> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fincept.in/llms.txt
> Use this file to discover all available pages before exploring further.

# Volatility models

> GARCH-family conditional volatility models (GARCH, GJR, TARCH, EGARCH, APARCH, FIGARCH, HARCH, MIDAS hyperbolic, EWMA, RiskMetrics 2006, fixed variance) with constant, zero, AR, HAR, regression or volatility-in-mean means and normal, Student t, skewed t or GED errors: estimation, diagnostics, forecasts with VaR and expected shortfall, ARCH-effect tests, simulation and the error distributions.

Toolset `vol_models`: 4 tools.

| Tool | What it does | Notes |
| - | - | - |
| `vol_garch` | Fits a conditional volatility model (default constant mean, GARCH(1,1), normal errors; any mean, volatility process and distribution through model) and forecasts it. | |
| `vol_arch_effects` | Tests a return series for ARCH effects (volatility clustering) before any model is fitted: Engle's ARCH-LM test and the Ljung-Box (McLeod-Li) test on squared returns at each lag. | |
| `vol_simulate` | Simulates returns from a volatility model (any mean, process and distribution) at given parameters, or at parameters fitted to returns. | |
| `vol_distribution` | Evaluates the standardized error distributions of the volatility models (normal, Student t, Hansen skewed t, generalized error) at given shape parameters: quantiles (the VaR multipliers), CDF, moments, lower partial moments (expected-shortfall building blocks), random draws or the log-likelihood of values. | |

Inputs, limits and outputs are described in [Fincept Volatility](/guides/fincept-volatility). Full schemas: `fincept_describe_tool`.


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