2019/12/05 by Patrick Chang, Chang, Patrick, Roger Bukuru +3 · 1 citation
Economics, Econometrics and Finance · #Computational Finance (q-fin.CP) #FOS: Economics and business #Statistical Finance (q-fin.ST) #Trading and Market Microstructure (q-fin.TR) #q-fin.CP #q-fin.ST #q-fin.TR
paper · pdf · doi:10.48550/arxiv.1912.02416
23 pages, 9 figures, 2 tables, 13 algorithms, link to our supporting R code: https://github.com/rogerbukuru/Exploring-The-Epps-Effect-R, Submitted to CSDA, corrects a figure error with regards to the Nyquist frequency
arxiv created 2020/02/16 · arxiv updated 2020/02/18
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.