Econometrics

This handbook (in 4 volumes) investigates important tools for empirical and theoretical research in finance and accounting. Based on editors' and c...

Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide varie...

In response to the damage caused by a growth-led global economy, researchers across the world started investigating the association between environ...

This textbook for advanced econometrics students introduces key concepts of dynamic non-stationary modelling. It discusses all the classic topics i...

The Regression Discontinuity (RD) design is one of the most popular and credible research designs for program evaluation and causal inference. This...

A User's Guide to Business Analytics provides a comprehensive discussion of statistical methods useful to the business analyst. Methods are develop...

Volume 40 in the Advances in Econometrics series features twenty-three chapters that are split thematically into two parts. Part A presents novel c...

The Causes of Tropical Deforestation (1994) is an analysis of the problem of deforestation, using statistical technique a form of environ-metrics ...

Expand your data analysis toolkit with Python, R, and Tableau Data Analytics Common Core is designed to help professionals transition from spreadsh...

Focusing on methods for data that are ordered in time, this textbook provides a comprehensive guide to analyzing time series data using modern tech...

Focusing on methods for data that are ordered in time, this textbook provides a comprehensive guide to analyzing time series data using modern tech...

Die Beschäftigung mit finanzwirtschaftlichen Fragestellungen erfordert heute mehr denn je fundierte mathematische Kenntnisse nicht nur im Rahmen d...

Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and pra...

The aim of the book is to help students become data scientists. Since this requires a series of courses over a considerable period of time, the boo...

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tra...

This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. The...

This textbook is a comprehensive introduction to applied spatial data analysis using R. Each chapter walks the reader through a different method, e...

Technical Analysis of Stock Trends helps investors make smart, profitable trading decisions by providing proven long- and short-term stock trend an...

This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. The...

Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and providing detail...

Now in its third edition, Essential Econometric Techniques: A Guide to Concepts and Applications is a concise, student-friendly textbook which prov...

Since a major source of income for many countries comes from exporting commodities, price discovery and information transmission between commodity ...

The book unifies quantum theory and the general theory of relativity. As an unsolved problem for about 100 years and influencing so many fields, th...

Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along wit...

Developed over 20 years of teaching academic courses, the Handbook of Financial Risk Management can be divided into two main parts: risk management...

This book presents a critical review of the empirical literature that studies the efficiency of the forward and futures markets for foreign exchang...

Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with t...

Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is...

Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. Th...

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory fro...