Predicting Stock Market N-Days Ahead Using SVM Optimized by Selective Thresholds-Reference-Cited by-同舟云学术

Predicting Stock Market N-Days Ahead Using SVM Optimized by Selective Thresholds

Published:2020-02-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2020 12th International Conference on Machine Learning and Computing
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Author:

Jiang Jason¹,Liu Jianguo¹

Affiliation:

1. Department of Mathematics, University of North Texas, Denton, TX, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3383972.3384010

Reference10 articles.

1. Achelis S. B. "Technical Analysis from A to Z" New York: McGraw Hill 2001. Achelis S. B. "Technical Analysis from A to Z" New York: McGraw Hill 2001.

2. Twitter mood predicts the stock market

3. Huang C. F. âĂIJA hybrid stock selection model using genetic algorithms and support vector regressionâĂİ Applied Soft Computing 12(2) (2012): 807--818. Huang C. F. âĂIJA hybrid stock selection model using genetic algorithms and support vector regressionâĂİ Applied Soft Computing 12(2) (2012): 807--818.

4. Huang Wei Yoshiteru Nakamori and Shou-Yang Wang "Forecasting stock market movement direction with support vector machine" Computers & operations research 32.10 (2005): 2513--2522. Huang Wei Yoshiteru Nakamori and Shou-Yang Wang "Forecasting stock market movement direction with support vector machine" Computers & operations research 32.10 (2005): 2513--2522.

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