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This book offers an overview of state-of-the-art econometric
techniques, with a special emphasis on financial econometrics.
There is a major need for such techniques, since the traditional
way of designing mathematical models - based on researchers'
insights - can no longer keep pace with the ever-increasing data
flow. To catch up, many application areas have begun relying on
data science, i.e., on techniques for extracting models from data,
such as data mining, machine learning, and innovative statistics.
In terms of capitalizing on data science, many application areas
are way ahead of economics. To close this gap, the book provides
examples of how data science techniques can be used in economics.
Corresponding techniques range from almost traditional statistics
to promising novel ideas such as quantum econometrics. Given its
scope, the book will appeal to students and researchers interested
in state-of-the-art developments, and to practitioners interested
in using data science techniques.
This volume emphasizes techniques of optimal transport statistics,
but it also describes and uses other econometric techniques,
ranging from more traditional statistical techniques to more
innovative ones such as quantiles (in particular, multidimensional
quantiles), maximum entropy approach, and machine learning.
Applications range from general analysis of GDP growth, stock
market, and consumer prices to analysis of specific sectors of
economics (construction, credit and banking, energy, health, labor,
textile, tourism, international trade) to specific issues affecting
economy such as bankruptcy, effect of Covid-19 pandemic, effect of
pollution, effect of gender, cryptocurrencies, and the existence of
shadow economy. Papers presented in this volume also cover data
processing techniques, with economic and financial application
being the unifying theme. This volume shows what has been achieved,
but even more important are remaining open problems. We hope that
this volume will: ˆ inspire practitioners to learn how to apply
state-of-the-art techniques, especially techniques of optimal
transport statistics, to economic and financial problems, and ˆ
inspire researchers to further improve the existing techniques and
to come up with new techniques for studying economic and financial
phenomena.
This book overviews latest ideas and developments in financial
econometrics, with an emphasis on how to best use prior knowledge
(e.g., Bayesian way) and how to best use successful data processing
techniques from other application areas (e.g., from quantum
physics). The book also covers applications to economy-related
phenomena ranging from traditionally analyzed phenomena such as
manufacturing, food industry, and taxes, to newer-to-analyze
phenomena such as cryptocurrencies, influencer marketing, COVID-19
pandemic, financial fraud detection, corruption, and shadow
economy. This book will inspire practitioners to learn how to apply
state-of-the-art Bayesian, quantum, and related techniques to
economic and financial problems and inspire researchers to further
improve the existing techniques and come up with new techniques for
studying economic and financial phenomena. The book will also be of
interest to students interested in latest ideas and results.
This book provides the ultimate goal of economic studies to predict
how the economy develops-and what will happen if we implement
different policies. To be able to do that, we need to have a good
understanding of what causes what in economics. Prediction and
causality in economics are the main topics of this book's chapters;
they use both more traditional and more innovative
techniques-including quantum ideas -- to make predictions about the
world economy (international trade, exchange rates), about a
country's economy (gross domestic product, stock index, inflation
rate), and about individual enterprises, banks, and micro-finance
institutions: their future performance (including the risk of
bankruptcy), their stock prices, and their liquidity. Several
papers study how COVID-19 has influenced the world economy. This
book helps practitioners and researchers to learn more about
prediction and causality in economics -- and to further develop
this important research direction.
This book overviews latest ideas and developments in financial
econometrics, with an emphasis on how to best use prior knowledge
(e.g., Bayesian way) and how to best use successful data processing
techniques from other application areas (e.g., from quantum
physics). The book also covers applications to economy-related
phenomena ranging from traditionally analyzed phenomena such as
manufacturing, food industry, and taxes, to newer-to-analyze
phenomena such as cryptocurrencies, influencer marketing, COVID-19
pandemic, financial fraud detection, corruption, and shadow
economy. This book will inspire practitioners to learn how to apply
state-of-the-art Bayesian, quantum, and related techniques to
economic and financial problems and inspire researchers to further
improve the existing techniques and come up with new techniques for
studying economic and financial phenomena. The book will also be of
interest to students interested in latest ideas and results.
This book provides the ultimate goal of economic studies to predict
how the economy develops-and what will happen if we implement
different policies. To be able to do that, we need to have a good
understanding of what causes what in economics. Prediction and
causality in economics are the main topics of this book's chapters;
they use both more traditional and more innovative
techniques-including quantum ideas -- to make predictions about the
world economy (international trade, exchange rates), about a
country's economy (gross domestic product, stock index, inflation
rate), and about individual enterprises, banks, and micro-finance
institutions: their future performance (including the risk of
bankruptcy), their stock prices, and their liquidity. Several
papers study how COVID-19 has influenced the world economy. This
book helps practitioners and researchers to learn more about
prediction and causality in economics -- and to further develop
this important research direction.
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