  We revisit and demonstrate the Epps effect using two well-known
non-parametric covariance estimators; the Malliavin and Mancino (MM), and
Hayashi and Yoshida (HY) estimators. We show the existence of the Epps effect
in the top 10 stocks from the Johannesburg Stock Exchange (JSE) by various
methods of aggregating Trade and Quote (TAQ) data. Concretely, we compare
calendar time sampling with two volume time sampling methods: asset intrinsic
volume time averaging, and volume time averaging synchronised in volume time
across assets relative to the least and most liquid asset clocks. We reaffirm
the argument made in much of the literature that the MM estimator is more
representative of trade time reality because it does not over-estimate
short-term correlations in an asynchronous event driven world. We confirm well
known market phenomenology with the aim of providing some standardised R based
simulation tools.
