Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Stock Values and Earnings Call Transcripts: a Dataset Suitable for Sentiment Analysis

Version 1 : Received: 17 February 2021 / Approved: 18 February 2021 / Online: 18 February 2021 (17:22:50 CET)

How to cite: Roozen, D.; Lelli, F. Stock Values and Earnings Call Transcripts: a Dataset Suitable for Sentiment Analysis. Preprints 2021, 2021020424 (doi: 10.20944/preprints202102.0424.v1). Roozen, D.; Lelli, F. Stock Values and Earnings Call Transcripts: a Dataset Suitable for Sentiment Analysis. Preprints 2021, 2021020424 (doi: 10.20944/preprints202102.0424.v1).

Abstract

The dataset reports a collection of earnings call transcripts, the related stock prices, and the related sector index. It contains a total of 188 transcripts, 11970 stock prices, and 1196 sector index values. Furthermore, all of these data originated in the period 2016-2020 and are related to the NASDAQ stock market. The data have been collected using Yahoo Finance and Thomson Reuters Eikon. Specifically, Yahoo Finance offered daily stock prices and traded volume. At the same time, Thomson Reuters Eikon has been used as source for the earnings call transcripts. The dataset can be used as a benchmark for the evaluation of several NLP techniques as well as machine learning algorithms for understanding their potential for financial applications. Moreover, it is also possible to expand the dataset by extending the period in which the data originated following a similar procedure.

Supplementary and Associated Material

https://francescolelli.info/: Francesco Lelli Author's website

Subject Areas

dataset; stock; sentiment analysis; nlp; Nasdaq; stock prices; ML

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