Overnight and seasonality effects or analysis of sentiment are favorite themes in quantitative academic research. Novel and very recent research from Baoqing Gan, Vitali Alexeev, and Danny Yeung (August 2022) presents us with an opportunity to discover new findings related to both these phenomena. The main takeaway is that the accumulated sentiment from the overnight non-trading period can predict the next period’s intraday stock return.
The study is an example of the extraction of alpha signal from ‘alternative data‘ set – minute-to-minute overnight sentiment scores based on textual analysis of over two million blogs, internet message boards, and social and news media sites. Authors investigate subsequent daily price action in DJ 30 stocks. Overall, social media have a bigger possibility to change investors’ moods than news outlets. Most returns come from influence during the first minutes of opening, most likely through orders submitted at the pre-opening sessions. Results are consistent with findings from behavioral finance and display various psychological biases of traders.
The paper shows how people’s opinions during the time when US markets are not open: from the close of US markets at 4 pm to 9:30 am, influence computer’s algorithms afterward. Being aware of those implications can allow investors and traders to make the right decisions in the morning during their working session and step into the day on the right foot.
Authors: Baoqing Gan, Vitali Alexeev, and Danny Yeung
Title: Moods on the Move: Overnight Sentiment and the Intraday Return Dynamics
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