Macro Forecasting Using Alternative Data

Macro Forecasting Using Alternative Data
Author: Apurv Jain
Publsiher: Unknown
Total Pages: 48
Release: 2019
ISBN 10: 1928374650XXX
ISBN 13: OCLC:1304265178
Language: EN, FR, DE, ES & NL

Macro Forecasting Using Alternative Data Book Review:

Traditional macroeconomic data used by economic agents to make decisions are noisy, lack richness, and produced with considerable lag. This chapter explores how alternative, web-scale data sources (“Big Data”) can help. We present a case study using a common alternative data source- web search to predict one of the most important data releases- non-farm payrolls (NFP). We discuss the efficacy of various machine learning (ML) techniques, the live performance of alternative data prediction models and the typical problems faced in practice.

Macroeconomic Forecasting Using Alternative Data

Macroeconomic Forecasting Using Alternative Data
Author: Apurv Jain
Publsiher: Academic Press
Total Pages: 250
Release: 2020-12-01
ISBN 10: 0128191228
ISBN 13: 9780128191224
Language: EN, FR, DE, ES & NL

Macroeconomic Forecasting Using Alternative Data Book Review:

Macroeconomic Forecasting Using Alternative Data: Techniques for Applying Big Data and Machine Learning applies computer science to the demands of macroeconomic forecasting. It is the first book to combine machine learning methods with macroeconomics. By using artificial intelligence and machine learning techniques, it unlocks the increased forecasting accuracy offered by alternative data sources. Through its interdisciplinary approach, readers learn how to use big datasets efficiently and effectively. Combines big data/machine learning with macroeconomic forecasting Explains how alternative data improves forecasting accuracy when controlled for traditional data sources Provides new innovative methods for handling large databases and improving forecasting accuracy

Does Alternative Data Improve Financial Forecasting

Does Alternative Data Improve Financial Forecasting
Author: Olivier Dessaint,Thierry Foucault,Laurent Frésard
Publsiher: Unknown
Total Pages: 64
Release: 2021
ISBN 10: 1928374650XXX
ISBN 13: OCLC:1262661520
Language: EN, FR, DE, ES & NL

Does Alternative Data Improve Financial Forecasting Book Review:

We analyze the effect of alternative data on the informativeness of financial forecasts. Our starting hypothesis is that the emergence of alternative data reduces the cost of obtaining information about firms' short-term cash-flows more than their long-term cash-flows. If correct, and forecasting short-term and long-term cash-flows are distinct tasks, analysts will reduce effort to process long-term information when alternative data become available. Alternative data thus makes long-term forecasts less informative, while increasing the informativeness of short-term forecasts. We confirm this prediction using variations in analysts' exposure to social media data and a new measure of forecast informativeness at various horizons.

Fintech with Artificial Intelligence Big Data and Blockchain

Fintech with Artificial Intelligence  Big Data  and Blockchain
Author: Paul Moon Sub Choi,Seth H. Huang
Publsiher: Springer Nature
Total Pages: 304
Release: 2021-03-08
ISBN 10: 9813361379
ISBN 13: 9789813361379
Language: EN, FR, DE, ES & NL

Fintech with Artificial Intelligence Big Data and Blockchain Book Review:

This book introduces readers to recent advancements in financial technologies. The contents cover some of the state-of-the-art fields in financial technology, practice, and research associated with artificial intelligence, big data, and blockchain—all of which are transforming the nature of how products and services are designed and delivered, making less adaptable institutions fast become obsolete. The book provides the fundamental framework, research insights, and empirical evidence in the efficacy of these new technologies, employing practical and academic approaches to help professionals and academics reach innovative solutions and grow competitive strengths.

Macroeconomic Forecasting in the Era of Big Data

Macroeconomic Forecasting in the Era of Big Data
Author: Peter Fuleky
Publsiher: Springer Nature
Total Pages: 719
Release: 2019-11-28
ISBN 10: 3030311503
ISBN 13: 9783030311506
Language: EN, FR, DE, ES & NL

Macroeconomic Forecasting in the Era of Big Data Book Review:

This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

Handbook of US Consumer Economics

Handbook of US Consumer Economics
Author: Andrew Haughwout,Benjamin Mandel
Publsiher: Academic Press
Total Pages: 550
Release: 2019-08-15
ISBN 10: 0128135247
ISBN 13: 9780128135242
Language: EN, FR, DE, ES & NL

Handbook of US Consumer Economics Book Review:

Handbook of U.S. Consumer Economics presents a deep understanding on key, current topics and a primer on the landscape of contemporary research on the U.S. consumer. This volume reveals new insights into household decision-making on consumption and saving, borrowing and investing, portfolio allocation, demand of professional advice, and retirement choices. Nearly 70% of U.S. gross domestic product is devoted to consumption, making an understanding of the consumer a first order issue in macroeconomics. After all, understanding how households played an important role in the boom and bust cycle that led to the financial crisis and recent great recession is a key metric. Introduces household finance by examining consumption and borrowing choices Tackles macro-problems by observing new, original micro-data Looks into the future of consumer spending by using data, not questionnaires

