# What type of data we use to predict volatility of an asset with GARCH or ARCH models?

When we are trying to feed time-series data to a GARCH or ARCH model, what kind of data should we give the model?

• A: Absolute difference between daily prices over-time
• B: % of the difference between daily prices over-time
• C: B but squared (to take out the negative values)
• D: module of B (to take out the negative values)

• What I am saying is exactly correct. Moreover, the OP writes we are trying to feed time-series data to a GARCH or ARCH model, not to the conditional variance equation of a GARCH or ARCH model, and they are right in their choice. GARCH or ARCH model an entire conditional distribution of the random variable of interest, not just its conditional variance. You never feed squared returns, you feed raw returns. You cannot fit a GARCH or ARCH model for a time series $x_t$ using $x_t^2$ as inputs; rather, you use $x_t$ as inputs. Feb 12 at 7:07