Characterizing stock market data using time series analysis within industries

Authors

Gilbert Chua ⋅ PH National Institute of Physics, University of the Philippines Diliman
Gabriel Sison ⋅ PH National Institute of Physics, University of the Philippines Diliman
Giovanni Tapang ⋅ PH National Institute of Physics, University of the Philippines Diliman

Abstract

Using a new metric combining Pearson's r and Mutual Information, the study revealed trends within the stock market prices of certain industries within the Philippines. The stock prices of the companies within the Securities, Reinsurance, Transportation, Housewares, Renewable Energy, and Industrial Electronics industries were found to have a positive correlation (p < 0.05) within their respective industries. On the other hand, the stock prices of companies in the Hotels, Water Transportation, Building Materials, Oil/Gas Products, Water Utilities, Life Insurance, Non-Alcoholic Beverages, Semiconductors, and the Passenger Airlines industries were found to have a negative correlation (p < 0.05). These results can aid economists and stock traders in analyzing the state of the Philippine economy. Further studies could include the introduction of time delays to the time series analysis and the analysis of other real-world time series data.

Downloads

Issue

2016: Proceedings of the 34th Samahang Pisika ng Pilipinas Physics Conference

Physics at the front and center: Strengthening core values in physics research
18–21 August 2016, University of the Philippines Visayas, Iloilo City

SPP2016 Conference Organizers
SPP2016 Editorial Board
SPP2016 Partners and Sponsors

Article ID

SPP-2016-4B-03

Section

Complex Systems and Data Analytics

Published

2016-08-18

How to Cite

[1]

G Chua, G Sison, and G Tapang, Characterizing stock market data using time series analysis within industries, Proceedings of the Samahang Pisika ng Pilipinas 34, SPP-2016-4B-03 (2016). URL: https://proceedings.spp-online.org/article/view/SPP-2016-4B-03.