Theory and Econometrics of Financial Asset Pricing / / Kian Guan Lim.

• Superior document: Title is part of eBook package: De Gruyter DG Plus DeG Package 2022 Part 1
• VerfasserIn: Lim, Kian Guan,
• Place / Publishing House: Berlin ;, Boston : : De Gruyter, , [2022]; ©2022
• Year of Publication: 2022
• Language: English
• Physical Description: 1 online resource (XIV, 388 p.)
• Other title: Frontmatter --; Preface --; Contents --; 1 Probability Distributions --; 2 Simple Linear Regression --; 3 Capital Asset Pricing Model --; 4 Event Studies --; 5 Time Series Modeling --; 6 Multiple Linear Regression --; 7 Multi-Factor Asset Pricing --; 8 Euler Condition for Asset Pricing --; 9 Maximum Likelihood Methods --; 10 Unit Roots and Cointegration --; 11 Bond Prices and Interest Rate Models --; 12 Option Pricing and Implied Moments --; List of Figures --; List of Tables --; About the Author --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9783110673951; 9783110766820; 9783110992823; 9783110993899; 9783110994810; 9783110992922
• DOI: 10.1515/9783110673951
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Kian Guan Lim.

This book will provide a firm foundation in the understanding of financial economics applied to asset pricing. It carries the real world perspective of how the market works, including behavioral biases, and also wraps that understanding in the context of a rigorous economics framework of investors’ risk preferences, underlying price dynamics, rational choice in the large, and market equilibrium other than inexplicable irrational bubbles. It concentrates on analyses of stock, credit, and option pricing. Existing highly cited finance models in pricing of these assets are covered in detail, and theory is accompanied by rigorous applications of econometrics. Econometrics contain elucidations of both the statistical theory as well as the practice of data analyses. Linear regression methods and some nonlinear methods are also covered. The contribution of this book, and at the same time, its novelty, is in employing materials in probability theory, economics optimization, econometrics, and data analyses together to provide a rigorous and sharp intellect for investment and financial decision-making. Mistakes are often made with far too often sweeping pragmatism without deeply knowing the underpinnings of how the market economics works. This book is written at a level that is both academically rigorous for university courses in investment, derivatives, risk management, as well as not too mathematically deep so that finance and banking graduate professionals can have a real journey into the frontier financial economics thinking and rigorous data analytical findings.