vol_* tool: GARCH, GJR, TARCH, EGARCH, APARCH, FIGARCH, HARCH, MIDAS hyperbolic, EWMA and RiskMetrics 2006 variance with constant, zero, AR, HAR, regression and volatility-in-mean mean equations and normal, Student t, skewed t or GED errors; analytic, simulated and bootstrap forecasts with Value-at-Risk and expected shortfall; rolling and expanding re-estimation backtests and scenario forecasts; unit-root, variance-ratio and cointegration tests with cointegrating vectors (DOLS, FMOLS, CCR); bootstrap confidence intervals; forecast comparison (SPA, StepM, model confidence set) and kernel long-run covariances. It runs on Fincept’s servers; your agent sends numbers or data references and gets back a result envelope with tables and charts.
Fincept Volatility tools are free. They count toward the rate limit only; a
$fincept reference inside a call is charged like a direct call to that tool.Modules
Tools are grouped in modules. Each module is a toolset namedvol_<module>, so you can list it or search within it. The Fincept Volatility reference lists every module and tool.
vol_catalog returns the live list of modules and tools from inside your agent.
Inputs
Unit-root and cointegration tools take levels in
values or data; transform: "log" turns prices into log prices and "log_diff" into log returns. Models are fitted on percent returns, and volatility, VaR and expected shortfall come back in percent.
Limits
A computation that runs past its time limit answers
timeout; a busy engine answers busy and the call can be retried a few seconds later.
Outputs
vol_garch returns the parameters with robust standard errors, persistence, half-life and unconditional volatility, ARCH-LM, Ljung-Box and Jarque-Bera diagnostics, the conditional volatility and standardized residuals as series with charts, and the forecast of mean and volatility with a fan chart and per-step VaR and expected shortfall. vol_rolling_forecast returns every out-of-sample forecast with its VaR hits, the hit rates and squared-error and QLIKE losses that vol_spa and vol_mcs take as losses. Tests return statistics, p-values, critical values and a verdict; bootstrap tools return estimates with their bounds, replicate distributions and fans of cumulative return.
Example
Prompt
GARCH volatility, finds vol_garch and vol_rolling_forecast, and passes the closes as a $fincept reference to market_get_candles (candles.close) with units: "prices_log".