Author: G. Elliott
Publisher: Elsevier
ISBN: 0444513957
Category : Business & Economics
Languages : en
Pages : 1071
Book Description
Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
Handbook of Economic Forecasting
Author: G. Elliott
Publisher: Elsevier
ISBN: 0444513957
Category : Business & Economics
Languages : en
Pages : 1071
Book Description
Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
Publisher: Elsevier
ISBN: 0444513957
Category : Business & Economics
Languages : en
Pages : 1071
Book Description
Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
Financial Modeling Under Non-Gaussian Distributions
Author: Eric Jondeau
Publisher: Springer Science & Business Media
ISBN: 1846286964
Category : Mathematics
Languages : en
Pages : 541
Book Description
This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.
Publisher: Springer Science & Business Media
ISBN: 1846286964
Category : Mathematics
Languages : en
Pages : 541
Book Description
This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.
Forecasting Volatility in the Financial Markets
Author: Stephen Satchell
Publisher: Elsevier
ISBN: 0080494978
Category : Business & Economics
Languages : en
Pages : 417
Book Description
'Forecasting Volatility in the Financial Markets' assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modelling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.The editors have brought together a set of contributors that give the reader a firm grounding in relevant theory and research and an insight into the cutting edge techniques applied in this field of the financial markets.This book is of particular relevance to anyone who wants to understand dynamic areas of the financial markets.* Traders will profit by learning to arbitrage opportunities and modify their strategies to account for volatility.* Investment managers will be able to enhance their asset allocation strategies with an improved understanding of likely risks and returns.* Risk managers will understand how to improve their measurement systems and forecasts, enhancing their risk management models and controls.* Derivative specialists will gain an in-depth understanding of volatility that they can use to improve their pricing models.* Students and academics will find the collection of papers an invaluable overview of this field.This book is of particular relevance to those wanting to understand the dynamic areas of volatility modeling and forecasting of the financial marketsProvides the latest research and techniques for Traders, Investment Managers, Risk Managers and Derivative Specialists wishing to manage their downside risk exposure Current research on the key forecasting methods to use in risk management, including two new chapters
Publisher: Elsevier
ISBN: 0080494978
Category : Business & Economics
Languages : en
Pages : 417
Book Description
'Forecasting Volatility in the Financial Markets' assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting edge modelling and forecasting techniques. It then uses a technical survey to explain the different ways to measure risk and define the different models of volatility and return.The editors have brought together a set of contributors that give the reader a firm grounding in relevant theory and research and an insight into the cutting edge techniques applied in this field of the financial markets.This book is of particular relevance to anyone who wants to understand dynamic areas of the financial markets.* Traders will profit by learning to arbitrage opportunities and modify their strategies to account for volatility.* Investment managers will be able to enhance their asset allocation strategies with an improved understanding of likely risks and returns.* Risk managers will understand how to improve their measurement systems and forecasts, enhancing their risk management models and controls.* Derivative specialists will gain an in-depth understanding of volatility that they can use to improve their pricing models.* Students and academics will find the collection of papers an invaluable overview of this field.This book is of particular relevance to those wanting to understand the dynamic areas of volatility modeling and forecasting of the financial marketsProvides the latest research and techniques for Traders, Investment Managers, Risk Managers and Derivative Specialists wishing to manage their downside risk exposure Current research on the key forecasting methods to use in risk management, including two new chapters
Essentials of Time Series for Financial Applications
Author: Massimo Guidolin
Publisher: Academic Press
ISBN: 0128134100
Category : Business & Economics
Languages : en
Pages : 435
Book Description
Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. - Provides practical, hands-on examples in time-series econometrics - Presents a more application-oriented, less technical book on financial econometrics - Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction - Features examples worked out in EViews (9 or higher)
Publisher: Academic Press
ISBN: 0128134100
Category : Business & Economics
Languages : en
Pages : 435
Book Description
Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. - Provides practical, hands-on examples in time-series econometrics - Presents a more application-oriented, less technical book on financial econometrics - Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction - Features examples worked out in EViews (9 or higher)
Empirical Dynamic Asset Pricing
Author: Kenneth J. Singleton
Publisher: Princeton University Press
ISBN: 1400829232
Category : Business & Economics
Languages : en
Pages : 497
Book Description
Written by one of the leading experts in the field, this book focuses on the interplay between model specification, data collection, and econometric testing of dynamic asset pricing models. The first several chapters provide an in-depth treatment of the econometric methods used in analyzing financial time-series models. The remainder explores the goodness-of-fit of preference-based and no-arbitrage models of equity returns and the term structure of interest rates; equity and fixed-income derivatives prices; and the prices of defaultable securities. Singleton addresses the restrictions on the joint distributions of asset returns and other economic variables implied by dynamic asset pricing models, as well as the interplay between model formulation and the choice of econometric estimation strategy. For each pricing problem, he provides a comprehensive overview of the empirical evidence on goodness-of-fit, with tables and graphs that facilitate critical assessment of the current state of the relevant literatures. As an added feature, Singleton includes throughout the book interesting tidbits of new research. These range from empirical results (not reported elsewhere, or updated from Singleton's previous papers) to new observations about model specification and new econometric methods for testing models. Clear and comprehensive, the book will appeal to researchers at financial institutions as well as advanced students of economics and finance, mathematics, and science.
