Conditional Moments in Asset Pricing
Contribuinte(s) |
Svenska handelshögskolan, institutionen för finansiell ekonomi och ekonomisk statistik, finansiell ekonomi Swedish School of Economics and Business Administration, Department of Finance and Statistics, Finance |
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Data(s) |
27/05/2004
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Resumo |
A better understanding of stock price changes is important in guiding many economic activities. Since prices often do not change without good reasons, searching for related explanatory variables has involved many enthusiasts. This book seeks answers from prices per se by relating price changes to their conditional moments. This is based on the belief that prices are the products of a complex psychological and economic process and their conditional moments derive ultimately from these psychological and economic shocks. Utilizing information about conditional moments hence makes it an attractive alternative to using other selective financial variables in explaining price changes. The first paper examines the relation between the conditional mean and the conditional variance using information about moments in three types of conditional distributions; it finds that the significance of the estimated mean and variance ratio can be affected by the assumed distributions and the time variations in skewness. The second paper decomposes the conditional industry volatility into a concurrent market component and an industry specific component; it finds that market volatility is on average responsible for a rather small share of total industry volatility — 6 to 9 percent in UK and 2 to 3 percent in Germany. The third paper looks at the heteroskedasticity in stock returns through an ARCH process supplemented with a set of conditioning information variables; it finds that the heteroskedasticity in stock returns allows for several forms of heteroskedasticity that include deterministic changes in variances due to seasonal factors, random adjustments in variances due to market and macro factors, and ARCH processes with past information. The fourth paper examines the role of higher moments — especially skewness and kurtosis — in determining the expected returns; it finds that total skewness and total kurtosis are more relevant non-beta risk measures and that they are costly to be diversified due either to the possible eliminations of their desirable parts or to the unsustainability of diversification strategies based on them. |
Formato |
1837 bytes 1243811 bytes text/plain application/pdf |
Identificador |
http://hdl.handle.net/10227/100 URN:ISBN:951-555-832-8 951-555-832-8 |
Idioma(s) |
en |
Publicador |
Svenska handelshögskolan Swedish School of Economics and Business Administration |
Relação |
Economics and Society 128 |
Direitos |
Publikationen är skyddad av upphovsrätten. Den får läsas och skrivas ut för personligt bruk. Användning i kommersiellt syfte är förbjuden. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited. Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty. |
Palavras-Chave | #conditional moments #mean and variance ratio #skewed student's t-distribution #variance decomposition #industry volatility #market volatility #arch effects #heteroskedasticity #volume #total skewness #total kurtosis #higher moments #Finance |
Tipo |
Doctoral thesis Väitöskirja Doktorsavhandling Text |