quant-statistics

Cointegration analysis identifies long-run equilibrium relationships between financial time-series. This skill applies cointegration tests to ensure data stationarity and generate robust pair-trading signals while avoiding spurious regression pitfalls.

Regression diagnostics validate model integrity by checking for heteroskedasticity, autocorrelation, and multicollinearity in financial data. This skill applies these diagnostics to ensure robust factor research and prevent overfitting in trading strategies.

Yes, you can use statsmodels and arch with pandas and numpy for econometric testing. This skill requires these dependencies to execute unit-root tests, GARCH modeling, and regression diagnostics on financial time-series data for quantitative analysis.

The best way to identify long-run equilibrium relationships for pair-trading is through cointegration analysis and Granger causality tests. This skill performs these statistical tests to validate strategy assumptions and generate pair-trading signals.

Spurious regressions and overfitting in trading strategies occur when financial time-series data is non-stationary or model integrity is compromised. This skill prevents these pitfalls by applying rigorous statistical testing and regression diagnostics to validate assumptions.