Volatility Forecasts

Methodology

Volatility forecasts in cryptocurrency derivatives utilize time-series econometrics to project future price variance by analyzing historical distribution patterns. These models incorporate autoregressive conditional heteroskedasticity to capture the tendency of market shocks to cluster over specific time horizons. By applying these statistical frameworks, traders estimate the expected standard deviation of underlying assets to price options accurately.