Prediction using Deep Neural Networks. Social Science Electronic Publishing, 2016
[2] Dixon M, Klabjan D, Jin H B. Implementing deep neural networks for financial market prediction on the Intel Xeon Phi// The Workshop on High PERFORMANCE Computational Finance. ACM, 2015:1-6
[3] Dunis C L, Nathani A. Quantitative trading of gold and silver using nonlinear models. Neural Network World, 2007, 17(2):93-111
[4] Shambora W E, Rossiter R. Are there exploitable inefficiencies in the futures market for oil? Energy Economics, 2007, 29(1):18-27
[5] Xiong R, Nichols E P, Shen Y. Deep Learning Stock Volatilities with Google Domestic Trends. Computer Science, 2008, 10(2):1:7
[6] Sayyed Abdolmajid Jalaee, Mehrdad Lashkary, Amin GhasemiNejad The Phillips curve in Iran: econometric versus artificial neural networks [J] Heliyon, 2019, 5(8)
[7] Rashmi Malhotra, D.K Malhotra Evaluating consumer loans using neural networks [J] Omega, 2003, 31(2)
[8] Haiyan Mo, Jun Wang, Hongli Niu Exponent back propagation neural network forecasting for financial cross-correlation relationship[J] Expert Systems With Applications, 2016, 53
[9] Anonymous DATAMONITOR: Cloudy forecast for Salesforce.com's on-demand service initiative; Will social networking drive customer service in the future?[J] M2 Presswire, 2009
[10] Wiz Maps is developing unique forecasting models and mobile data mapping technology that fixes the huge disconnect and risk between a property and the surrounding environment, which helps real estate professionals and businesses[J] M2 Presswire, 2016