Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/188183 
Erscheinungsjahr: 
2015
Quellenangabe: 
[Journal:] Pakistan Journal of Commerce and Social Sciences (PJCSS) [ISSN:] 2309-8619 [Volume:] 9 [Issue:] 1 [Publisher:] Johar Education Society, Pakistan (JESPK) [Place:] Lahore [Year:] 2015 [Pages:] 69-95
Verlag: 
Johar Education Society, Pakistan (JESPK), Lahore
Zusammenfassung: 
The main focus of the current study was to investigate 33 major stock indices on a weekly basis to fill the void concerning fresh information in the context of co-movement of markets as a result of the Global Financial Crisis. Factor analysis was applied through two methods, principle component (PC) and maximum likelihood (ML), as both of these methods are widely accepted. The assumption of normality is not required in the PC method, whereas ML demands data normality. To check normality, Kolmogorov- Smirnov Test was applied. All the markets except a few Asian markets (e.g. Hong Kong, China, Japan and Philippine) have significant values which indicate the abnormality of data; therefore, principal component analysis was applied. Global stock markets were divided into three groups and affects of the crisis on their comovements were judged by applying rotated factor analysis. Results of the analysis revealed that American and Asian equity markets demonstrated a linear interaction. However, European markets were prone to the financial crisis of 2007. Findings of this study are of great value for investors, as they can develop their future investment plans to optimize the benefits of diversification. American, Asian, and European regional investors can spread their investment portfolios by adding new investment proportions of all regions. This study is conducted on global data taking the financial crisis of 2007 as the main event that could affect stock markets. This study is new in nature, as none of the previous researchers have conducted study in this domain.
Schlagwörter: 
portfolio diversification
factory analysis
stock prices
global financial crisis
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