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Technical analysis, spread trading, and data snooping control
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dc.contributor.author | Psaradellis, Ioannis | |
dc.contributor.author | Laws, Jason | |
dc.contributor.author | Pantelous, Athanasios | |
dc.contributor.author | Sermpinis, Georgios | |
dc.date.accessioned | 2023-11-24T00:35:17Z | |
dc.date.available | 2023-11-24T00:35:17Z | |
dc.date.issued | 2023-01-01 | |
dc.identifier | 276738484 | |
dc.identifier | bd79cb04-e652-4674-a2dc-e82c3dae8e12 | |
dc.identifier | 85119923059 | |
dc.identifier | 000904903100011 | |
dc.identifier.citation | Psaradellis , I , Laws , J , Pantelous , A & Sermpinis , G 2023 , ' Technical analysis, spread trading, and data snooping control ' , International Journal of Forecasting , vol. 39 , no. 1 , pp. 178-191 . https://doi.org/10.1016/j.ijforecast.2021.10.002 | en |
dc.identifier.issn | 0169-2070 | |
dc.identifier.other | ORCID: /0000-0002-7628-8931/work/103865760 | |
dc.identifier.uri | https://hdl.handle.net/10023/28760 | |
dc.description.abstract | This paper utilizes a large universe of 18,410 technical trading rules (TTRs) and adopts a technique that controls for false discoveries to evaluate the performance of frequently traded spreads using daily data over 1990–2016. For the first time, the paper applies an excessive out-of-sample analysis in different subperiods across all TTRs examined. For commodity spreads, the evidence of significant predictability appears much stronger compared to equity and currency spreads. Out-of-sample performance of portfolios of significant rules typically exceeds transaction cost estimates and generates a Sharpe ratio of 3.67 in 2016. In general, we reject previous studies’ evidence of a uniformly monotonic downward trend in the selection of predictive TTRs over 1990–2016. | |
dc.format.extent | 14 | |
dc.format.extent | 418910 | |
dc.language.iso | eng | |
dc.relation.ispartof | International Journal of Forecasting | en |
dc.subject | Technical trading rules | en |
dc.subject | Spread trading predictability | en |
dc.subject | False discovery rate | en |
dc.subject | Bootstrap test | en |
dc.subject | Portfolio performance | en |
dc.subject | HD28 Management. Industrial Management | en |
dc.subject | 3rd-DAS | en |
dc.subject | MCC | en |
dc.subject.lcc | HD28 | en |
dc.title | Technical analysis, spread trading, and data snooping control | en |
dc.type | Journal article | en |
dc.contributor.institution | University of St Andrews. School of Economics and Finance | en |
dc.contributor.institution | University of St Andrews. Finance (Business School) | en |
dc.identifier.doi | https://doi.org/10.1016/j.ijforecast.2021.10.002 | |
dc.description.status | Peer reviewed | en |
dc.date.embargoedUntil | 2023-11-24 |
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