GSPTSE Directional Forecasting via U.S. Market Signals and Technical Indicator

DOI

10.2991/978-2-38476-585-0_30How to use a DOI?

Keywords

Machine Learning; Cross-Market Forecasting; MACD-HVIX

Abstract

With the deepening of economic globalization and the international flow of financial capital and assets, the stock markets of different countries tend to be interconnected, and there will be correlations and co-movement among the stock markets globally or regionally. This study aims to predict the daily directional movement, whether upward movement or downward movement, of the Canadian major index S&P / TSX Composite Index (GSPTSE) by using the major stock market indices of the United States and technical indicators. The study used six major US market indices, the volatility index (VIX), the Relative Strength Index (RSI), Moving Average Convergence and Divergence (MACD), and MACD based on historical volatility (MACD-HVIX), and lagging returns for prediction. MACD-HVIX is an indicator based on dynamic volatility adjustment from MACD. Linear model Logistic Regression, and two nonlinear models, Random Forest and eXtreme Gradient Boosting (XGBoost) were applied. The research results showed that nonlinear models performed better than the linear model, and random forest is better than XGBoost. Moreover, the study found that the effect of XGBoost was much better than the other two models when using the MACD-HVIX indicator.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Beibo Jiang
PY  - 2026
DA  - 2026/06/18
TI  - GSPTSE Directional Forecasting via U.S. Market Signals and Technical Indicator
BT  - Proceedings of the 2025 International Conference on Hybrid Commerce, Human Capital, and Economic Dynamics (ICHCH 2025)
PB  - Atlantis Press
SP  - 254
EP  - 261
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-2-38476-585-0_30
DO  - 10.2991/978-2-38476-585-0_30
ID  - Jiang2026
ER  -