Handbook of US Consumer Economics

Handbook of US Consumer Economics
Author: Andrew Haughwout,Benjamin Mandel
Publsiher: Academic Press
Total Pages: 456
Release: 2019-08-12
ISBN 10: 0128135255
ISBN 13: 9780128135259
Language: EN, FR, DE, ES & NL

Handbook of US Consumer Economics Book Review:

Handbook of U.S. Consumer Economics presents a deep understanding on key, current topics and a primer on the landscape of contemporary research on the U.S. consumer. This volume reveals new insights into household decision-making on consumption and saving, borrowing and investing, portfolio allocation, demand of professional advice, and retirement choices. Nearly 70% of U.S. gross domestic product is devoted to consumption, making an understanding of the consumer a first order issue in macroeconomics. After all, understanding how households played an important role in the boom and bust cycle that led to the financial crisis and recent great recession is a key metric. Introduces household finance by examining consumption and borrowing choices Tackles macro-problems by observing new, original micro-data Looks into the future of consumer spending by using data, not questionnaires

Data Science for Economics and Finance

Data Science for Economics and Finance
Author: Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Publsiher: Springer Nature
Total Pages: 355
Release: 2021
ISBN 10: 3030668916
ISBN 13: 9783030668914
Language: EN, FR, DE, ES & NL

Data Science for Economics and Finance Book Review:

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Alternative Economic Indicators

Alternative Economic Indicators
Author: C. James Hueng
Publsiher: W.E. Upjohn Institute
Total Pages: 132
Release: 2020-09-08
ISBN 10: 0880996765
ISBN 13: 9780880996761
Language: EN, FR, DE, ES & NL

Alternative Economic Indicators Book Review:

Policymakers and business practitioners are eager to gain access to reliable information on the state of the economy for timely decision making. More so now than ever. Traditional economic indicators have been criticized for delayed reporting, out-of-date methodology, and neglecting some aspects of the economy. Recent advances in economic theory, econometrics, and information technology have fueled research in building broader, more accurate, and higher-frequency economic indicators. This volume contains contributions from a group of prominent economists who address alternative economic indicators, including indicators in the financial market, indicators for business cycles, and indicators of economic uncertainty.

Adventures in Financial Data Science The Empirical Properties of Financial and Economic Data Second Edition

Adventures in Financial Data Science  The Empirical Properties of Financial and Economic Data   Second Edition
Author: Graham L. Giller
Publsiher: World Scientific
Total Pages: 512
Release: 2022
ISBN 10: 9811251827
ISBN 13: 9789811251825
Language: EN, FR, DE, ES & NL

Adventures in Financial Data Science The Empirical Properties of Financial and Economic Data Second Edition Book Review:

Economic Forecasting

Economic Forecasting
Author: Graham Elliott,Allan Timmermann
Publsiher: Princeton University Press
Total Pages: 568
Release: 2016-04-05
ISBN 10: 0691140138
ISBN 13: 9780691140131
Language: EN, FR, DE, ES & NL

Economic Forecasting Book Review:

Economic forecasting involves choosing simple yet robust models to best approximate highly complex and evolving data-generating processes. This poses unique challenges for researchers in a host of practical forecasting situations, from forecasting budget deficits and assessing financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the costs and benefits of different methods currently available to forecasters. This text approaches forecasting problems from the perspective of decision theory and estimation, and demonstrates the profound implications of this approach for how we understand variable selection, estimation, and combination methods for forecasting models, and how we evaluate the resulting forecasts. Both Bayesian and non-Bayesian methods are covered in depth, as are a range of cutting-edge techniques for producing point, interval, and density forecasts. The book features detailed presentations and empirical examples of a range of forecasting methods and shows how to generate forecasts in the presence of large-dimensional sets of predictor variables. The authors pay special attention to how estimation error, model uncertainty, and model instability affect forecasting performance. Presents a comprehensive and integrated approach to assessing the strengths and weaknesses of different forecasting methods Approaches forecasting from a decision theoretic and estimation perspective Covers Bayesian modeling, including methods for generating density forecasts Discusses model selection methods as well as forecast combinations Covers a large range of nonlinear prediction models, including regime switching models, threshold autoregressions, and models with time-varying volatility Features numerous empirical examples Examines the latest advances in forecast evaluation Essential for practitioners and students alike

A Companion to Economic Forecasting

A Companion to Economic Forecasting
Author: Michael P. Clements,David F. Hendry
Publsiher: John Wiley & Sons
Total Pages: 616
Release: 2008-04-15
ISBN 10: 140517191X
ISBN 13: 9781405171915
Language: EN, FR, DE, ES & NL

A Companion to Economic Forecasting Book Review:

A Companion to Economic Forecasting provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together in a single volume a range of contrasting approaches and views. Uniquely surveying forecasting in a single volume, the Companion provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed.

The Book of Alternative Data

The Book of Alternative Data
Author: Alexander Denev,Saeed Amen
Publsiher: John Wiley & Sons
Total Pages: 416
Release: 2020-06-29
ISBN 10: 1119601800
ISBN 13: 9781119601807
Language: EN, FR, DE, ES & NL

The Book of Alternative Data Book Review:

The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.

