Empirical Asset Pricing Models
Autor Jau-Lian Jengen Limba Engleză Paperback – 5 ian 2019
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Specificații
ISBN-13: 9783030089320
ISBN-10: 3030089320
Pagini: 284
Ilustrații: XVI, 268 p. 1 illus.
Dimensiuni: 148 x 210 x 16 mm
Greutate: 0.37 kg
Ediția:Softcover reprint of the original 1st edition 2018
Editura: Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3030089320
Pagini: 284
Ilustrații: XVI, 268 p. 1 illus.
Dimensiuni: 148 x 210 x 16 mm
Greutate: 0.37 kg
Ediția:Softcover reprint of the original 1st edition 2018
Editura: Springer
Locul publicării:Cham, Switzerland
Cuprins
Part I Asset Pricing Models: Discussions and Statistical Inferences.- 1. Asset Pricing Models: Specification, Data and Theoretical Foundation.- 2. Statistical Inferences with Specification Tests.- 3. Statistical Inferences with Model Selection Criteria.- Part II The Alternative Methodology. - 4. Finding Essential Variables in Empirical Asset Pricing Models.- 5. Hypothesis Testing with Model Search.
Notă biografică
Jau-Lian Jeng is Professor of Finance at Azusa Pacific University, USA.
Textul de pe ultima copertă
This book analyzes the verification of empirical asset pricing models when returns of securities are projected onto a set of presumed (or observed) factors. Particular emphasis is placed on the verification of essential factors and features for asset returns through model search approaches, in which non-diversifiability and statistical inferences are considered. The discussion reemphasizes the necessity of maintaining a dichotomy between the nondiversifiable pricing kernels and the individual components of stock returns when empirical asset pricing models are of interest. In particular, the model search approach (with this dichotomy emphasized) for empirical model selection of asset pricing is applied to discover the pricing kernels of asset returns.
Caracteristici
Positions forecastability as one of several statistical criteria for verifying model specification Discusses cross-sectional properties of asset pricing models Details model selection criteria and sequential model search methods