Comparing the persistency of different frequencies of stock returns volatility in an emerging market: A case study of Pakistan


Amir Rafique1* and Kashif-Ur-Rehman2

This study aimed at comparing the variance structure of high (daily) and low (weekly, monthly) frequencies of data. By employing ARCH (1) and GARCH (1, 1) models, the study found that the intensity of the shocks was not equal for all the series. The study found that statistical properties of the three data series of returns were substantially different from one another and the persistence of conditional volatility was also different for the three series. The presence of persistency was more in the daily stock returns as compared to other data sets, which showed that the volatility models were sensitive to the frequencies of data series. In simple, the results revealed that the variance structure of high-frequency data were dissimilar from the low frequencies of data, and variance structure in the daily data were more linked with the stylized facts associated with stock returns volatility as compared to other data series.

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