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| econometrics of financial markets: The Econometrics of Financial Markets John Y. Campbell, Andrew W. Lo, A. Craig MacKinlay, 2012-06-28 The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications. |
| econometrics of financial markets: The Econometrics of Financial Markets John Y. Campbell, Andrew W. Lo, A. Craig MacKinlay, 1997 The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory. Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications. |
| econometrics of financial markets: Financial Econometrics Oliver Linton, 2019-02-21 Presents an up-to-date treatment of the models and methodologies of financial econometrics by one of the world's leading financial econometricians. |
| econometrics of financial markets: The Econometrics of Financial Markets John Y. Campbell, Andrew Wen-Chuan Lo, Archie Craig MacKinlay, 2007 |
| econometrics of financial markets: Introductory Econometrics for Finance Chris Brooks, 2008-05-22 This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details. |
| econometrics of financial markets: Financial Econometrics Svetlozar T. Rachev, Stefan Mittnik, Frank J. Fabozzi, Sergio M. Focardi, Teo Jašić, 2007-03-22 A comprehensive guide to financial econometrics Financial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed. Svetlozar T. Rachev, PhD (Karlsruhe, Germany) is currently Chair-Professor at the University of Karlsruhe. Stefan Mittnik, PhD (Munich, Germany) is Professor of Financial Econometrics at the University of Munich. Frank J. Fabozzi, PhD, CFA, CFP (New Hope, PA) is an adjunct professor of Finance at Yale University’s School of Management. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm The Intertek Group. Teo Jasic, PhD, (Frankfurt, Germany) is a senior manager with a leading international management consultancy firm in Frankfurt. |
| econometrics of financial markets: Handbook of Financial Econometrics Yacine Ait-Sahalia, Lars Peter Hansen, 2009-10-19 This collection of original articles—8 years in the making—shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume. - Presents a broad survey of current research—from local characterizations of the Markov process dynamics to financial market trading activity - Contributors include Nobel Laureate Robert Engle and leading econometricians - Offers a clarity of method and explanation unavailable in other financial econometrics collections |
| econometrics of financial markets: Econometrics of Financial High-Frequency Data Nikolaus Hautsch, 2011-10-12 The availability of financial data recorded on high-frequency level has inspired a research area which over the last decade emerged to a major area in econometrics and statistics. The growing popularity of high-frequency econometrics is driven by technological progress in trading systems and an increasing importance of intraday trading, liquidity risk, optimal order placement as well as high-frequency volatility. This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis. |
| econometrics of financial markets: Financial Economics and Econometrics Nikiforos T. Laopodis, 2021-12-14 Financial Economics and Econometrics provides an overview of the core topics in theoretical and empirical finance, with an emphasis on applications and interpreting results. Structured in five parts, the book covers financial data and univariate models; asset returns; interest rates, yields and spreads; volatility and correlation; and corporate finance and policy. Each chapter begins with a theory in financial economics, followed by econometric methodologies which have been used to explore the theory. Next, the chapter presents empirical evidence and discusses seminal papers on the topic. Boxes offer insights on how an idea can be applied to other disciplines such as management, marketing and medicine, showing the relevance of the material beyond finance. Readers are supported with plenty of worked examples and intuitive explanations throughout the book, while key takeaways, ‘test your knowledge’ and ‘test your intuition’ features at the end of each chapter also aid student learning. Digital supplements including PowerPoint slides, computer codes supplements, an Instructor’s Manual and Solutions Manual are available for instructors. This textbook is suitable for upper-level undergraduate and graduate courses on financial economics, financial econometrics, empirical finance and related quantitative areas. |
| econometrics of financial markets: Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures G. Gregoriou, R. Pascalau, 2010-12-13 This book proposes new methods to build optimal portfolios and to analyze market liquidity and volatility under market microstructure effects, as well as new financial risk measures using parametric and non-parametric techniques. In particular, it investigates the market microstructure of foreign exchange and futures markets. |
| econometrics of financial markets: The Elements of Financial Econometrics Jianqing Fan, Qiwei Yao, 2017-03-23 A compact, master's-level textbook on financial econometrics, focusing on methodology and including real financial data illustrations throughout. The mathematical level is purposely kept moderate, allowing the power of the quantitative methods to be understood without too much technical detail. |
| econometrics of financial markets: High-Frequency Financial Econometrics Yacine Aït-Sahalia, Jean Jacod, 2014-07-21 A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial data High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike. |
| econometrics of financial markets: The Basics of Financial Econometrics Frank J. Fabozzi, Sergio M. Focardi, Svetlozar T. Rachev, Bala G. Arshanapalli, 2014-03-04 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. |
