IDEAS home Printed from https://ideas.repec.org/a/ers/journl/vxxviiy2024i2p952-966.html
   My bibliography  Save this article

Co-variance in Action: Analyzing the Impact of EUR/USD Exchange Rate Changes on Polish Zloty (PLN) Valuation (2019–2022) as a Predictive Tool in Forex Markets

Author

Listed:
  • Jaroslaw Klepacki

Abstract

Purpose: The purpose of the study is to examine the phenomenon of co-variance using the example of the impact of changes in the EUR/USD exchange rate on the value of the Polish zloty (PLN) as an element of forecasting in the foreign exchange market. The first objective of the study is to confirm the hypothesis that one of the most important external factors influencing the state of the Polish currency is the euro-dollar exchange rate. The second secondary objective is to confirm the research findings that an increase in volatility on the foreign exchange market often leads to a depreciation of the currencies of countries with a relatively higher interest rate level, i.e., mainly emerging countries, even in periods of unpredictable phenomena. Design/methodology/approach: Using research based, inter alia, on the Pearson linear correlation coefficient over the period 2019 - 2022, at different time intervals for Japanese technical analysis candles, taking into account the occurrence of so-called unpredictable events. Findings: The results show that, contrary to popular opinion, it is possible to speak of the occurrence of a co-variance phenomenon with respect to USD/PLN and EUR/USD. Moreover, the hypothesis of an impact of the EUR/USD exchange rate on EUR/PLN according to the principle: "an increase in the EUR/USD exchange rate favours the zloty against the euro" is also not supported by the research conducted. It can be confirmed that the sharp increase in liquidity and volatility in the area of the currency pairs studied does not allow us to confirm the assumption that they directly favour the phenomenon of co-movement. Practical implications: These results provide an important practical vector for the creation of predictive models in such a complex and volatile area as the foreign exchange market. Originality value: This research aims to fill the research gap in the field of exchange rate forecasting models taking into account extreme phenomena of the external environment. The implications of such a study can be applied as part of a prediction system in the corporate area.

Suggested Citation

  • Jaroslaw Klepacki, 2024. "Co-variance in Action: Analyzing the Impact of EUR/USD Exchange Rate Changes on Polish Zloty (PLN) Valuation (2019–2022) as a Predictive Tool in Forex Markets," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 952-966.
    • Handle: RePEc:ers:journl:v:xxvii:y:2024:i:2:p:952-966
    as

    Download full text from publisher

    File URL: https://ersj.eu/journal/3829/download
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bajgrowicz, Pierre & Scaillet, Olivier, 2012. "Technical trading revisited: False discoveries, persistence tests, and transaction costs," Journal of Financial Economics, Elsevier, vol. 106(3), pages 473-491.
    2. Moshirian, Fariborz, 2004. "Elements of global financial stability," Journal of Multinational Financial Management, Elsevier, vol. 14(4-5), pages 305-314.
    3. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability of Technical Analysis: A Review," AgMAS Project Research Reports 37487, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    4. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    5. Byrne, Joseph P. & Korobilis, Dimitris & Ribeiro, Pinho J., 2016. "Exchange rate predictability in a changing world," Journal of International Money and Finance, Elsevier, vol. 62(C), pages 1-24.
    6. Lukas Menkhoff & Lucio Sarno & Maik Schmeling & Andreas Schrimpf, 2012. "Carry Trades and Global Foreign Exchange Volatility," Journal of Finance, American Finance Association, vol. 67(2), pages 681-718, April.
    7. Liu, Ming-Hua & Margaritis, Dimitris & Tourani-Rad, Alireza, 2012. "Risk appetite, carry trade and exchange rates," Global Finance Journal, Elsevier, vol. 23(1), pages 48-63.
    8. Jenni L. Bettman & Stephen J. Sault & Emma L. Schultz, 2009. "Fundamental and technical analysis: substitutes or complements?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(1), pages 21-36, March.
    9. Jessica James, 2003. "Simple trend-following strategies in currency trading," Quantitative Finance, Taylor & Francis Journals, vol. 3(4), pages 75-77.
    10. Eleftherios J. Thalassinos & Evagelos D. Politis, 2012. "The Evaluation of the USD Currency and the Oil Prices: A Var Analysis," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 137-146.
    11. Van Rijckeghem, Caroline & Weder, Beatrice, 2001. "Sources of contagion: is it finance or trade?," Journal of International Economics, Elsevier, vol. 54(2), pages 293-308, August.
    Full references (including those not matched with items on IDEAS)

