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Finanse, Rynki Finansowe, Ubezpieczenia

Previously: Zeszyty Naukowe Uniwersytetu Szczecińskiego. Finanse, Rynki Finansowe, Ubezpieczenia

2/2017 (86)
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  1. 10.18778/2391-6478.4.44.06 (2024)
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Ryzyko rynkowe inwestycji w akcje na GPW w Warszawie w latach 2009 - 2015. Analizy branżowe.


(MARKET RISK OF INVESTMENTS ON WARSAW STOCK EXCHANGE 2009-2015. TRADE SECTORS ANALYSIS)
DOI: 10.18276/frfu.2017.86-03
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Abstract

Purpose - The paper considers market risk of investments on stock exchange distinguishing different trade sectors. We have analyzed branch indexes behaviour: 11 defined as indexes of income and 28 defined as price indexes. The subjects of interest were also collinearity of rates of return and distinguishing economy branches possibly preferable for investors. Design/Methodology/approach - The risk of investments is measured on the base of weekly data on rates of return, classical volatility measures, quantile measures: VaR (Value-at-Risk) and CVaR (Conditional Value-at-Risk).We compare investment risk for different economy sectors and examine the properties of the covariance matrix of rates of return, presenting dynamics of the condition index. Principal component analysis (PCA) was conducted to determine the number of orthogonal components describing the total market risk in at least 75%. The work is accomplished by the results of portfolio analysis based on historical simulation for different optimization criteria, including minimization of risk and maximization of utility. Findings – Analyzing the dynamics of covariance matrix condition index it was found that strength of relationships among rates of return is greater in the periods when all indexes decline comparing with the periods of growth. Our choice of “optimal” branches is the following: chemical, pharmaceutical and building materials industries as well as power engineering, informatics, hotel and restaurant services. Originality/value – The empirical research was conducted in which apart from classical approach to risk analysis and portfolio optimization we propose to measure of strength of stock market collinearity and its dynamics applying covariance matrix of branch indexes rates of return condition index and PCA.
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