The Oxford Handbook of Economic Forecasting

The Oxford Handbook of Economic Forecasting
Author: Michael P. Clements,David F. Hendry
Publsiher: OUP USA
Total Pages: 712
Release: 2011-07-08
ISBN 10: 0195398645
ISBN 13: 9780195398649
Language: EN, FR, DE, ES & NL

The Oxford Handbook of Economic Forecasting Book Review:

Greater data availability has been coupled with developments in statistical theory and economic theory to allow more elaborate and complicated models to be entertained. These include factor models, DSGE models, restricted vector autoregressions, and non-linear models.

Economic Forecasts

Economic Forecasts
Author: Ralf Brüggemann,Winfried Pohlmeier,Werner Smolny
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 176
Release: 2016-11-21
ISBN 10: 3110510847
ISBN 13: 9783110510843
Language: EN, FR, DE, ES & NL

Economic Forecasts Book Review:

Forecasts guide decisions in all areas of economics and finance. Economic policy makers base their decisions on business cycle forecasts, investment decisions of firms are based on demand forecasts, and portfolio managers try to outperform the market based on financial market forecasts. Forecasts extract relevant information from the past and help to reduce the inherent uncertainty of the future. The topic of this special issue of the Journal of Economics and Statistics is the theory and practise of forecasting and forecast evaluation and an overview of the state of the art of forecasting.

Big Data for Twenty First Century Economic Statistics

Big Data for Twenty First Century Economic Statistics
Author: Katharine G. Abraham,Ron S. Jarmin,Brian C. Moyer,Matthew D. Shapiro
Publsiher: University of Chicago Press
Total Pages: 488
Release: 2022-03-11
ISBN 10: 022680125X
ISBN 13: 9780226801254
Language: EN, FR, DE, ES & NL

Big Data for Twenty First Century Economic Statistics Book Review:

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.

Mining Data for Financial Applications

Mining Data for Financial Applications
Author: Valerio Bitetta,Ilaria Bordino,Andrea Ferretti,Francesco Gullo,Giovanni Ponti,Lorenzo Severini
Publsiher: Springer Nature
Total Pages: 151
Release: 2021-01-14
ISBN 10: 3030669815
ISBN 13: 9783030669812
Language: EN, FR, DE, ES & NL

Mining Data for Financial Applications Book Review:

This book constitutes revised selected papers from the 5th Workshop on Mining Data for Financial Applications, MIDAS 2020, held in conjunction with ECML PKDD 2020, in Ghent, Belgium, in September 2020.* The 8 full and 3 short papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with challenges, potentialities, and applications of leveraging data-mining tasks regarding problems in the financial domain. *The workshop was held virtually due to the COVID-19 pandemic. “Information Extraction from the GDELT Database to Analyse EU Sovereign Bond Markets” and “Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Macroeconomic Forecasting

Macroeconomic Forecasting
Author: Robert Evans
Publsiher: Routledge
Total Pages: 256
Release: 2002-01-22
ISBN 10: 1134623461
ISBN 13: 9781134623464
Language: EN, FR, DE, ES & NL

Macroeconomic Forecasting Book Review:

Drawing on interviews with the UK government's Panel of Independent Forecasters, the author shows how economic models, forecasts and policy analysis depend crucially upon the judgements of economists.

Big Data and Machine Learning in Quantitative Investment

Big Data and Machine Learning in Quantitative Investment
Author: Tony Guida
Publsiher: John Wiley & Sons
Total Pages: 296
Release: 2018-12-12
ISBN 10: 1119522080
ISBN 13: 9781119522089
Language: EN, FR, DE, ES & NL

Big Data and Machine Learning in Quantitative Investment Book Review:

Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance. The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning. • Gain a solid reason to use machine learning • Frame your question using financial markets laws • Know your data • Understand how machine learning is becoming ever more sophisticated Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment — and this book shows you how.

Economic and Business Forecasting

Economic and Business Forecasting
Author: John E. Silvia,Azhar Iqbal,Kaylyn Swankoski,Sarah Watt,Sam Bullard
Publsiher: John Wiley & Sons
Total Pages: 400
Release: 2014-03-10
ISBN 10: 1118569547
ISBN 13: 9781118569542
Language: EN, FR, DE, ES & NL

Economic and Business Forecasting Book Review:

Discover the secrets to applying simple econometric techniques to improve forecasting Equipping analysts, practitioners, and graduate students with a statistical framework to make effective decisions based on the application of simple economic and statistical methods, Economic and Business Forecasting offers a comprehensive and practical approach to quantifying and accurate forecasting of key variables. Using simple econometric techniques, author John E. Silvia focuses on a select set of major economic and financial variables, revealing how to optimally use statistical software as a template to apply to your own variables of interest. Presents the economic and financial variables that offer unique insights into economic performance Highlights the econometric techniques that can be used to characterize variables Explores the application of SAS software, complete with simple explanations of SAS-code and output Identifies key econometric issues with practical solutions to those problems Presenting the "ten commandments" for economic and business forecasting, this book provides you with a practical forecasting framework you can use for important everyday business applications.