IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v52y2020ics1062940820300784.html
   My bibliography  Save this article

News will tell: Forecasting foreign exchange rates based on news story events in the economy calendar

Author

Listed:
  • Naderi Semiromi, Hamed
  • Lessmann, Stefan
  • Peters, Wiebke

Abstract

The paper proposes a novel approach to predict intraday directional-movements of currency-pairs in the foreign exchange market based on news story events in the economy calendar. Prior work on using textual data for forecasting foreign exchange market developments does not consider economy calendar events. We consider a rich set of text analytics methods to extract information from news story events and propose a novel sentiment dictionary for the foreign exchange market. The paper shows how news events and corresponding news stories provide valuable information to increase forecast accuracy and inform trading decisions. More specifically, using textual data together with technical indicators as inputs to different machine learning models reveals that the accuracy of market predictions shortly after the release of news is substantially higher than in other periods, which suggests the feasibility of news-based trading. Furthermore, empirical results identify a combination of a gradient boosting algorithm, our new sentiment dictionary, and text-features based-on term frequency weighting to offer the most accurate forecasts. These findings are valuable for traders, risk managers and other consumers of foreign exchange market forecasts and offer guidance how to design accurate prediction systems.

Suggested Citation

  • Naderi Semiromi, Hamed & Lessmann, Stefan & Peters, Wiebke, 2020. "News will tell: Forecasting foreign exchange rates based on news story events in the economy calendar," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    • Handle: RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940820300784
    DOI: 10.1016/j.najef.2020.101181
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940820300784
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.najef.2020.101181?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Michael J. Sager & Mark P. Taylor, 2006. "Under the microscope: the structure of the foreign exchange market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(1), pages 81-95.
    2. Stephen Hansen & Michael McMahon, 2016. "Shocking Language: Understanding the Macroeconomic Effects of Central Bank Communication," NBER Chapters, in: NBER International Seminar on Macroeconomics 2015, National Bureau of Economic Research, Inc.
    3. Frankel, Jeffrey A. & Rose, Andrew K., 1995. "Empirical research on nominal exchange rates," Handbook of International Economics, in: G. M. Grossman & K. Rogoff (ed.), Handbook of International Economics, edition 1, volume 3, chapter 33, pages 1689-1729, Elsevier.
    4. Liebmann, Michael & Orlov, Alexei G. & Neumann, Dirk, 2016. "The tone of financial news and the perceptions of stock and CDS traders," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 159-175.
    5. Chang, Ya-Ting & Gau, Yin-Feng & Hsu, Chih-Chiang, 2017. "Liquidity Commonality in Foreign Exchange Markets During the Global Financial Crisis and the Sovereign Debt Crisis: Effects of Macroeconomic and Quantitative Easing Announcements," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 172-192.
    6. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    7. Bekiros, Stelios D., 2015. "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 34-49.
    8. Sarno,Lucio & Taylor,Mark P., 2003. "The Economics of Exchange Rates," Cambridge Books, Cambridge University Press, number 9780521485845, September.
    9. Sun, Andrew & Lachanski, Michael & Fabozzi, Frank J., 2016. "Trade the tweet: Social media text mining and sparse matrix factorization for stock market prediction," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 272-281.
    10. repec:bla:intfin:v:4:y:2001:i:2:p:303-20 is not listed on IDEAS
    11. Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
    12. Campbell, John Y. & Lo, Andrew W. & MacKinlay, A. Craig & Whitelaw, Robert F., 1998. "The Econometrics Of Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(4), pages 559-562, December.
    13. Pincak, R., 2013. "The string prediction models as invariants of time series in the forex market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6414-6426.
    14. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    15. Basak, Suryoday & Kar, Saibal & Saha, Snehanshu & Khaidem, Luckyson & Dey, Sudeepa Roy, 2019. "Predicting the direction of stock market prices using tree-based classifiers," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 552-567.
    16. Coleman, Andrew & Karagedikli, Özer, 2012. "The relative size of exchange rate and interest rate responses to news: An empirical investigation," The North American Journal of Economics and Finance, Elsevier, vol. 23(1), pages 1-19.
    17. Chen, Zhongfei & Matousek, Roman & Wanke, Peter, 2018. "Chinese bank efficiency during the global financial crisis: A combined approach using satisficing DEA and Support Vector Machines☆," The North American Journal of Economics and Finance, Elsevier, vol. 43(C), pages 71-86.
