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result(s) for
"Rachev, S. T. (Svetlozar Todorov)"
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The basics of financial econometrics : tools, concepts, and asset management applications
2014
An accessible guide to the growing field of financial econometrics As finance and financial products have become more complex, financial econometrics has emerged as a fast-growing field and necessary foundation for anyone involved in quantitative finance. The techniques of financial econometrics facilitate the development and management of new financial instruments by providing models for pricing and risk assessment. In short, financial econometrics is an indispensable component to modern finance. The Basics of Financial Econometrics covers the commonly used techniques in the field without using unnecessary mathematical/statistical analysis. It focuses on foundational ideas and how they are applied. Topics covered include: regression models, factor analysis, volatility estimations, and time series techniques. * Covers the basics of financial econometrics—an important topic in quantitative finance * Contains several chapters on topics typically not covered even in basic books on econometrics such as model selection, model risk, and mitigating model risk Geared towards both practitioners and finance students who need to understand this dynamic discipline, but may not have advanced mathematical training, this book is a valuable resource on a topic of growing importance.
Financial models with Lévy processes and volatility clustering
by
Rachev, Svetlozar T
,
Kim, Young Shin
,
Bianchi, Michele L
in
BUSINESS & ECONOMICS
,
Capital assets pricing model
,
Finance
2011
An in-depth guide to understanding probability distributions and financial modeling for the purposes of investment management In Financial Models with Lévy Processes and Volatility Clustering, the expert author team provides a framework to model the behavior of stock returns in both a univariate and a multivariate setting, providing you with practical applications to option pricing and portfolio management. They also explain the reasons for working with non-normal distribution in financial modeling and the best methodologies for employing it. The book's framework includes the basics of probability distributions and explains the alpha-stable distribution and the tempered stable distribution. The authors also explore discrete time option pricing models, beginning with the classical normal model with volatility clustering to more recent models that consider both volatility clustering and heavy tails. Reviews the basics of probability distributions Analyzes a continuous time option pricing model (the so-called exponential Lévy model) Defines a discrete time model with volatility clustering and how to price options using Monte Carlo methods Studies two multivariate settings that are suitable to explain joint extreme events Financial Models with Lévy Processes and Volatility Clustering is a thorough guide to classical probability distribution methods and brand new methodologies for financial modeling.
Bayesian methods in Finance
by
Rachev, Svetlozar T
,
Fabozzi, Frank J
,
Bagasheva, Biliana S
in
Bayes-Statistik
,
Bayesian statistical decision theory
,
Business & Economics
2008
Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management—since these are the areas in finance where Bayesian methods have had the greatest penetration to date.
Advanced stochastic models, risk assessment, and portfolio optimization
by
Fabozzi, Frank J
,
Stoyanov, Stoyan V
,
Rachev, Svetlozar T
in
Business & Economics
,
Finance
,
Mathematical models
2008
This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework. Throughout these pages, the expert authors explain the fundamentals of probability metrics, outline new approaches to portfolio optimization, and discuss a variety of essential risk measures. Using numerous examples, they illustrate a range of applications to optimal portfolio choice and risk theory, as well as applications to the area of computational finance that may be useful to financial engineers.
The Basics of Financial Econometrics
2014
An accessible guide to the growing field of financial econometrics As finance and financial products have become more complex, financial econometrics has emerged as a fast-growing field and necessary foundation for anyone involved in quantitative finance. The techniques of financial econometrics facilitate the development and management of new financial instruments by providing models for pricing and risk assessment. In short, financial econometrics is an indispensable component to modern finance. Financial Econometric Basics covers the commonly used techniques in the field without using unne
Laplace-Weibull Mixtures for Modeling Price Changes
1993
B. Mandelbrot and E. Fama in the sixties, and W. Ziemba in the seventies, suggested stable laws for modeling stock returns and commodity prices. Geometric stable distributions, with Laplace distribution playing the role of a \"normal\" law, have been found to give better fit to such data. We study the \"stability\" properties of Laplace and a mixture of Laplace and Weibull and discuss the statistical inference for such mixture models. Application of the mixture distribution to modeling price changes in real estate prices in France is given.
Journal Article