I'm excited to share with you a Pine Script™ that I developed to analyze GARCH (Generalized Autoregressive Conditional Heteroskedasticity) volatility. This script allows you to calculate and plot GARCH volatility on TradingView. Let's see together how it works!
Introduction
Volatility is a key concept in finance that measures the variation in prices of a financial asset. The GARCH model is a statistical method that predicts future volatility based on past volatilities and prediction residuals (errors).
Indicator settings
We define several parameters for our indicator:
length: The period used for the calculations, default 20.
p: The order of the delay for the GARCH model.
q: The degree of the moving average for the GARCH model.
cluster_value: A threshold value used to color the graph.
Calculation of logarithmic returns
We calculate logarithmic returns to capture price changes:
Initializing arrays
We initialize arrays to store residuals and volatilities:
We add the new logarithmic returns to the tables and keep their size constant:
We then calculate the mean and variance of the residuals:
We update the volatility table with the new value:
GARCH volatility is calculated from accumulated data:
Plot GARCH volatility
We finally plot the GARCH volatility on the chart and add horizontal lines for easier visual analysis:
colorGarch: Determines the fill color based on the comparison between garchVolatility and cluster_value.
Using the script in your trading
Incorporating this Pine Script™ into your trading strategy can provide you with a better understanding of market volatility and help you make more informed decisions. Here are some ways to use this script:
Identification of periods of high volatility:
When the GARCH volatility is greater than the cluster value (cluster_value), it indicates a period of high volatility. Traders can use this information to avoid taking large positions or to adjust their risk management strategies.
Anticipation of price movements:
An increase in volatility can often precede significant price movements. By monitoring GARCH volatility spikes, traders can prepare for potential market reversals or accelerations.
Optimization of entry and exit points:
By using GARCH volatility, traders can better identify favorable times to enter or exit a position. For example, entering a position when volatility begins to decrease after a peak can be an effective strategy.
Adjustment of stops and objectives:
Since volatility is an indicator of the magnitude of price fluctuations, traders can adjust their stop-loss and take-profit orders accordingly. Periods of high volatility may require wider stops to avoid being exited from a position prematurely.
That's it for the detailed explanation of this Pine Script™ script. Don’t hesitate to use it, adapt it to your needs and share your feedback! Happy analysis and trading everyone!
Introduction
Volatility is a key concept in finance that measures the variation in prices of a financial asset. The GARCH model is a statistical method that predicts future volatility based on past volatilities and prediction residuals (errors).
Indicator settings
We define several parameters for our indicator:
length = input.int(20, title="Length")
p = input.int(1, title="Lag order (p)")
q = input.int(1, title="Degree of moving average (q)")
cluster_value = input(0.2,title="cluster value")length: The period used for the calculations, default 20.
p: The order of the delay for the GARCH model.
q: The degree of the moving average for the GARCH model.
cluster_value: A threshold value used to color the graph.
Calculation of logarithmic returns
We calculate logarithmic returns to capture price changes:
logReturns = math.log(close) - math.log(close[1])Initializing arrays
We initialize arrays to store residuals and volatilities:
var float[] residuals = array.new_float(length, 0)
var float[] volatilities = array.new_float(length, 0)We add the new logarithmic returns to the tables and keep their size constant:
array.unshift(residuals, logReturns)
if (array.size(residuals) > length)
array.pop(residuals)We then calculate the mean and variance of the residuals:
meanResidual = array.avg(residuals)
varianceResidual = array.stdev(residuals, meanResidual)
volatility = math.sqrt(varianceResidual)We update the volatility table with the new value:
array.unshift(volatilities, volatility)
if (array.size(volatilities) > length)
array.pop(volatilities)GARCH volatility is calculated from accumulated data:
var float garchVolatility = na
if (array.size(volatilities) >= length and array.size(residuals) >= length)
alpha = 0.1 // Alpha coefficient
beta = 0.85 // Beta coefficient
omega = 0.01 // Omega constant
sumVolatility = 0.0
for i = 0 to p-1
sumVolatility := sumVolatility + beta * math.pow(array.get(volatilities, i), 2)
sumResiduals = 0.0
for j = 0 to q-1
sumResiduals := sumResiduals + alpha * math.pow(array.get(residuals, j), 2)
garchVolatility := math.sqrt(omega + sumVolatility + sumResiduals)Plot GARCH volatility
We finally plot the GARCH volatility on the chart and add horizontal lines for easier visual analysis:
plt = plot(garchVolatility, title="GARCH Volatility", color=color.rgb(33, 149, 243, 100))
h1 = hline(0.1)
h2 = plot(cluster_value)
h3 = hline(0.3)
colorGarch = garchVolatility > cluster_value ? color.red: color.green
fill(plt, h2, color = colorGarch)colorGarch: Determines the fill color based on the comparison between garchVolatility and cluster_value.
Using the script in your trading
Incorporating this Pine Script™ into your trading strategy can provide you with a better understanding of market volatility and help you make more informed decisions. Here are some ways to use this script:
Identification of periods of high volatility:
When the GARCH volatility is greater than the cluster value (cluster_value), it indicates a period of high volatility. Traders can use this information to avoid taking large positions or to adjust their risk management strategies.
Anticipation of price movements:
An increase in volatility can often precede significant price movements. By monitoring GARCH volatility spikes, traders can prepare for potential market reversals or accelerations.
Optimization of entry and exit points:
By using GARCH volatility, traders can better identify favorable times to enter or exit a position. For example, entering a position when volatility begins to decrease after a peak can be an effective strategy.
Adjustment of stops and objectives:
Since volatility is an indicator of the magnitude of price fluctuations, traders can adjust their stop-loss and take-profit orders accordingly. Periods of high volatility may require wider stops to avoid being exited from a position prematurely.
That's it for the detailed explanation of this Pine Script™ script. Don’t hesitate to use it, adapt it to your needs and share your feedback! Happy analysis and trading everyone!