Squeeze Labs / Research

Research

Current studies and experiments using Squeeze’s datasets and analysis tools. The directions below describe planned work, with results and methodology on each study’s page.

Short interest & short squeezes

How does reported short positioning relate to volatility and subsequent price extremes?

Explore short-interest research

Current work

A descriptive event study of the tracked universe, with days-to-cover and prior-volatility cohorts. Linked stock charts place adjusted prices, volatility, and short-interest reports on a shared timeline.

Planned directions

Improve historical float coverage, examine reporting delays, and test whether relationships persist across liquidity groups and market regimes. Separate short-covering explanations from other causes of large price moves.

Report dates are correct; exact publication timestamps are currently unknown. Current results describe associations rather than a tradable signal.

Filing & news impact · CatalystBERT-v1

Can filing language help identify a significant subsequent market reaction?

View CatalystBERT-v1

Current work

The current ModernBERT-large baseline uses SEC filings only, with return-based labels across multiple horizons. An earlier news-only experiment is documented separately. The study page documents input and output tensors, the connection to returns, methodology, and evaluation results.

Planned directions

Run SEC text-only and structured-only ablations, compare longer and multiple passages, and evaluate results by filing form. Revisit direction targets and timing before attempting a mixed news-and-SEC experiment.

The current v1 baseline uses SEC filings; combined inputs mean text plus structured context. Its evaluation does not establish a profitable directional trading strategy.

Strategy backtesting

How do widely used technical strategies behave across a broad universe?

Inspect strategy experiments

Current work

MACD, RSI, and TTM Squeeze backtests across tracked symbols. Interactive distributions and individual account histories expose returns, drawdowns, and other performance metrics.

Planned directions

Compare parameter sensitivity and stock characteristics, then evaluate transaction costs and performance outside the parameter-selection period. Use these experiments as baselines for more targeted research.

Default parameters provide a common comparison. Individual stocks may perform better with targeted parameters; tuning requires separate validation.