Keynote speaker

Centre for Computational Finance and Economic Agents, University of Essex, UK

Edward Tsang

Title: Why is Directional Change Good For High-Frequency Data

Abstract:
How one represents knowledge determines what one could reason about. In this talk I shall examine how the way that we collect data in a market impacts our analysis.

Time Series (TS) records transactions in a market at fixed intervals. Directional Change (DC) is an alternative way to record transactions: it only records transactions that represent significant price changes in the opposite direction in a trend, where “significance” is observer-defined. In this talk, I shall argue that DC is better than TS for handling tick-to-tick data. First, I shall explain that DC records true transactions in the market, whereas TS only records approximations. Then I shall argue that DC enables one to feel the pulse of the market better than TS: by tracking the market transaction by transaction under DC, we could potentially detect events such as crashes, directional changes or regime changes in the market, which may not be possible under TS.

Biography:
Edward Tsang is an emeritus professor at the University of Essex. He co-founded the Centre for Computational Finance and Economic Agents (CCFEA) in 2002, and took up its Directorship from 1st August 2009 to 31st December 2016. He retired from the University of Essex on 1st November 2017 but remains active in research and consultancy. He has taught freelance at Traders Training Company, King’s College (London), Queen Mary College (London), and University of Hong Kong.