SHIPPING WORLDWIDE

Fat-Tailed and Skewed Asset Return Distributions: Implications for Risk Management, Portfolio Selection, and Option Pricing - Hardcover

Fat-Tailed and Skewed Asset Return Distributions: Implications for Risk Management, Portfolio Selection, and Option Pricing - Hardcover

9780471718864
Vendor
Books by splitShops
Regular price
$113.40
Sale price
$113.40
Unit price
per 
All duties and taxes calculated at checkout.

by Svetlozar T. Rachev (Author), Christian Menn (Author), Frank J. Fabozzi (Author)

While mainstream financial theories and applications assume that asset returns are normally distributed, overwhelming empirical evidence shows otherwise. Yet many professionals don't appreciate the highly statistical models that take this empirical evidence into consideration. Fat-Tailed and Skewed Asset Return Distributions examines this dilemma and offers readers a less technical look at how portfolio selection, risk management, and option pricing modeling should and can be undertaken when the assumption of a non-normal distribution for asset returns is violated. Topics covered in this comprehensive book include an extensive discussion of probability distributions, estimating probability distributions, portfolio selection, alternative risk measures, and much more. Fat-Tailed and Skewed Asset Return Distributions provides a bridge between the highly technical theory of statistical distributional analysis, stochastic processes, and econometrics of financial returns and real-world risk management and investments.

Back Jacket

Fat-Tailed and Skewed Asset Return Distributions

While mainstream financial theories and applications assume that asset returns are normally distributed, the overwhelming empirical evidence shows otherwise. Yet many professionals fail to appreciate the highly statistical models that take this empirical evidence into consideration.

Svetlozar Rachev, Christian Menn, and Frank Fabozzi understand this dilemma, and in Fat-Tailed and Skewed Asset Return Distributions, they offer you a less technical look at how portfolio selection, risk management, and option pricing modeling should and can be undertaken when the assumption of a non-normal distribution for asset returns is violated.

Topics covered in this comprehensive book include:

  • An extensive discussion of probability distributions used in finance
  • Estimating probability distributions
  • The basics of stochastic processes
  • Portfolio selection and alternative risk measures
  • Market, credit, and operational risk measurement
  • Black-Scholes option pricing model and its extensions when the model's assumptions are modified to meet the empirical distributional evidence and tests
  • And much more

Fat-Tailed and Skewed Asset Return Distributions provides a bridge between the highly technical theory of statistical distributional analysis, stochastic processes, and econometrics of financial returns and real-world risk management and investments.

Author Biography

SVETLOZAR T. RACHEV, PhD, DR. SCI, is currently Chair-Professor at the University of Karlsruhe in the School of Economics and Business Engineering and Professor Emeritus at the University of California. He is also the founder of Bravo Risk Management Group and Chief Scientist of FinAnalytica.

CHRISTIAN MENN, DR. RER. POL., is Hochschulassistent at the Chair of Statistics, Econometrics and Mathematical Finance at the University of Karlsruhe. Currently, he is a Visiting Scientist at the School of Operations Research and Industrial Engineering at Cornell University as a postdoctoral fellow.

FRANK J. FABOZZI, PhD, CFA, CPA, is the Frederick Frank Adjunct Professor of Finance at Yale University's School of Management. He is also a Fellow of the International Center for Finance at Yale University. Prior to joining the Yale faculty, Fabozzi was a visiting professor of finance in the Sloan School at MIT. Fabozzi has authored and edited many acclaimed books in finance and is also the Editor of the Journal of Portfolio Management.

Number of Pages: 384
Dimensions: 1.11 x 9.51 x 6.44 IN
Illustrated: Yes
Publication Date: July 01, 2005