    18. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    19. István Ábel & Pierre L. Siklos & István P. Székely, 1998. "Money and Finance in the Transition to a Market Economy," Books, Edward Elgar Publishing, number 830.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu, Yingying & Dai, Yifan & Guo, Lingling & Chen, Jingjing, 2024. "Leveraging machine learning to forecast carbon returns: Factors from energy markets," Applied Energy, Elsevier, vol. 357(C).
    2. Muhammad Ateeq ur REHMAN & Furman ALI & Shang XIE, 2022. "Impact of Foreign Investment News on the Return, Cost of Equity and Cash Flow Activities," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 112-127, December.
    3. Han, Chen & Wu, Chengliang & Wei, Lu, 2023. "The impact of the disclosure characteristics of the application material on the successful listing of companies on China’s Science and Technology Innovation Board," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    4. Hongcheng Ding & Xuanze Zhao & Zixiao Jiang & Shamsul Nahar Abdullah & Deshinta Arrova Dewi, 2024. "EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods," Papers 2408.13214, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    2. Alexander Jakob Dautel & Wolfgang Karl Härdle & Stefan Lessmann & Hsin-Vonn Seow, 2020. "Forex exchange rate forecasting using deep recurrent neural networks," Digital Finance, Springer, vol. 2(1), pages 69-96, September.
    3. Taylor, Mark & Hsu, Po-Hsuan, 2014. "Forty Years, Thirty Currencies and 21,000 Trading Rules: A Large-scale, Data-Snooping Robust Analysis of Technical Trading in t," CEPR Discussion Papers 10018, C.E.P.R. Discussion Papers.
    4. Lukas Menkhoff & Mark P. Taylor, 2007. "The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis," Journal of Economic Literature, American Economic Association, vol. 45(4), pages 936-972, December.
    5. Hsu, Po-Hsuan & Taylor, Mark P. & Wang, Zigan & Li, Yan, 2024. "The out-of-sample performance of carry trades," Journal of International Money and Finance, Elsevier, vol. 143(C).
    6. Andreas Hadjixenophontos & Christos Christodoulou-Volos, 2017. "Predictability of Foreign Exchange Rates with the AR(1) Model," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-3.
    7. Stuart Landon & Constance E. Smith, 2003. "The Risk Premium, Exchange Rate Expectations, and the Forward Exchange Rate: Estimates for the Yen–Dollar Rate," Review of International Economics, Wiley Blackwell, vol. 11(1), pages 144-158, February.
    8. Accominotti, Olivier & Chambers, David, 2016. "If You're So Smart: John Maynard Keynes and Currency Speculation in the Interwar Years," The Journal of Economic History, Cambridge University Press, vol. 76(2), pages 342-386, June.
    9. Melvin, Michael & Prins, John & Shand, Duncan, 2013. "Forecasting Exchange Rates: an Investor Perspective," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 721-750, Elsevier.
    10. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
    11. M A Sánchez-Granero & J E Trinidad-Segovia & J Clara-Rahola & A M Puertas & F J De las Nieves, 2017. "A model for foreign exchange markets based on glassy Brownian systems," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-22, December.
    12. Ronald MacDonald & Lukas Menkhoff & Rafael R. Rebitzky, 2009. "Exchange Rate Forecasters' Performance: Evidence of Skill?," CESifo Working Paper Series 2615, CESifo.
    13. Venus Khim-Sen Liew & Ricky Chee-Jiun Chia & Tai-Hu Ling, 2010. "Long-run validity of purchasing power parity and rank tests for cointegration for Central Asian countries," Applied Economics Letters, Taylor & Francis Journals, vol. 17(11), pages 1073-1077.
    14. Bauer, Christian & De Grauwe, Paul & Reitz, Stefan, 2009. "Exchange rate dynamics in a target zone--A heterogeneous expectations approach," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 329-344, February.
    15. Cheung, Yin-Wong & Chinn, Menzie David, 2001. "Currency traders and exchange rate dynamics: a survey of the US market," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 439-471, August.
    16. Menkhoff, Lukas & Rebitzky, Rafael R. & Schröder, Michael, 2009. "Heterogeneity in exchange rate expectations: Evidence on the chartist-fundamentalist approach," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 241-252, May.
    17. MacDonald, Ronald & Menkhoff, Lukas & Rebitzky, Rafael R., 2009. "Exchange rate forecasters’ performance: evidence of skill?," SIRE Discussion Papers 2009-10, Scottish Institute for Research in Economics (SIRE).
    18. Thomas Gehrig & Lukas Menkhoff, 2005. "The Rise of Fund Managers in Foreign Exchange:Will Fundamentals Ultimately Dominate?," The World Economy, Wiley Blackwell, vol. 28(4), pages 519-540, April.
    19. Cavusoglu Nevin, 2011. "Exchange Rates and the Effectiveness of Actual and Oral Official Interventions: A Survey on Findings, Issues and Policy Implications," Global Economy Journal, De Gruyter, vol. 10(4), pages 1-42, January.
    20. Taylor, Mark P. & Peel, David A., 2000. "Nonlinear adjustment, long-run equilibrium and exchange rate fundamentals," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 33-53, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:52:y:2020:i:c:s1062940820300784. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.