Multi-Asset Lagged Price Adjustment Model for NYSE Stocks

A multi-asset price formation model introduced by Giuseppe Buccheri, motivated by empirical evidence of high-frequency lead-lag effects and cross-asset linkages. The model's econometric inference provides a unified statistical test for lead-lag correlations and separate estimation of contemporaneous and lagged dependencies. An application to a set of NYSE stocks provides empirical evidence for the existence of a multi-asset price formation mechanism.

Use Cases

• Testing for lead-lag correlations in latent price processes based on the described statistical test.
• Estimating contemporaneous and lagged dependencies between assets as outlined in the model.
• Calculating an integrated covariance estimator robust to microstructure noise, asynchronous trading, and lead-lag effects.
• Simulating and comparing price formation mechanisms to recover true lead-lag structures.

Strengths

• The model provides an unbiased estimator of integrated covariance robust to microstructure noise, asynchronous trading, and lead-lag dependencies.
• An extensive simulation study was conducted to compare the proposed estimator to alternative approaches.
• Empirical application provides evidence from a set of NYSE stocks.

Limitations

• Row count, column names, and sample data are unavailable, limiting suitability assessment.
• The dataset's specific time range and update frequency are unknown.
• Column-level documentation is absent; field semantics must be inferred from the academic description.

Provenance

Source

Giuseppe Buccheri via paperswithcode.

Collection Method

Likely contains simulated data from an extensive study and empirical application to NYSE stocks.

Geography

Application involves NYSE stocks, suggesting a U.S. financial market focus.