Co-Movements of Pacific-Basin Stock Markets: Portfolio Diversification Implications

2007 ◽  
Vol 8 (2) ◽  
pp. 11-34
Author(s):  
Ilhan Meric ◽  
Joe Kim ◽  
Lewis Coopersmith ◽  
Gulser Meric
Keyword(s):  
Principal Components ◽  
Stock Markets ◽  
Weak Form ◽  
Portfolio Diversification ◽  
Pacific Basin ◽  
Test Results ◽  
Considerable Time ◽  
Causality Test ◽  
The Pacific ◽  
Components Analysis

This paper studies the co-movements of and the linkages between twelve Pacific-Basin stock markets during the June 1995-May 2005 period. We use the principal components analysis (PCA) technique to group the stock markets into statistically significant principal components in terms of the similarities of their index return movements. The rolling correlation analysis results show that correlation between the Pacific-Basin stock markets has considerable time-varying volatility. The Granger causality test results indicate that the weekly index returns of most Pacific-Basin stock markets are weak-form efficient and that most Pacific-Basin stock markets have significant lead/lag linkages. The study investigates the portfolio diversification implications of the linkages between the Pacific-Basin stock markets.

scholarly journals Global Portfolio Diversification with Emerging Stock Markets

2016 ◽  
Vol 6 (1) ◽  
pp. 59-62 ◽  
Author(s):  
İlhan Meriç ◽  
Jie Ding ◽  
Gülser Meriç
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Stock Markets ◽  
Portfolio Diversification ◽  
Emerging Stock Markets ◽  
Low Correlation ◽  
Pca Method ◽  
Components Analysis ◽  
Global Investors ◽  
Developed Stock Markets

Because of their low correlation with each other and with developed stock markets, emerging stock markets are generally mentioned as attractive portfolio diversification prospects for global investors. In this paper, we use the Principal Components Analysis (PCA) method to study the global portfolio diversification opportunities for the investors of seven developed stock markets in twenty emerging stock markets with data for the January 1, 2003-January 1, 2014 period.

INVESTIGATION OF THE RELATIONSHIP BETWEEN TURKEY AND DEVELOPED STOCK MARKETS IN THE PANDEMIC PERIOD: ARDL BOUND TESTING APPROACH

2021 ◽  
Vol 8 (21) ◽  
pp. 36-44
Author(s):  
Anıl LÖGÜN ◽  
Rahman AYDIN
Keyword(s):  
Granger Causality ◽  
Stock Markets ◽  
Granger Causality Test ◽  
Portfolio Diversification ◽  
Test Results ◽  
Causality Test ◽  
International Portfolio Diversification ◽  
Developed Stock Markets ◽  
Bound Test

The integration of stock markets is an essential issue for international investors who aim to make short and long term investments. This paper examines Turkey and developed stock markets co-movements during the pandemic. International portfolio diversification advantages are investigated for Turkish investors who have a portfolio in developed markets. For this purpose, the long-term relationship between stock markets is analyzed using the Autoregressive Distributed Lag (ARDL) bound test. The study covers January 2019 and April 2021, and this period is divided into two separate periods, pre-pandemic and pandemic. The results of ARDL bounds tests have not found a cointegration relationship between stock markets in both the pre-pandemic period and the pandemic period. Granger causality test results show that NIKKEI 225 (Japan), DAX (Germany), FTSE 100 (United Kingdom) and CAC 40 (France) are the cause of BIST 100 (Turkey) in the pre-pandemic period. However, Granger causality test results show that there is no causality relationship during the pandemic period. Turkish stock market investors investing in developed stock markets will benefit from portfolio diversification in the long term.

scholarly journals Analysing portfolio diversification opportunities in selected stock markets of North and South America and their impact on the textile sector: An empirical case study

2021 ◽  
Vol 72 (04) ◽  
pp. 398-407
Author(s):  
RAMONA BIRAU ◽  
CRISTI SPULBAR ◽  
AJMAL HAMZA ◽  
EJAZ ABDULLAH ◽  
ELENA LOREDANA MINEA ◽  
...  
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Stock Markets ◽  
Financial Integration ◽  
Stock Exchange ◽  
Portfolio Diversification ◽  
Causality Test ◽  
International Portfolio Diversification ◽  
Integration Test ◽  
Textile Sector

This empirical study investigates the financial integration linkages among the sample stock markets of Canada, Mexico,United States (for both New York Stock Exchange, i.e. NYSE and NASDAQ), Panama, Brazil, Chile, Peru, Venezuela,Jamaica, Trinidad, and Tobago during the period from January 2001 to April 2019. This research study also examinesthe impact of selected stock market dynamics on the textile sector. International portfolio diversification has been animportant subject of research in financial fraternity since the emergence of Modern Portfolio Theory in 1952. This studyexamines the portfolio diversification opportunities in the 11 stock markets of Americas.International diversificationamong stock market indices has proven to be fruitful in the past. Certain tests have been used to determine opportunitiesfor diversification are correlation test, pairwise co-integration test, multiple co-integration test and granger causality test.The empirical results show that stock market indices share low correlation among other and they are not highlyco-integrated whereas results of Granger causality test exhibit an unidirectional relationship among few stock marketsin short run.

CYTOGENETIC STUDIES OF CHROMOSOME REPLICATION IN ZEA MAYS L.: I. Analysis of quantitative autoradiographic data using Principal Components Analysis

1973 ◽  
Vol 15 (3) ◽  
pp. 417-426 ◽  
Author(s):  
George R. Douglas ◽  
David B. Walden
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Euclidean Distance ◽  
Primary Root ◽  
Autoradiographic Study ◽  
Test Results ◽  
Additional Chromosome ◽  
The Mean ◽  
Components Analysis ◽  
Silver Grains

A quantitative, autoradiographic study of 3H-TdR uptake at 18 °C was undertaken in the nuclei of primary root meristems of a highly inbred stock of maize. Plots of the mean number of silver grains over nuclei vs. hours after removal from 3H-TdR (replication profiles) revealed fluctuation in DNA replication. Wilcoxon's signed-ranks test showed that some chromosome arms had replication profiles different from the profile of the nucleus. A Principal Components Analysis (PCA) was used to characterize empirically and further compare the replication of chromosome arms. The PCA results confirm the Wilcoxon's signed-ranks test results and also suggest unique replication behavior for some additional chromosome arms. To quantitatively compare the position of individuals in the scatter diagram of the first three factor axes from the PCA, the standardized Euclidean distance of each individual from the centroid was employed. Since some chromosome arms were found to be different from the others, at least limited autonomy of replication among chromosome arms is proposed.

scholarly journals RANCANG BANGUN SISTEM PENGENALAN WAJAH DENGAN METODE PRINCIPAL COMPONENT ANALYSIS

2016 ◽  
Vol 1 (2) ◽  
pp. 59-75
Author(s):  
Salamun Salamun ◽  
Firman Wazir
Keyword(s):  
Principal Component Analysis ◽  
Face Recognition ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Principal Component ◽  
Physiological Measures ◽  
Test Results ◽  
Analysis Method ◽  
The Face ◽  
Components Analysis

The face is one of the easiest physiological measures and is often used to distinguish individual identities from one another. This facial recognition process uses raw information from pixel images generated through a camera which is then represented in the Principal Components Analysis method. The Principal Components Analysis method works by calculating the average flatvector pixel of images that have been stored in a database, from the average flatvector will get the value of each image eigenface and then the nearest eigenface value of the image will be found and then the nearest eigenface value of the image will be found the image of the face you want to recognize. The test results showed an overall success rate of face recognition of 82.27% with face data of 130 images.

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