Provides statistical tools and techniques needed to understand today's financial markets The Second Edition of this critically acclaimed text provides a comprehensive and systematic introduction to financial econometric models and their applications in modeling and predicting financial time series data.
Tools to improve decision making in an imperfect world This publication provides readers with a thorough understanding of Bayesian analysis that is grounded in the theory of inference and optimal decision making.
A comprehensive account of economic size distributions around the world and throughout the years In the course of the past 100 years, economists and applied statisticians have developed a remarkably diverse variety of income distribution models, yet no single resource convincingly accounts for all of these models, analyzing their strengths and weaknesses, similarities and differences.
Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation.
This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications to modeling and prediction of financial time series data.
The first cutting-edge guide to using the SAS system for the analysis of econometric data Applied Econometrics Using the SAS System is the first book of its kind to treat the analysis of basic econometric data using SAS , one of the most commonly used software tools among today's statisticians in business and industry.
This groundbreaking book extends traditional approaches of risk measurement and portfolio optimization by combining distributional models with risk or performance measures into one framework.
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.
Handbook of Computational Economics: Heterogeneous Agent Modeling, Volume Four, focuses on heterogeneous agent models, emphasizing recent advances in macroeconomics (including DSGE), finance, empirical validation and experiments, networks and related applications.
Handbook of Field Experiments, Volume Two explains how to conduct experimental research, presents a catalog of research to date, and describes which areas remain to be explored.
Handbook of Econometrics, Volume 7A, examines recent advances in foundational issues and "e;hot"e; topics within econometrics, such as inference for moment inequalities and estimation of high dimensional models.
Handbook of Field Experiments provides tactics on how to conduct experimental research, also presenting a comprehensive catalog on new results from research and areas that remain to be explored.
Applied financial econometrics subjects are featured in this second volume, with papers that survey important research even as they make unique empirical contributions to the literature.
In today's fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information.
In today's fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information.
Pathwise estimation and inference for diffusion market models discusses contemporary techniques for inferring, from options and bond prices, the market participants' aggregate view on important financial parameters such as implied volatility, discount rate, future interest rate, and their uncertainty thereof.
Pathwise estimation and inference for diffusion market models discusses contemporary techniques for inferring, from options and bond prices, the market participants' aggregate view on important financial parameters such as implied volatility, discount rate, future interest rate, and their uncertainty thereof.
Inhomogeneous Random Evolutions and Their Applications explains how to model various dynamical systems in finance and insurance with non-homogeneous in time characteristics.
Inhomogeneous Random Evolutions and Their Applications explains how to model various dynamical systems in finance and insurance with non-homogeneous in time characteristics.