| econometrics of financial markets: Financial Econometrics Using Stata Simona Boffelli, Giovanni Urga, 2016 Financial Econometrics Using Stata is an essential reference for graduate students, researchers, and practitioners who use Stata to perform intermediate or advanced methods. After discussing the characteristics of financial time series, the authors provide introductions to ARMA models, univariate GARCH models, multivariate GARCH models, and applications of these models to financial time series. The last two chapters cover risk management and contagion measures. After a rigorous but intuitive overview, the authors illustrate each method by interpreting easily replicable Stata examples. |
| econometrics of financial markets: Financial Econometrics Peijie Wang, 2005-08-16 This book which provides an overview of contemporary topics related to the modelling of financial time series, is set against a backdrop of rapid expansions of interest in both the models themselves and the financial problems to which they are applied. This excellent textbook covers all the major developments in the area in recent years in an informative as well as succinct way. Refreshingly, every chapter has a section of two or more examples and a section of empirical literature, offering the reader the opportunity to practice the kind of research going on in the area. This approach helps the reader develop interest, confidence and momentum in learning contemporary econometric topics |
| econometrics of financial markets: Applied Financial Econometrics Moinak Maiti, 2021-08-31 This textbook gives students an approachable, down to earth resource for the study of financial econometrics. While the subject can be intimidating, primarily due to the mathematics and modelling involved, it is rewarding for students of finance and can be taught and learned in a straightforward way. This book, going from basics to high level concepts, offers knowledge of econometrics that is intended to be used with confidence in the real world. This book will be beneficial for both students and tutors who are associated with econometrics subjects at any level. |
| econometrics of financial markets: International Financial Markets Julien Chevallier, Stéphane Goutte, David Guerreiro, Sophie Saglio, Bilel Sanhaji, 2019-06-28 This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. International Financial Markets: Volume I provides a key repository on the current state of knowledge, the latest debates and recent literature on international financial markets. Against the background of the financialization of commodities since the 2008 sub-primes crisis, section one contains recent contributions on commodity and financial markets, pushing the frontiers of applied econometrics techniques. The second section is devoted to exchange rate and current account dynamics in an environment characterized by large global imbalances. Part three examines the latest research in the field of meta-analysis in economics and finance. This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature. |
| econometrics of financial markets: Statistical Models and Methods for Financial Markets Tze Leung Lai, Haipeng Xing, 2008-09-08 The idea of writing this bookarosein 2000when the ?rst author wasassigned to teach the required course STATS 240 (Statistical Methods in Finance) in the new M. S. program in ?nancial mathematics at Stanford, which is an interdisciplinary program that aims to provide a master’s-level education in applied mathematics, statistics, computing, ?nance, and economics. Students in the programhad di?erent backgroundsin statistics. Some had only taken a basic course in statistical inference, while others had taken a broad spectrum of M. S. - and Ph. D. -level statistics courses. On the other hand, all of them had already taken required core courses in investment theory and derivative pricing, and STATS 240 was supposed to link the theory and pricing formulas to real-world data and pricing or investment strategies. Besides students in theprogram,thecoursealso attractedmanystudentsfromother departments in the university, further increasing the heterogeneity of students, as many of them had a strong background in mathematical and statistical modeling from the mathematical, physical, and engineering sciences but no previous experience in ?nance. To address the diversity in background but common strong interest in the subject and in a potential career as a “quant” in the ?nancialindustry,thecoursematerialwascarefullychosennotonlytopresent basic statistical methods of importance to quantitative ?nance but also to summarize domain knowledge in ?nance and show how it can be combined with statistical modeling in ?nancial analysis and decision making. The course material evolved over the years, especially after the second author helped as the head TA during the years 2004 and 2005. |
| econometrics of financial markets: Financial Econometric Modeling Stan Hurn, 2020-02 An introduction to the field of financial econometrics, focusing on providing an introduction for undergraduate and postgraduate students whose math skills may not be at the most advanced level, but who need this material to pursue careers in research and the financial industry-- |
