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Testing investment forecast efficiency with textual data

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  • Foltas, Alexander

Abstract

I use textual data to model German professional macroeconomic forecasters' information sets and use machine-learning techniques to analyze the efficiency of forecasts. To this end, I extract information from forecast reports using a combination of topic models and word embeddings. I then use this information and traditional macroeconomic predictors to study the efficiency of investment forecasts.

Suggested Citation

  • Foltas, Alexander, 2020. "Testing investment forecast efficiency with textual data," Working Papers 19, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    • Handle: RePEc:zbw:pp1859:19
    DOI: 10.18452/21651
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    References listed on IDEAS

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    7. Ulrich Fritsche & Johannes Puckelwald, 2018. "Deciphering Professional Forecasters’ Stories - Analyzing a Corpus of Textual Predictions for the German Economy," Macroeconomics and Finance Series 201804, University of Hamburg, Department of Socioeconomics.
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    9. Christoph Behrens, 2019. "A Nonparametric Evaluation of the Optimality of German Export and Import Growth Forecasts under Flexible Loss," Economies, MDPI, vol. 7(3), pages 1-23, September.
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    Cited by:

    1. Alexander Foltas & Christian Pierdzioch, 2022. "Business-cycle reports and the efficiency of macroeconomic forecasts for Germany," Applied Economics Letters, Taylor & Francis Journals, vol. 29(10), pages 867-872, June.
    2. Foltas, Alexander & Pierdzioch, Christian, 2020. "On the efficiency of German growth forecasts: An empirical analysis using quantile random forests," Working Papers 21, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.

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    More about this item

    Keywords

    Forecast Efficiency; Investment; Random Forest; Topic Modeling;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity

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