An Exploratory Study of Stock Price Movements from Earnings Calls

01/31/2022
by   Sourav Medya, et al.
0

Financial market analysis has focused primarily on extracting signals from accounting, stock price, and other numerical hard data reported in P L statements or earnings per share reports. Yet, it is well-known that the decision-makers routinely use soft text-based documents that interpret the hard data they narrate. Recent advances in computational methods for analyzing unstructured and soft text-based data at scale offer possibilities for understanding financial market behavior that could improve investments and market equity. A critical and ubiquitous form of soft data are earnings calls. Earnings calls are periodic (often quarterly) statements usually by CEOs who attempt to influence investors' expectations of a company's past and future performance. Here, we study the statistical relationship between earnings calls, company sales, stock performance, and analysts' recommendations. Our study covers a decade of observations with approximately 100,000 transcripts of earnings calls from 6,300 public companies from January 2010 to December 2019. In this study, we report three novel findings. First, the buy, sell and hold recommendations from professional analysts made prior to the earnings have low correlation with stock price movements after the earnings call. Second, using our graph neural network based method that processes the semantic features of earnings calls, we reliably and accurately predict stock price movements in five major areas of the economy. Third, the semantic features of transcripts are more predictive of stock price movements than sales and earnings per share, i.e., traditional hard data in most of the cases.

READ FULL TEXT
research
08/23/2020

Towards Earnings Call and Stock Price Movement

Earnings calls are hosted by management of public companies to discuss t...
research
06/07/2019

Modeling financial analysts' decision making via the pragmatics and semantics of earnings calls

Every fiscal quarter, companies hold earnings calls in which company exe...
research
06/24/2015

Leverage Financial News to Predict Stock Price Movements Using Word Embeddings and Deep Neural Networks

Financial news contains useful information on public companies and the m...
research
06/25/2022

Predicting Stock Price Movement after Disclosure of Corporate Annual Reports: A Case Study of 2021 China CSI 300 Stocks

In the current stock market, computer science and technology are more an...
research
06/23/2021

Stock Market Analysis with Text Data: A Review

Stock market movements are influenced by public and private information ...
research
08/11/2022

New drugs and stock market: how to predict pharma market reaction to clinical trial announcements

Pharmaceutical companies operate in a strictly regulated and highly risk...
research
05/22/2017

Predicting stock market movements using network science: An information theoretic approach

A stock market is considered as one of the highly complex systems, which...

Please sign up or login with your details

Forgot password? Click here to reset