Context Analytics (CA) is proud to announce an expansion in social sentiment global security coverage to include Australian securities (ASX). Similar to other foreign asset classes CA covers, the ASX dataset will retrieve textual data from Twitter messages and generate sentiment scores using our proprietary Natural Language Processing (NLP) technology. These sentiment scores are actionable factors that reflect both the tone and volume of conversations at the security level. One of CA’s flagship products, the S-Factor feed, features the S-Score—a metric that quantifies the positivity or negativity of sentiment for each security.
The ASX dataset tracks over 800 securities with roughly 125 securities generating a daily signal. The S-Score, one of many factors, is a Z-Score that detects sentiment from Twitter. A S-Score greater than 2 indicates that the conversation over the last 24 hours is 2 standard deviations more positive than the previous 20 days, suggesting a bullish outlook for the stock price. Conversely, a more negative S-Score reflects negative sentiment and a bearish outlook.
To demonstrate the relationship between S-Score and future price returns, we grouped securities into daily quintiles and plot the cumulative price return. Five minutes before market close, at 3:55pm AET, we grab all securities with an S-Score published. These securities are bucketed into daily quintiles based on the value of their S-Score. Each day the highest 20% of S-Scores are grouped in quintile 5, the next highest 20% in quintile 4, and so on until the bottom 20% of S-Score are in quintile 1. We then calculate the Close-to-Close return of each individual stock, equally average the return by quintile and day to generate a portfolio of cumulative returns by quintile. Below is the plot of the quintiles’ cumulative returns sine 2021 on Twitter sentiment data.