Heteroskedasticity happens when the standard deviations of a predicted variable, monitored over different values of an independent variable or as related to prior time periods, are non-constant. With heteroskedasticity, the tell-tale sign upon visual inspection of the residual errors is that they will tend to fan out over time, as depicted in the image below.Heteroskedasticity often arises in two forms: conditional and unconditional. Conditional heteroskedasticity identifies nonconstant volatility related to the prior period's volatility. Unconditional heteroskedasticity refers to general structural changes in volatility that are not related to prior period volatility. Unconditional heteroskedasticity is used when future periods of high and low volatility can be identified.Become a supporter of this podcast: https://www.spreaker.com/podcast/investment-terms--4432332/support.

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