High Frequency Analysis of Macro News Releases on the Foreign Exchange Market: A Survey of Literature

Wei Li; Micheal C.S. Wong; Jovan Cenev

doi:10.1016/j.bdr.2015.02.003

High Frequency Analysis of Macro News Releases on the Foreign Exchange Market: A Survey of Literature

Wei Li^*, Micheal C.S. Wong, Jovan Cenev

^*Corresponding author for this work

Department of Economics and Finance

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

19 Citations (Scopus)

Abstract

Most previous literature focuses on proving market impacts of macro news and price discovery process of the FX market. In general, the literature is divided into two camps. The first one attempts to explain directions of exchange-rate changes (the first moments). The second one attempts to explain exchange rate volatility (the second moments). There are many studies addressing the first camp of research, while there is a limited number of studies addressing the second camp of research. In the future, researchers may further investigate the following issues regarding the release of macro news: (a) their impacts on FX volatility; (b) their impacts on FX derivatives; (c) profitability of trading strategies arising from news releases; (d) price patterns associated with selected news announcements, non-scheduled news and selected headline news; and (e) machine learning on the impacts with advanced computer technologies.

Original language	English
Pages (from-to)	33-48
Journal	Big Data Research
Volume	2
Issue number	1
Online published	18 Feb 2015
DOIs	https://doi.org/10.1016/j.bdr.2015.02.003
Publication status	Published - Mar 2015

Research Keywords

Foreign currency
High frequency analysis
Macroeconomic announcements

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title = "High Frequency Analysis of Macro News Releases on the Foreign Exchange Market: A Survey of Literature",

abstract = "Most previous literature focuses on proving market impacts of macro news and price discovery process of the FX market. In general, the literature is divided into two camps. The first one attempts to explain directions of exchange-rate changes (the first moments). The second one attempts to explain exchange rate volatility (the second moments). There are many studies addressing the first camp of research, while there is a limited number of studies addressing the second camp of research. In the future, researchers may further investigate the following issues regarding the release of macro news: (a) their impacts on FX volatility; (b) their impacts on FX derivatives; (c) profitability of trading strategies arising from news releases; (d) price patterns associated with selected news announcements, non-scheduled news and selected headline news; and (e) machine learning on the impacts with advanced computer technologies.",

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AB - Most previous literature focuses on proving market impacts of macro news and price discovery process of the FX market. In general, the literature is divided into two camps. The first one attempts to explain directions of exchange-rate changes (the first moments). The second one attempts to explain exchange rate volatility (the second moments). There are many studies addressing the first camp of research, while there is a limited number of studies addressing the second camp of research. In the future, researchers may further investigate the following issues regarding the release of macro news: (a) their impacts on FX volatility; (b) their impacts on FX derivatives; (c) profitability of trading strategies arising from news releases; (d) price patterns associated with selected news announcements, non-scheduled news and selected headline news; and (e) machine learning on the impacts with advanced computer technologies.

KW - Foreign currency

KW - High frequency analysis

KW - Macroeconomic announcements

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High Frequency Analysis of Macro News Releases on the Foreign Exchange Market: A Survey of Literature

Abstract

Research Keywords

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Corrigendum to “High Frequency Analysis of Macro News Releases on the Foreign Exchange Market A Survey of Literature” [Big Data Res. 2 (1) (2015) 33–48]

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