Statistical Dynamics of Social Media Mood Data & Intra-Day Volatility (whitepaper)

 

BY TYNAN OVERSTREET

In this paper we provide empirical evidence that the HIVE-MIND System can predict an asset’s future price volatility. The HIVE-MIND scans PsychSignal’s Trader Mood Data for anomalous behavior from traders and investors expressed via social media.

Our research suggests a causal link between social anomalies and future stock price behavior.

We conducted several experiments to measure how effective the HIVE-MIND’s short term Social Anomaly Scores (“SAS”) can predict volatility. In addition, we measured the effectiveness of the medium term SAS in predicting daily volatility for a given asset. In our experiments we use three ETFs: (SPY, DIA and QQQ) as well as the constituents of the Dow 30. The results serve as guidance on how to intuitively and practically apply the HIVE to trading models and systems.

“Pre-Market anomalous sentiment activity leads increased market price volatility”