| econometrics of financial markets: Handbook Of Financial Econometrics, Mathematics, Statistics, And Machine Learning (In 4 Volumes) Cheng Few Lee, John C Lee, 2020-07-30 This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in asset pricing, corporate finance, international finance, options and futures, risk management, and in stress testing for financial institutions. This handbook discusses a variety of econometric methods, including single equation multiple regression, simultaneous equation regression, and panel data analysis, among others. It also covers statistical distributions, such as the binomial and log normal distributions, in light of their applications to portfolio theory and asset management in addition to their use in research regarding options and futures contracts.In both theory and methodology, we need to rely upon mathematics, which includes linear algebra, geometry, differential equations, Stochastic differential equation (Ito calculus), optimization, constrained optimization, and others. These forms of mathematics have been used to derive capital market line, security market line (capital asset pricing model), option pricing model, portfolio analysis, and others.In recent times, an increased importance has been given to computer technology in financial research. Different computer languages and programming techniques are important tools for empirical research in finance. Hence, simulation, machine learning, big data, and financial payments are explored in this handbook.Led by Distinguished Professor Cheng Few Lee from Rutgers University, this multi-volume work integrates theoretical, methodological, and practical issues based on his years of academic and industry experience. |
| econometrics of financial markets: Complex Systems in Finance and Econometrics Robert A. Meyers, 2010-11-03 Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience. |
| econometrics of financial markets: The Econometrics of Financial Markets John Y. Campbell, Andrew Wen-chuan Lo, 1994 |
| econometrics of financial markets: Statistics of Financial Markets Szymon Borak, Wolfgang Karl Härdle, Brenda López-Cabrera, 2013-01-11 Practice makes perfect. Therefore the best method of mastering models is working with them. This book contains a large collection of exercises and solutions which will help explain the statistics of financial markets. These practical examples are carefully presented and provide computational solutions to specific problems, all of which are calculated using R and Matlab. This study additionally looks at the concept of corresponding Quantlets, the name given to these program codes and which follow the name scheme SFSxyz123. The book is divided into three main parts, in which option pricing, time series analysis and advanced quantitative statistical techniques in finance is thoroughly discussed. The authors have overall successfully created the ideal balance between theoretical presentation and practical challenges. |
| econometrics of financial markets: The Econometric Modelling of Financial Time Series Terence C. Mills, Raphael N. Markellos, 2008-03-20 Terence Mills' best-selling graduate textbook provides detailed coverage of research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. This third edition, co-authored with Raphael Markellos, contains a wealth of material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing. |
| econometrics of financial markets: A Solution Manual to the Econometrics of Financial Markets Petr Adamek, Andrew W. Lo, Archie Craig MacKinlay, 1996-12 |
| econometrics of financial markets: Recent Econometric Techniques for Macroeconomic and Financial Data Gilles Dufrénot, Takashi Matsuki, 2020-11-21 The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models. The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data. |
| econometrics of financial markets: Econometric Analyses of International Housing Markets Rita Yi Man Li, Kwong Wing Chau, 2016-03-31 This book explores how econometric modelling can be used to provide valuable insight into international housing markets. Initially describing the role of econometrics modelling in real estate market research and how it has developed in recent years, the book goes on to compare and contrast the impact of various macroeconomic factors on developed and developing housing markets. Explaining the similarities and differences in the impact of financial crises on housing markets around the world, the author's econometric analysis of housing markets across the world provides a broad and nuanced perspective on the impact of both international financial markets and local macro economy on housing markets. With discussion of countries such as China, Germany, UK, US and South Africa, the lessons learned will be of interest to scholars of Real Estate economics around the world. |
| econometrics of financial markets: Empirical Dynamic Asset Pricing Kenneth J. Singleton, 2009-12-13 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. |
| econometrics of financial markets: Modeling Financial Time Series with S-PLUS Eric Zivot, Jiahui Wang, 2013-11-11 The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the 2000 Outstanding Scholars of the 21st Century by International Biographical Centre. |
| econometrics of financial markets: Market Risk Analysis, Practical Financial Econometrics Carol Alexander, 2008-05-27 Written by leading market risk academic, Professor Carol Alexander, Practical Financial Econometrics forms part two of the Market Risk Analysis four volume set. It introduces the econometric techniques that are commonly applied to finance with a critical and selective exposition, emphasising the areas of econometrics, such as GARCH, cointegration and copulas that are required for resolving problems in market risk analysis. The book covers material for a one-semester graduate course in applied financial econometrics in a very pedagogical fashion as each time a concept is introduced an empirical example is given, and whenever possible this is illustrated with an Excel spreadsheet. All together, the Market Risk Analysis four volume set illustrates virtually every concept or formula with