The effects of aggregation on FIGARCH variances
نویسنده
چکیده
In this work we focus on the effects of aggregation on parameters estimation and Value-at-Risk computation if the data generator follow a FIGARCH model. We present a Montecarlo experiment which shows that the memory structure is affected. In a second simulation study we compare Value-at-Risk estimates obtained by high frequency and aggregated data. We verify that aggregated data have a better performance on a loss function approach while on a statistical based test analysis high frequency data are preferred.
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