A TFD Approach to Stock Price Prediction

被引：0

作者：

Chanduka, Bhabesh ^{[1
]}

Bhat, Swati S. ^{[1
]}

Rajput, Neha ^{[1
]}

Mohan, Biju R. ^{[1
]}

机构：

[1] Natl Inst Technol Karnataka, Dept Informat Technol, Surathkal 575025, India

来源：

INTELLIGENT COMPUTING AND COMMUNICATION, ICICC 2019 | 2020年 / 1034卷

关键词：

Stock price prediction; Time series; Financial ratios; Deep learning;

D O I：

10.1007/978-981-15-1084-7_61

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Accurate stock price predictions can help investors take correct decisions about the selling/purchase of stocks. With improvements in data analysis and deep learning algorithms, a variety of approaches has been tried for predicting stock prices. In this paper, we deal with the prediction of stock prices for automobile companies using a novel TFD-Time Series, Financial Ratios, and Deep Learning approach. We then study the results over multiple activation functions for multiple companies and reinforce the viability of the proposed algorithm.

引用

页码：635 / 644

页数：10

共 18 条

[1] Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction [J].

Adebiyi, Ayodele Ariyo ;

Adewumi, Aderemi Oluyinka ;

Ayo, Charles Korede .

JOURNAL OF APPLIED MATHEMATICS, 2014,

[2]

Agarap A F., 2018, DEEP LEARNING USING, DOI DOI 10.48550/ARXIV.1803.08375

[3]

[Anonymous], 2010, JMLR WORKSHOP C P

[4]

[Anonymous], 2016, ARXIV160500003V1

[5] A neural network with a case based dynamic window for stock trading prediction [J].

Chang, Pei-Chann ;

Liu, Chen-Hao ;

Lin, Jun-Lin ;

Fan, Chin-Yuan ;

Ng, Celeste S. P. .

EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (03) :6889-6898

[6]

Dash Rajashree, 2016, Journal of Finance and Data Science, V2, P42, DOI DOI 10.1016/J.JFDS.2016.03.002

[7] Applying Artificial Neural Networks to prediction of stock price and improvement of the directional prediction index - Case study of PETR4, Petrobras, Brazil [J].

de Oliveira, Fagner A. ;

Nobre, Cristiane N. ;

Zarate, Luis E. .

EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (18) :7596-7606

[8]

Ferreira TAE, 2005, GECCO 2005: Genetic and Evolutionary Computation Conference, Vols 1 and 2, P2221

[9] Kernel principal component analysis and support vector machines for stock price prediction [J].

Ince, Huseyin ;

Trafalis, Theodore B. .

IIE TRANSACTIONS, 2007, 39 (06) :629-637

[10]

Kingma DP, 2014, ADV NEUR IN, V27

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