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

• Main Authors: Andu, Yusrina, Lee, Muhammad Hisyam Lee, Algamal, Zakariya Yahya
• Format: Article
• Language: English
• Published: Penerbit UTM Press 2019
• Subjects: QA Mathematics
• Online Access: http://eprints.utm.my/id/eprint/84878/1/MuhammadHisyamLee2019_Non-transformedPrincipalComponentTechnique.pdf; http://eprints.utm.my/id/eprint/84878/; 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.