a practical, numerical example or a longer, empirical case study. Across all four volumes there are approximately 300 numerical and empirical examples, 400 graphs and figures and 30 case studies many of which are contained in interactive Excel spreadsheets available from the the accompanying CD-ROM. Empirical examples and case studies specific to this volume include: Factor analysis with orthogonal regressions and using principal component factors; Estimation of symmetric and asymmetric, normal and Student t GARCH and E-GARCH parameters; Normal, Student t, Gumbel, Clayton, normal mixture copula densities, and simulations from these copulas with application to VaR and portfolio optimization; Principal component analysis of yield curves with applications to portfolio immunization and asset/liability management; Simulation of normal mixture and Markov switching GARCH returns; Cointegration based index tracking and pairs trading, with error correction and impulse response modelling; Markov switching regression models (Eviews code); GARCH term structure forecasting with volatility targeting; Non-linear quantile regressions with applications to hedging. |
| econometrics of financial markets: Financial, Macro and Micro Econometrics Using R , 2020-01-20 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. |
| econometrics of financial markets: Econometrics of Risk Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta, Komsan Suriya, 2014-12-15 This edited book contains several state-of-the-art papers devoted to econometrics of risk. Some papers provide theoretical analysis of the corresponding mathematical, statistical, computational, and economical models. Other papers describe applications of the novel risk-related econometric techniques to real-life economic situations. The book presents new methods developed just recently, in particular, methods using non-Gaussian heavy-tailed distributions, methods using non-Gaussian copulas to properly take into account dependence between different quantities, methods taking into account imprecise (fuzzy) expert knowledge, and many other innovative techniques. This versatile volume helps practitioners to learn how to apply new techniques of econometrics of risk, and researchers to further improve the existing models and to come up with new ideas on how to best take into account economic risks. |
| econometrics of financial markets: Econometric Analysis of the Real Estate Market and Investment Peijie Wang, 2003-09-02 This book provides an economic and econometric analysis of real estate investment and real estate market behaviour. Peijie Wang examines fluctuations in the real estate business to reveal the mechanisms governing the interactions between the industry and other sectors of the economy. |
| econometrics of financial markets: Financial Valuation and Econometrics Kian Guan Lim, 2011-03-31 This book brings together domains in financial asset pricing and valuation, financial investment theory, econometrics modeling, and the empirical analyses of financial data by applying appropriate econometric techniques. These domains are highly intertwined and should be properly understood in order to correctly and effectively harness the power of data and methods for investment and financial decision-making. The book is targeted at advanced finance undergraduates and beginner professionals performing financial forecasts or empirical modeling who will find it refreshing to see how forecasting is not simply running a least squares regression line across data points, and that there are many minefields and pitfalls to avoid, such as spurious results and incorrect interpretations. |
| econometrics of financial markets: Energy Economics and Financial Markets André Dorsman, John L. Simpson, Wim Westerman, 2012-10-12 Energy issues feature frequently in the economic and financial press. Specific examples of topical energy issues come from around the globe and often concern economics and finance. The importance of energy production, consumption and trade raises fundamental economic issues that impact the global economy and financial markets. This volume presents research on energy economics and financial markets related to the themes of supply and demand, environmental impact and renewables, energy derivatives trading, and finance and energy. The contributions by experts in their fields take a global perspective, as well as presenting cases from various countries and continents. |
| econometrics of financial markets: Essentials of Applied Econometrics Aaron D. Smith, J. Edward Taylor, 2017 Why Care About Causation? |
| econometrics of financial markets: Financial Econometrics, Mathematics and Statistics Cheng-Few Lee, Hong-Yi Chen, John Lee, 2019-06-03 This rigorous textbook introduces graduate students to the principles of econometrics and statistics with a focus on methods and applications in financial research. Financial Econometrics, Mathematics, and Statistics introduces tools and methods important for both finance and accounting that assist with asset pricing, corporate finance, options and futures, and conducting financial accounting research. Divided into four parts, the text begins with topics related to regression and financial econometrics. Subsequent sections describe time-series analyses; the role of binomial, multi-nomial, and log normal distributions in option pricing models; and the application of statistics analyses to risk management. The real-world applications and problems offer students a unique insight into such topics as heteroskedasticity, regression, simultaneous equation models, panel data analysis, time series analysis, and generalized method of moments. Written by leading academics in the quantitative finance field, allows readers to implement the principles behind financial econometrics and statistics through real-world applications and problem sets. This textbook will appeal to a less-served market of upper-undergraduate and graduate students in finance, economics, and statistics. |
