Article ID Journal Published Year Pages File Type
974252 Physica A: Statistical Mechanics and its Applications 2015 6 Pages PDF
Abstract

•We used two models to describe the intraday pattern of inter-event times.•We connected estimators of autocorrelation of stationary and non-stationary process.•We proved that day seasonality extends the memory of process and its absolute value.

In this paper we propose a new approach to a well-known phenomena of intra-day activity pattern on the stock market. We suggest that seasonality of inter-transaction times has a more significant impact than intra-day pattern of volatility. Our aim is not to remove the intra-day pattern from the data but to describe its impact on autocorrelation function estimators. We obtain an exact, analytical formula relating estimators of the autocorrelation functions of non-stationary (seasonal) process to its stationary counterpart. Hence, we prove that the day seasonality of inter-transaction times extends the memory of the process. That is, autocorrelation of both, price returns and their absolute values, relaxation to zero is longer.

Related Topics
Physical Sciences and Engineering Mathematics Mathematical Physics
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