Econometrics and economic statistics

Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness.

Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness.

Master business modeling and analysis techniques with Microsoft Excel 2016, and transform data into bottom-line results.

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book.

Data mining has become the fastest growing topic of interest in business programs in the past decade.

An Introduction to Data Science is an easy-to-read, gentle introduction for advanced undergraduate, certificate, and graduate students coming from a wide range of backgrounds into the world of data science.

Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas.

Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas.

An Introduction to Statistics and Data Analysis Using Stata(R): From Research Design to Final Report provides a step-by-step introduction for statistics, data analysis, or research methods classes using Stata software.

An Introduction to Statistics and Data Analysis Using Stata(R): From Research Design to Final Report provides a step-by-step introduction for statistics, data analysis, or research methods classes using Stata software.

Addressing the immensely important topic of research credibility, Raymond Hubbard's groundbreaking work proposes that we must treat such information with a healthy dose of skepticism.

A provocative new analysis of immigration's long-term effects on a nation's economy and culture.

In this book, the development process of blockchain algorithms and examples of their applications in different sectors are explored.

This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis.

This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis.

The growth of machines and users of the Internet has led to the proliferation of all sorts of data concerning individuals, institutions, companies, governments, universities, and all kinds of known objects and events happening everywhere in daily life.

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities.

Solve the DVA/FVA Overlap Issue and Effectively Manage Portfolio Credit RiskCounterparty Risk and Funding: A Tale of Two Puzzles explains how to study risk embedded in financial transactions between the bank and its counterparty.

Versatile for Several Interrelated Courses at the Undergraduate and Graduate LevelsFinancial Mathematics: A Comprehensive Treatment provides a unified, self-contained account of the main theory and application of methods behind modern-day financial mathematics.

In an easy-to-understand, nontechnical yet mathematically elegant manner, An Introduction to Exotic Option Pricing shows how to price exotic options, including complex ones, without performing complicated integrations or formally solving partial differential equations (PDEs).

This book is especially relevant to undergraduates, postgraduates and researchers studying quantitative techniques as part of business, management and finance.

Teach Your Students How to Become Successful Working QuantsQuantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration.

Financial Mathematics: From Discrete to Continuous Time is a study of the mathematical ideas and techniques that are important to the two main arms of the area of financial mathematics: portfolio optimization and derivative valuation.

Financial Mathematics: From Discrete to Continuous Time is a study of the mathematical ideas and techniques that are important to the two main arms of the area of financial mathematics: portfolio optimization and derivative valuation.

This book provides an introduction to R programming and a summary of financial mathematics.

A properly structured financial model can provide decision makers with a powerful planning tool that helps them identify the consequences of their decisions before they are put into practice.

A properly structured financial model can provide decision makers with a powerful planning tool that helps them identify the consequences of their decisions before they are put into practice.

Written in a highly accessible style, A Factor Model Approach to Derivative Pricing lays a clear and structured foundation for the pricing of derivative securities based upon simple factor model related absence of arbitrage ideas.

Written in a highly accessible style, A Factor Model Approach to Derivative Pricing lays a clear and structured foundation for the pricing of derivative securities based upon simple factor model related absence of arbitrage ideas.

If you know a little bit about financial mathematics but don't yet know a lot about programming, then C++ for Financial Mathematics is for you.

If you know a little bit about financial mathematics but don't yet know a lot about programming, then C++ for Financial Mathematics is for you.

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems.

This short book introduces the main ideas of statistical inference in a way that is both user friendly and mathematically sound.

This short book introduces the main ideas of statistical inference in a way that is both user friendly and mathematically sound.

A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of actuarial science.

Introduction to Functional Data Analysis provides a concise textbook introduction to the field.

Introduction to Functional Data Analysis provides a concise textbook introduction to the field.

Focusing on Bayesian approaches and computations using analytic and simulation-based methods for inference, Time Series: Modeling, Computation, and Inference, Second Edition integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis.

The quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries.

Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner's hands-on experience.

Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner's hands-on experience.

Virtually any random process developing chronologically can be viewed as a time series.

Virtually any random process developing chronologically can be viewed as a time series.

The goal of Portfolio Rebalancing is to provide mathematical and empirical analysis of the effects of portfolio rebalancing on portfolio returns and risks.

Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions.

The advent of "e;Big Data"e; has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons.

A fair question to ask of an advocate of subjective Bayesianism (which the author is) is "e;how would you model uncertainty?

This book is among the first to present the mathematical models most commonly used to solve optimal execution problems and market making problems in finance.

All the Tools for Gathering and Analyzing Data and Presenting ResultsReproducible Research with R and RStudio, Second Edition brings together the skills and tools needed for doing and presenting computational research.