Testing investment forecast efficiency with textual data

Alexander Foltas

No 19, Working Papers from German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin

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.

Keywords: Forecast Efficiency; Investment; Random Forest; Topic Modeling (search for similar items in EconPapers)
JEL-codes: C53 E22 E27 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-big, nep-cmp and nep-mac
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:pp1859:19

DOI: 10.18452/21651

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