Analysis Flows Reference

Framework: alphaswarm_docs/analysis-framework.md · UI: alphaswarm_docs/analysis-lab.md.

Every flow in the registry. Each flow is identified by a namespaced name (namespace.flow), declares a Pydantic params model, and returns a FlowResult with metrics / rows / chart / optional arrow_table for Iceberg persistence.

GET /analysis/flows lists every entry with the JSON-schema body derived from the params model — the lab UI auto-renders forms from this surface.

profiling.*

Name	Label	Notes
profiling.describe	Column profile	Wraps alphaswarm.data.profiling.compute_profile
profiling.dtypes	Dtypes	Per-column dtype + memory footprint
profiling.null_audit	Null audit	Null counts + null fractions
profiling.topk	Top-K values	Most-frequent values + share

distribution.*

Name	Label	Notes
distribution.descriptive_stats	Descriptive stats	Mean / median / std / skew / kurt / IQR / MAD / quantiles
distribution.histogram	Histogram	Equal-width bins + Plotly chart
distribution.ecdf	Empirical CDF	Sorted-value ECDF (down-sampled to max_points)
distribution.qq_plot_points	Q-Q plot points	Slope/intercept fit vs. norm/t/uniform/expon
distribution.shapiro_wilk	Shapiro-Wilk	Normality test (capped at 5000 samples)
distribution.jarque_bera	Jarque-Bera	Skew + kurt goodness-of-fit
distribution.kolmogorov_smirnov	K-S	One-sample vs reference dist (norm / t / uniform / expon / lognorm)

outlier.*

Name	Label	Notes
outlier.zscore	Z-score	Robust (median/MAD) or classical
outlier.iqr	IQR fences	Tukey [Q1 - kIQR, Q3 + kIQR]
outlier.iforest	Isolation Forest	sklearn
outlier.dbscan	DBSCAN	Density-based; -1 is noise
outlier.lof	LOF	sklearn LocalOutlierFactor
outlier.ecod	ECOD	PyOD; falls back to z-score
outlier.pulse_vs_step	Pulse vs Step	Distinguish transient pulses from level shifts

imputation.*

Name	Label	Notes
imputation.ffill_bfill	Forward / backward fill	Default ffill_then_bfill
imputation.linear	Linear interpolation	pandas axis=0
imputation.spline	Cubic spline	pandas spline (order configurable)
imputation.knn	KNN imputer	sklearn KNNImputer
imputation.mice	MICE (IterativeImputer)	sklearn IterativeImputer

regression.*

Name	Label	Notes
regression.ols_diagnostics	OLS diagnostics	Coefs + SE + t / p + Durbin-Watson + AIC / BIC
regression.white_test	White's test	Heteroskedasticity (general form)
regression.breusch_pagan	Breusch-Pagan	Heteroskedasticity vs regressors
regression.vif	VIF	Variance Inflation Factors per regressor

time_series.*

Name	Label	Notes
time_series.stl	STL decomposition	Trend / seasonal / residual
time_series.adf	Augmented Dickey-Fuller	H0 = unit root
time_series.kpss	KPSS	H0 = stationary (ADF complement)
time_series.acf_pacf	ACF / PACF	Auto- and partial-autocorrelation series
time_series.garch	GARCH(p, q)	Volatility model + horizon variance forecast
time_series.change_point	Change-point	ruptures.KernelCPD with rbf kernel
time_series.granger_causality	Granger causality	Up to max_lag
time_series.cointegration	Engle-Granger	Pair cointegration
time_series.spectral_fft	Spectral (FFT)	Real FFT magnitude + power spectrum
time_series.spectral_wavelet	Continuous wavelet transform	PyWavelets (optional)
time_series.hurst_exponent	Hurst exponent	Long-range dependence
time_series.theil_sen	Theil-Sen slope	Robust median-of-pairwise-slopes

derivatives.*

Name	Label	Notes
derivatives.bsm	Black-Scholes-Merton	Closed-form European price + Greeks
derivatives.greeks_surface	Greeks surface	Δ/Γ/ν/Θ/ρ across strikes × expiries
derivatives.implied_volatility	Implied volatility (Brent)	Recover σ from a market quote
derivatives.monte_carlo_european	MC European option	Vectorised GBM; opt-in CUDA via cupy
derivatives.monte_carlo_barrier	MC barrier option	Knock-in / knock-out variants
derivatives.monte_carlo_asian	MC Asian option	Arithmetic / geometric averaging
derivatives.sabr_smile	SABR smile (Hagan)	Hagan-Kumar-Lesniewski-Woodward 2002
derivatives.bachelier	Bachelier (normal model)	Wraps alphaswarm.options.normal_model

portfolio.*

Name	Label	Notes
portfolio.markowitz_efficient_frontier	Efficient frontier	cvxpy if available, numpy-only fallback
portfolio.ledoit_wolf_shrinkage	Ledoit-Wolf covariance	Stabilised covariance matrix
portfolio.fama_french_5_rolling	FF5 rolling betas	Rolling-window OLS on Mkt-RF / SMB / HML / RMW / CMA
portfolio.risk_parity	Risk parity	Equal-risk-contribution weights (Spinu 2013)

factors.*

Name	Label	Notes
factors.evaluate	Factor evaluation	Wraps alphaswarm.data.factors.evaluate_factor (IC + quantile spread + turnover)

microstructure.*

Name	Label	Notes
microstructure.realised_volatility	Realised volatility (OHLC)	Close-to-close / Parkinson / GK / RS / YZ
microstructure.order_book_imbalance	Order-book imbalance	Top-of-book
microstructure.vpin	VPIN	Wraps alphaswarm.data.microstructure.vpin

Optional dependencies

Flows tag their optional deps (optional_dependencies field on the descriptor). Missing extras raise a friendly RuntimeError("install extra X") instead of crashing the catalog.

Dep	Used by
scikit-learn	outlier.{iforest,dbscan,lof}, imputation.{knn,mice}, portfolio.ledoit_wolf_shrinkage
statsmodels	regression.*, time_series.{adf,kpss,acf_pacf,granger_causality,cointegration,stl}
arch	time_series.garch
ruptures	time_series.change_point
pywavelets	time_series.spectral_wavelet
pyod	outlier.ecod (falls back to z-score)
cvxpy	portfolio.markowitz_efficient_frontier (falls back to numpy projection)
cupy	derivatives.monte_carlo_* (opt-in GPU acceleration)