Garch
- 지표
- Giorgi Abuladze
- 버전: 1.0
GARCH(1,1) Volatility Estimator
This indicator provides a computational implementation of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model of order (1,1). It is designed to estimate the current volatility of a financial asset by factoring in both past shocks and previous variance estimates. Unlike standard moving averages, this model accounts for "volatility clustering"—the phenomenon where large price changes tend to be followed by further large changes. It's basically the better ATR, more adaptive and precise.
Technical Explanation of GARCH(1,1)
The GARCH(1,1) model operates through a recursive variance process.
-
Omega: Derived via variance targeting, ensuring the process reverts to the long-term observed variance .
-
Alpha: Represents the "shock" impact, or how much recent market news (squared returns) influences immediate volatility .
-
Beta: Represents volatility persistence, indicating how much the previous period's volatility influences the current period .
The indicator initializes using a rolling variance of squared returns (defined by the lookback input) and defaults to a cumulative mean if insufficient bars exist . The resulting variance is then floored at a nominal value to prevent numerical drift before being square-rooted to produce a volatility percentage .
Simplified Conceptual Overview
In simpler terms, this indicator tracks how "nervous" or active a market is:
-
How it works: Think of it as a weighted memory of the market. If there was a big price swing yesterday (the "shock"), it increases the volatility estimate today. However, it also remembers how volatile the market was yesterday generally (the "persistence") and blends these two factors to predict today's volatility.
-
Why it is useful: Instead of just looking at a flat average of price changes, this model adapts quickly to sudden market events while maintaining a smoother trend based on recent history.
-
Indicators: The histogram plots daily volatility . If the volatility is higher than its 50-period average, the bar turns red; if it is lower, it turns teal .
Input Parameters & Usage
The indicator is configured to be non-intrusive and provides a live data table on the chart.
| Input | Description |
| Alpha | Measures the reaction to recent price shocks . |
| Beta | Measures how long volatility persists over time . |
| Variance Lookback | The number of bars used to establish the initial variance baseline . |
| Annualize | If enabled, converts daily volatility to an annualized percentage using the Trading Days per Year input . |
Usage Note: The indicator includes an automated alert mechanism: if the current volatility exceeds 1.5 times the mean of the 50-period average, a background highlight and a visual alert in the info table are triggered to denote high-volatility conditions .