Publisher: Princeton University Press
ISBN: 1400829232
Category : Business & Economics
Languages : en
Pages : 497
Book Description
Written by one of the leading experts in the field, this book focuses on the interplay between model specification, data collection, and econometric testing of dynamic asset pricing models. The first several chapters provide an in-depth treatment of the econometric methods used in analyzing financial time-series models. The remainder explores the goodness-of-fit of preference-based and no-arbitrage models of equity returns and the term structure of interest rates; equity and fixed-income derivatives prices; and the prices of defaultable securities. Singleton addresses the restrictions on the joint distributions of asset returns and other economic variables implied by dynamic asset pricing models, as well as the interplay between model formulation and the choice of econometric estimation strategy. For each pricing problem, he provides a comprehensive overview of the empirical evidence on goodness-of-fit, with tables and graphs that facilitate critical assessment of the current state of the relevant literatures. As an added feature, Singleton includes throughout the book interesting tidbits of new research. These range from empirical results (not reported elsewhere, or updated from Singleton's previous papers) to new observations about model specification and new econometric methods for testing models. Clear and comprehensive, the book will appeal to researchers at financial institutions as well as advanced students of economics and finance, mathematics, and science.
Financial, Macro and Micro Econometrics Using R
Author:
Publisher: North Holland
ISBN: 0128202505
Category : Mathematics
Languages : en
Pages : 350
Book Description
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.
Publisher: North Holland
ISBN: 0128202505
Category : Mathematics
Languages : en
Pages : 350
Book Description
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.
Applications of Characteristic Functions
Author: Eugene Lukacs
Publisher:
ISBN:
Category : Characteristic functions
Languages : en
Pages : 208
Book Description
Publisher:
ISBN:
Category : Characteristic functions
Languages : en
Pages : 208
Book Description
A Time Series Approach to Option Pricing
Author: Christophe Chorro
Publisher: Springer
ISBN: 3662450372
Category : Business & Economics
Languages : en
Pages : 202
Book Description
The current world financial scene indicates at an intertwined and interdependent relationship between financial market activity and economic health. This book explains how the economic messages delivered by the dynamic evolution of financial asset returns are strongly related to option prices. The Black Scholes framework is introduced and by underlining its shortcomings, an alternative approach is presented that has emerged over the past ten years of academic research, an approach that is much more grounded on a realistic statistical analysis of data rather than on ad hoc tractable continuous time option pricing models. The reader then learns what it takes to understand and implement these option pricing models based on time series analysis in a self-contained way. The discussion covers modeling choices available to the quantitative analyst, as well as the tools to decide upon a particular model based on the historical datasets of financial returns. The reader is then guided into numerical deduction of option prices from these models and illustrations with real examples are used to reflect the accuracy of the approach using datasets of options on equity indices.
Publisher: Springer
ISBN: 3662450372
Category : Business & Economics
Languages : en
Pages : 202
Book Description
The current world financial scene indicates at an intertwined and interdependent relationship between financial market activity and economic health. This book explains how the economic messages delivered by the dynamic evolution of financial asset returns are strongly related to option prices. The Black Scholes framework is introduced and by underlining its shortcomings, an alternative approach is presented that has emerged over the past ten years of academic research, an approach that is much more grounded on a realistic statistical analysis of data rather than on ad hoc tractable continuous time option pricing models. The reader then learns what it takes to understand and implement these option pricing models based on time series analysis in a self-contained way. The discussion covers modeling choices available to the quantitative analyst, as well as the tools to decide upon a particular model based on the historical datasets of financial returns. The reader is then guided into numerical deduction of option prices from these models and illustrations with real examples are used to reflect the accuracy of the approach using datasets of options on equity indices.
A Practical Guide to Forecasting Financial Market Volatility
Author: Ser-Huang Poon
Publisher: John Wiley & Sons
ISBN: 0470856157
Category : Business & Economics
Languages : en
Pages : 236
Book Description
Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
Publisher: John Wiley & Sons
ISBN: 0470856157
Category : Business & Economics
Languages : en
Pages : 236
Book Description
Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.
Fundamental Statistical Inference
Author: Marc S. Paolella
Publisher: John Wiley & Sons
ISBN: 1119417880
Category : Mathematics
Languages : en
Pages : 584
Book Description
A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided. The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution. Presented in three parts—Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics—Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.
Publisher: John Wiley & Sons
ISBN: 1119417880
Category : Mathematics
Languages : en
Pages : 584
Book Description
A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided. The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution. Presented in three parts—Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics—Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.