The Short Squeeze Model dataset is a multifactor model, updated daily, and designed to predict short squeeze events. The model uses proprietary transaction-level information of short transactions and event indicators to identify catalysts that will make a stock a more likely candidate for a squeeze event.

The model is based on a hypothesis that squeezes are more likely to occur with stocks where short sellers are experiencing capital constraints (actual or potential losses). The model helps to identify those names at risk of a squeeze, improve the accuracy of short interest signals, and provide deeper insight into short positions.

The dataset includes:

• Short Loan Transaction Factors: Computed globally for all stocks based on proprietary transaction information
• P&L Bins: Distribution of profitability of stock positions out on loan, updated daily
• Short Squeeze Model Score: A combination of capital constraints variable from short loan transaction factors and event-based data from trade activity and news to assign a likelihood rank for squeeze event
• Granular information on capital constraints and market sentiment