Conditional heteroscedasticity refers to a situation in time series analysis where the variance of the error terms varies depending on the information available at a given time. This phenomenon is particularly important in financial modeling, as it indicates that volatility is not constant over time but rather depends on past information or events, leading to periods of higher or lower variability.
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