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Does high frequency trading affect technical analysis and market efficiency? And if so, how?

Manahov, Viktor; Hudson, Robert; Gebka, Bartosz

Authors

Viktor Manahov

Robert Hudson

Bartosz Gebka



Abstract

In this paper we investigate how high frequency trading affects technical analysis and market efficiency in the foreign exchange (FX) market by using a special adaptive form of the Strongly Typed Genetic Programming (STGP)-based learning algorithm. We use this approach for real one-minute high frequency data of the most traded currency pairs worldwide: EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/C HF, and USD/CAD. The STGP performance is compared with that of parametric and non-parametric models and validated by two formal empirical tests. We perform in-sample and out-of-sample comparisons between all models on the basis of forecast performance and investment return. Furthermore, our paper shows the relative strength of these models with respect to the actual trading profit generated by their forecasts. Empirical experiments suggest that the STGP forecasting technique significantly outperforms the traditional econometric models. We find evidence that the excess returns are both statistically and economically significant, even when appropriate transaction costs are taken into account. We also find evidence that HFT has a beneficial role in the price discovery process.

Citation

Manahov, V., Hudson, R., & Gebka, B. (2014). Does high frequency trading affect technical analysis and market efficiency? And if so, how?. Journal of International Financial Markets, Institutions and Money, 28, 131-157. https://doi.org/10.1016/j.intfin.2013.11.002

Journal Article Type Article
Acceptance Date Nov 12, 2013
Online Publication Date Nov 21, 2013
Publication Date 2014-01
Deposit Date Jun 8, 2022
Journal Journal of International Financial Markets, Institutions and Money
Print ISSN 1042-4431
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 28
Pages 131-157
DOI https://doi.org/10.1016/j.intfin.2013.11.002
Public URL https://hull-repository.worktribe.com/output/524135