Predicting the direction of stock market prices using tree-based classifiers
Suryoday Basak,
Saibal Kar (),
Snehanshu Saha,
Luckyson Khaidem and
Sudeepa Roy Dey
The North American Journal of Economics and Finance, 2019, vol. 47, issue C, 552-567
Abstract:
Predicting returns in the stock market is usually posed as a forecasting problem where prices are predicted. Intrinsic volatility in the stock market across the globe makes the task of prediction challenging. Consequently, forecasting and diffusion modeling undermines a diverse range of problems encountered in predicting trends in the stock market. Minimizing forecasting error would minimize investment risk. In the current work, we pose the problem as a direction-predicting exercise signifying gains and losses. We develop an experimental framework for the classification problem which predicts whether stock prices will increase or decrease with respect to the price prevailing n days earlier. Two algorithms, random forests, and gradient boosted decisio‘n trees (using XGBoost) facilitate this connection by using ensembles of decision trees. We test our approach and report the accuracies for a variety of companies as improvement over existing predictions. A novelty of the current work is about the selection of technical indicators and their use as features, with high accuracy for medium to long-run prediction of stock price direction.
Keywords: Stock price movement; Xgboost; Random forests; Machine classification (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (53)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S106294081730400X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecofin:v:47:y:2019:i:c:p:552-567
DOI: 10.1016/j.najef.2018.06.013
Access Statistics for this article
The North American Journal of Economics and Finance is currently edited by Hamid Beladi
More articles in The North American Journal of Economics and Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().