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The Impact of Macroeconomic Sustainability on Exchange Rate: Hybrid Machine-Learning Approach

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  • Hüseyin İlker Erçen

    (Department of Economics, Near East University, Nicosia 99138, Cyprus)

  • Hüseyin Özdeşer

    (Department of Economics, Near East University, Nicosia 99138, Cyprus)

  • Turgut Türsoy

    (Department of Banking and Finance, Near East University, Nicosia 99138, Cyprus)

Abstract

This paper constructed a robust methodology to investigate the impact of news regarding macroeconomic policies on exchange rate fluctuations, and to examined the applicability of qualitative information alongside historical data to predict exchange rates. To do so, hybrid machine learning algorithms comprised of natural language processing, fuzzy logic, and support vector regression have been constructed. This study emphasizes the significance of qualitative information on investors’ subjective consideration, the decision-making process, and causality on exchange rate volatility. To perceive the causality of expected and unexpected macroeconomic news on exchange rate fluctuations, news regarding the inflation rate, interest rate, unemployment rate, balance of trade, and credit ratings has been extracted from the web. Learning automata has been adopted to construct a unique lexicon for textual analysis. Subjective considerations of decision makers based on news have been evaluated by processing using the prospect theory and composing fuzzy antecedents for the fuzzy logic phase. The fuzzy logic method attained the correlation value between the macroeconomic news and the exchange rate. Finally, support vector regression predicted the exchange rate on a daily basis. The statistical test results indicated a strong correlation between recently published macroeconomic news on daily exchange rate fluctuations and their usability for predicting exchange rates in the short term, while emphasizing the significance of sustainable macroeconomic policies on exchange rate stability.

Suggested Citation

  • Hüseyin İlker Erçen & Hüseyin Özdeşer & Turgut Türsoy, 2022. "The Impact of Macroeconomic Sustainability on Exchange Rate: Hybrid Machine-Learning Approach," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5357-:d:805227
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    as
    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Chen, Shiu-Sheng, 2007. "A note on interest rate defense policy and exchange rate volatility," Economic Modelling, Elsevier, vol. 24(5), pages 768-777, September.
    3. repec:bla:ecorec:v:70:y:1994:i:209:p:204-19 is not listed on IDEAS
    4. Kandil, Magda & Berument, Hakan & Dincer, N. Nergiz, 2007. "The effects of exchange rate fluctuations on economic activity in Turkey," Journal of Asian Economics, Elsevier, vol. 18(3), pages 466-489, June.
    5. Bruno Miranda Henrique & Vinicius Amorim Sobreiro & Herbert Kimura, 2018. "Building direct citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 817-832, May.
    6. DavidC. Parsley & Shang-Jin Wei, 2007. "A Prism into the PPP Puzzles: The Micro-Foundations of Big Mac Real Exchange Rates," Economic Journal, Royal Economic Society, vol. 117(523), pages 1336-1356, October.
    7. Paul De Grauwe, 1988. "Exchange Rate Variability and the Slowdown in Growth of International Trade," IMF Staff Papers, Palgrave Macmillan, vol. 35(1), pages 63-84, March.
    8. He, Yinghua & Nielsson, Ulf & Wang, Yonglei, 2017. "Hurting without hitting: The economic cost of political tension," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 106-124.
    9. Sarstedt, Marko & Ringle, Christian M. & Smith, Donna & Reams, Russell & Hair, Joseph F., 2014. "Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 5(1), pages 105-115.
    10. Manish Kumar & M. Thenmozhi, 2014. "Forecasting stock index returns using ARIMA-SVM, ARIMA-ANN, and ARIMA-random forest hybrid models," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 5(3), pages 284-308.
    11. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    12. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    13. Guglielmo Maria Caporale & Mohamad Husam Helmi, 2018. "Islamic banking, credit, and economic growth: Some empirical evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 456-477, October.
    14. Jansen, David-Jan & De Haan, Jakob, 2005. "Talking heads: the effects of ECB statements on the euro-dollar exchange rate," Journal of International Money and Finance, Elsevier, vol. 24(2), pages 343-361, March.
    15. Hüseyin Şen & Ayşe Kaya & Savaş Kaptan & Metehan Cömert, 2020. "Interest rates, inflation, and exchange rates in fragile EMEs: A fresh look at the long-run interrelationships," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 29(3), pages 289-318, April.
    16. Wang, Ju-Jie & Wang, Jian-Zhou & Zhang, Zhe-George & Guo, Shu-Po, 2012. "Stock index forecasting based on a hybrid model," Omega, Elsevier, vol. 40(6), pages 758-766.
    17. Barro, Robert J & Gordon, David B, 1983. "A Positive Theory of Monetary Policy in a Natural Rate Model," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 589-610, August.
    18. Mehdian, Seyed & Nas, Tevfik & Perry, Mark J., 2008. "An examination of investor reaction to unexpected political and economic events in Turkey," Global Finance Journal, Elsevier, vol. 18(3), pages 337-350.
    19. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    20. Hachula, Michael & Nautz, Dieter, 2018. "The dynamic impact of macroeconomic news on long-term inflation expectations," Economics Letters, Elsevier, vol. 165(C), pages 39-43.
    21. Hakob GRIGORYAN, 2016. "A Stock Market Prediction Method Based on Support Vector Machines (SVM) and Independent Component Analysis (ICA)," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 7(1), pages 12-21, August.
    22. Walid Bahloul & Rangan Gupta, 2018. "Impact of macroeconomic news surprises and uncertainty for major economies on returns and volatility of oil futures," International Economics, CEPII research center, issue 156, pages 247-253.
    23. David A. Swanson, 2015. "On the Relationship among Values of the Same Summary Measure of Error when it is used across Multiple Characteristics at the Same Point in Time: An Examination of MALPE and MAPE," Review of Economics & Finance, Better Advances Press, Canada, vol. 5, pages 1-14, August.
    24. Lattimore, Pamela K. & Baker, Joanna R. & Witte, Ann D., 1992. "The influence of probability on risky choice: A parametric examination," Journal of Economic Behavior & Organization, Elsevier, vol. 17(3), pages 377-400, May.
    25. Ozturk, 2006. "Exchange Rate Volatility and Trade: A Literature Survey," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 3(1), pages 85-102.
    26. Asteriou, Dimitrios & Masatci, Kaan & Pılbeam, Keith, 2016. "Exchange rate volatility and international trade: International evidence from the MINT countries," Economic Modelling, Elsevier, vol. 58(C), pages 133-140.
    27. Pamela K. Lattimore & Joanna R. Baker & A. Dryden Witte, 1992. "The Influence Of Probability on Risky Choice: A parametric Examination," NBER Technical Working Papers 0081, National Bureau of Economic Research, Inc.
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