macroeconomic forecasting using alternative data

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Macroeconomic Forecasting Using Alternative Data
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Publisher : Academic Press
Release Date :
ISBN 10 : 9780128191217
Pages : 250 pages
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Macroeconomic Forecasting Using Alternative Data 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 improve forecasting accuracy when controlled for traditional data sources Provides new innovative methods for handling large databases and improving forecasting accuracy

Macroeconomic Forecasting Using Alternative Data

Macroeconomic Forecasting Using Alternative Data 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

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Macro Forecasting Using Alternative Data

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

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Macroeconomic Forecasting in the Era of Big Data

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Does Alternative Data Improve Financial Forecasting

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

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Handbook of US Consumer Economics

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

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Alternative Economic Indicators

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,

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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

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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,

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This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full papers presented were

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The papers in this volume analyze the deployment of Big Data to solve both existing and novel challenges in economic measurement. The existing infrastructure for the production of key economic statistics relies heavily on data collected through sample surveys and periodic censuses, together with administrative records generated in connection with

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