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Non-transformed principal component technique on weekly construction stock market price

Andu, Yusrina and Lee, Muhammad Hisyam Lee and Algamal, Zakariya Yahya (2019) Non-transformed principal component technique on weekly construction stock market price. MATEMATIKA, 35 (Aug). pp. 139-147. ISSN 0127-9602


Official URL: https://dx.doi.org/10.11113/matematika.v35.n2.1112


The fast-growing urbanization has contributed to the construction sector be- coming one of the major sectors traded in the world stock market. In general, non- stationarity is highly related to most of the stock market price pattern. Even though stationarity transformation is a common approach, yet this may prompt to originality loss of the data. Hence, the non-transformation technique using a generalized dynamic principal component (GDPC) were considered for this study. Comparison of GDPC was performed with two transformed principal component techniques. This is pertinent as to observe a larger perspective of both techniques. Thus, the latest weekly two-years observations of nine constructions stock market price from seven different countries were applied. The data was tested for stationarity before performing the analysis. As a re- sult, the mean squared error in the non-transformed technique shows eight lowest values. Similarly, eight construction stock market prices had the highest percentage of explained variance. In conclusion, a non-transformed technique can also present a better result outcome without the stationarity transformation.

Item Type:Article
Uncontrolled Keywords:Construction stock market price, nonstationary, non-transformed, stationar- ity test, time series data
Subjects:Q Science > QA Mathematics
ID Code:84878
Deposited By: Fazli Masari
Deposited On:29 Feb 2020 12:39
Last Modified:29 Feb 2020 12:39

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