Journal article
Using conditional probability to identify trends in intra-day high-frequency equity pricing
Physica A, Vol.392(24), pp.6169-6188
12/15/2013
DOI: 10.1016/j.physa.2013.08.003
Abstract
By examining the conditional probabilities of price movements in a popular US stock over different high-frequency intra-day timespans, varying levels of trend predictability are identified. This study demonstrates the existence of predictable short-term trends in the market; understanding the probability of price movement can be useful to high-frequency traders. Price movement was examined in trade-by-trade (tick) data along with temporal timespans between 1 s to 30 min for 52 one-week periods for one highly-traded stock. We hypothesize that much of the initial predictability of trade-by-trade (tick) data is due to traditional market dynamics, or the bouncing of the price between the stock's bid and ask. Only after timespans of between 5 to 10 s does this cease to explain the predictability; after this timespan, two consecutive movements in the same direction occur with higher probability than that of movements in the opposite direction. This pattern holds up to a one-minute interval, after which the strength of the pattern weakens. (C) 2013 Elsevier B.V. All rights reserved.
Details
- Title: Subtitle
- Using conditional probability to identify trends in intra-day high-frequency equity pricing
- Creators
- Michael Rechenthin - University of IowaW. Nick Street - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Physica A, Vol.392(24), pp.6169-6188
- Publisher
- Elsevier
- DOI
- 10.1016/j.physa.2013.08.003
- ISSN
- 0378-4371
- eISSN
- 1873-2119
- Number of pages
- 20
- Language
- English
- Date published
- 12/15/2013
- Academic Unit
- Bus Admin College; Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984380518302771
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