| econometrics of financial markets: Econometrics in a Formal Science of Economics Bernt P. Stigum, 2015 An examination of the role of theory in applied econometrics. |
| econometrics of financial markets: Financial Markets and the Real Economy John H. Cochrane, 2005 Financial Markets and the Real Economy reviews the current academic literature on the macroeconomics of finance. |
| econometrics of financial markets: Determinants of Financial Development Y. Huang, 2010-11-24 A PDF version of this book is available for free in open access via the OAPEN Library platform, www.oapen.org. This book examines the emergence of both financial markets and carbon markets, and provides an in-depth investigation on the fundamental determinants of financial development. |
Econometrics - Wikipedia
Econometrics is an application of statistical methods to economic data in order to give empirical content to economic relationships. [1] More precisely, it is "the quantitative analysis of actual …
Econometrics: Definition, Models, and Methods - Investopedia
May 10, 2025 · Econometrics is the use of statistical and mathematical models to construct theoretical frameworks or verify prior hypotheses in economics and to forecast future trends …
Notes on Econometrics I - Scholars at Harvard
This set of notes is intended to supplement the typical first semester of econometrics taken by PhD students in public policy, eco-nomics, and other related fields. It was developed …
What is Econometrics? Types, Stages and Functions
Econometrics is the quantitative application of statistical inferences, economic theory and mathematical models using data to develop theories or test existing hypotheses in economics …
What Is Econometrics? Back to Basics: Finance ... - IMF
Econometrics uses economic theory, mathematics, and statistical inference to quantify economic phenomena. In other words, it turns theoretical economic models into useful tools for …
Econometrics | Economics | MIT OpenCourseWare
The course will cover several key models as well as identification and estimation methods used in modern econometrics. We shall being with exploring some leading models of econometrics, …
What Is Econometrics? With Types, Tools and Skills
Mar 26, 2025 · Econometrics is the application of statistical and mathematical models to analyze economic data and create new economic models. Econometricians develop economic or …
Econometrics : Meaning, Examples, Theory and Methods
Apr 15, 2024 · What is Econometrics? Econometrics is a branch of economics that applies statistical methods and mathematical models to analyze economic data. It combines economic …
What is econometrics? - Lerner - University of Delaware
Jul 13, 2023 · Econometrics is a combination of three different fields: economics, statistics and mathematics. It is a quantitative analysis of economic phenomena that uses mathematical …
Econometrics - Overview, How it Works, Examples
What is Econometrics? Econometrics is an area of economics where statistical and mathematical methods are used to analyze economic data. Individuals who are involved with econometrics …
Econometrics - Wikipedia
Econometrics is an application of statistical methods to economic data in order to give empirical content to economic relationships. [1] More precisely, it is "the quantitative analysis of actual …
Econometrics: Definition, Models, and Methods - Investopedia
May 10, 2025 · Econometrics is the use of statistical and mathematical models to construct theoretical frameworks or verify prior hypotheses in economics and to forecast future trends …
Notes on Econometrics I - Scholars at Harvard
This set of notes is intended to supplement the typical first semester of econometrics taken by PhD students in public policy, eco-nomics, and other related fields. It was developed …
What is Econometrics? Types, Stages and Functions
Econometrics is the quantitative application of statistical inferences, economic theory and mathematical models using data to develop theories or test existing hypotheses in economics …
What Is Econometrics? Back to Basics: Finance ... - IMF
Econometrics uses economic theory, mathematics, and statistical inference to quantify economic phenomena. In other words, it turns theoretical economic models into useful tools for …
Econometrics | Economics | MIT OpenCourseWare
The course will cover several key models as well as identification and estimation methods used in modern econometrics. We shall being with exploring some leading models of econometrics, …
What Is Econometrics? With Types, Tools and Skills
Mar 26, 2025 · Econometrics is the application of statistical and mathematical models to analyze economic data and create new economic models. Econometricians develop economic or …
Econometrics : Meaning, Examples, Theory and Methods
Apr 15, 2024 · What is Econometrics? Econometrics is a branch of economics that applies statistical methods and mathematical models to analyze economic data. It combines economic …
What is econometrics? - Lerner - University of Delaware
Jul 13, 2023 · Econometrics is a combination of three different fields: economics, statistics and mathematics. It is a quantitative analysis of economic phenomena that uses mathematical …
Econometrics - Overview, How it Works, Examples
What is Econometrics? Econometrics is an area of economics where statistical and mathematical methods are used to analyze economic data. Individuals who are involved with econometrics …
