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Empirical Techniques in Finance [electronic resource] / by Ramaprasad Bhar, Shigeyuki Hamori.

By: Contributor(s): Material type: TextTextSeries: Springer FinancePublisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005Edition: 1st ed. 2005Description: XII, 243 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540276425
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 332
LOC classification:
  • HG1-9999
Online resources:
Contents:
Basic Probability Theory and Markov Chains -- Estimation Techniques -- Non-Parametric Method of Estimation -- Unit Root, Cointegration and Related Issues -- VAR Modeling -- Time Varying Volatility Models -- State-Space Models (I) -- State-Space Models (II) -- Discrete Time Real Asset Valuation Model -- Discrete Time Model of Interest Rate -- Global Bubbles in Stock Markets and Linkages -- Forward FX Market and the Risk Premium -- Equity Risk Premia from Derivative Prices.
In: Springer Nature eBookSummary: This book offers the opportunity to study and experience advanced empi- cal techniques in finance and in general financial economics. It is not only suitable for students with an interest in the field, it is also highly rec- mended for academic researchers as well as the researchers in the industry. The book focuses on the contemporary empirical techniques used in the analysis of financial markets and how these are implemented using actual market data. With an emphasis on Implementation, this book helps foc- ing on strategies for rigorously combing finance theory and modeling technology to extend extant considerations in the literature. The main aim of this book is to equip the readers with an array of tools and techniques that will allow them to explore financial market problems with a fresh perspective. In this sense it is not another volume in eco- metrics. Of course, the traditional econometric methods are still valid and important; the contents of this book will bring in other related modeling topics that help more in-depth exploration of finance theory and putting it into practice. As seen in the derivatives analysis, modern finance theory requires a sophisticated understanding of stochastic processes. The actual data analyses also require new Statistical tools that can address the unique aspects of financial data. To meet these new demands, this book explains diverse modeling approaches with an emphasis on the application in the field of finance.
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Holdings
Item type Home library Collection Call number Status Date due Barcode Item holds
E-Book E-Book Biblioteca Digital Colección SPRINGER 332 (Browse shelf(Opens below)) Not For Loan
Total holds: 0

Basic Probability Theory and Markov Chains -- Estimation Techniques -- Non-Parametric Method of Estimation -- Unit Root, Cointegration and Related Issues -- VAR Modeling -- Time Varying Volatility Models -- State-Space Models (I) -- State-Space Models (II) -- Discrete Time Real Asset Valuation Model -- Discrete Time Model of Interest Rate -- Global Bubbles in Stock Markets and Linkages -- Forward FX Market and the Risk Premium -- Equity Risk Premia from Derivative Prices.

This book offers the opportunity to study and experience advanced empi- cal techniques in finance and in general financial economics. It is not only suitable for students with an interest in the field, it is also highly rec- mended for academic researchers as well as the researchers in the industry. The book focuses on the contemporary empirical techniques used in the analysis of financial markets and how these are implemented using actual market data. With an emphasis on Implementation, this book helps foc- ing on strategies for rigorously combing finance theory and modeling technology to extend extant considerations in the literature. The main aim of this book is to equip the readers with an array of tools and techniques that will allow them to explore financial market problems with a fresh perspective. In this sense it is not another volume in eco- metrics. Of course, the traditional econometric methods are still valid and important; the contents of this book will bring in other related modeling topics that help more in-depth exploration of finance theory and putting it into practice. As seen in the derivatives analysis, modern finance theory requires a sophisticated understanding of stochastic processes. The actual data analyses also require new Statistical tools that can address the unique aspects of financial data. To meet these new demands, this book explains diverse modeling approaches with an emphasis on the application in the field of finance.

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