scholarly journals Stock Market Index Data and indicators for Day Trading as a Binary Classification problem

Data in Brief ◽  
2017 ◽  
Vol 10 ◽  
pp. 569-575 ◽  
Author(s):  
Renato Bruni
Keyword(s):  
Stock Market ◽  
Binary Classification ◽  
Classification Problem ◽  
Stock Market Index ◽  
Day Trading ◽  
Index Data ◽  
Market Index ◽  
Binary Classification Problem

Evaluation of Alternative Approaches in Classification Algorithms for Prediction of Stock Market Index

2021 ◽  
pp. 204-221
Author(s):  
Silvija Vlah Jerić
Keyword(s):  
Binary Classification ◽  
Technical Analysis ◽  
Classification Problem ◽  
Stock Index ◽  
Support Network ◽  
Stock Market Index ◽  
K Nearest Neighbors ◽  
Network Support ◽  
Market Index ◽  
Evaluation Metric

This chapter tackles the problem of automatic recognition of favorable days for intra-day trading. The problem is modeled as a binary classification problem, and several approaches are tested for solving it. Croatian stock index CROBEX data is used and 22 technical indicators are calculated as predictor variables. Performance of five classifiers is evaluated and compared by using Cohen's kappa as evaluation metric: artificial neural network, support network machine, random forest, k-nearest neighbors, and naïve Bayes classifier. The results give insight to effectiveness of technical analysis in predicting the day favorability for CROBEX index and suggest that technical analysis makes sense and might work for this case.

On the sensibility of the Pairs Trading strategy: the case of the FTS stock market index

2020 ◽  
Vol 38 (3) ◽  
Author(s):  
Ainhoa Fernández-Pérez ◽  
María de las Nieves López-García ◽  
José Pedro Ramos Requena
Keyword(s):  
Standard Deviation ◽  
Stock Market ◽  
Trading Strategy ◽  
Stock Market Index ◽  
Pairs Trading ◽  
Empirical Application ◽  
Statistical Arbitrage ◽  
Market Index ◽  
Standard Deviations ◽  
Using Data

In this paper we present a non-conventional statistical arbitrage technique based in varying the number of standard deviations used to carry the trading strategy. We will show how values of 1 and 1,2 in the standard deviation provide better results that the classic strategy of Gatev et al (2006). An empirical application is performance using data of the FST100 index during the period 2010 to June 2019.

Oil Price and Stock Market Index, the Case of GCC Countries

2012 ◽  
Author(s):  
Mazen Marwan Mardini ◽  
Talal Omar Fawzi Bayazeed
Keyword(s):  
Stock Market ◽  
Oil Price ◽  
Stock Market Index ◽  
Market Index ◽  
Gcc Countries
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