    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. Joscha Beckmann & Gary Koop & Dimitris Korobilis & Rainer Alexander Schüssler, 2020. "Exchange rate predictability and dynamic Bayesian learning," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(4), pages 410-421, June.
    2. Raheem, Ibrahim, 2020. "Global financial cycles and exchange rate forecast: A factor analysis," MPRA Paper 105358, University Library of Munich, Germany.
    3. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    4. 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).
    5. Hambuckers, J. & Ulm, M., 2023. "On the role of interest rate differentials in the dynamic asymmetry of exchange rates," Economic Modelling, Elsevier, vol. 129(C).
    6. Fabian Ackermann & Walt Pohl & Karl Schmedders, 2017. "Optimal and Naive Diversification in Currency Markets," Management Science, INFORMS, vol. 63(10), pages 3347-3360, October.
    7. Ahmed, Shamim & Liu, Xiaoquan & Valente, Giorgio, 2016. "Can currency-based risk factors help forecast exchange rates?," International Journal of Forecasting, Elsevier, vol. 32(1), pages 75-97.
    8. Engel, Charles & Kazakova, Katya & Wang, Mengqi & Xiang, Nan, 2022. "A reconsideration of the failure of uncovered interest parity for the U.S. dollar," Journal of International Economics, Elsevier, vol. 136(C).
    9. Lukas Kremens & Ian Martin, 2019. "The Quanto Theory of Exchange Rates," American Economic Review, American Economic Association, vol. 109(3), pages 810-843, March.
    10. Rubaszek, Michał & Beckmann, Joscha & Ca' Zorzi, Michele & Kwas, Marek, 2022. "Boosting carry with equilibrium exchange rate estimates," Working Paper Series 2731, European Central Bank.
    11. 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.
    12. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
    13. Dick, Christian D. & MacDonald, Ronald & Menkhoff, Lukas, 2015. "Exchange rate forecasts and expected fundamentals," Journal of International Money and Finance, Elsevier, vol. 53(C), pages 235-256.
    14. Demetrescu, Matei & Rodrigues, Paulo M.M. & Taylor, A.M. Robert, 2023. "Transformed regression-based long-horizon predictability tests," Journal of Econometrics, Elsevier, vol. 237(2).
    15. Joseph Agyapong, 2021. "Application of Taylor Rule Fundamentals in Forecasting Exchange Rates," Economies, MDPI, vol. 9(2), pages 1-27, June.
    16. Bruno P. C. Levy & Hedibert F. Lopes, 2021. "Dynamic Ordering Learning in Multivariate Forecasting," Papers 2101.04164, arXiv.org, revised Nov 2021.
    17. Lumengo Bonga-Bonga & Sefora Motena Rangoanana, 2022. "Carry Trade and Capital Market Returns in South Africa," JRFM, MDPI, vol. 15(11), pages 1-13, October.
    18. Alfredo Bateman y Javier E. Martinez & Javier Esteban Martinez, 2010. "Cuaderno 4: Análisis de las fuentes de oferta y demanda en el mercado de divisas," Cuadernos de Desarrollo Económico 7586, Secretaría Distrital de Desarrollo Económico.
    19. Emanuel Kohlscheen & Fernando Avalos & Andreas Schrimpf, 2017. "When the Walk Is Not Random: Commodity Prices and Exchange Rates," International Journal of Central Banking, International Journal of Central Banking, vol. 13(2), pages 121-158, June.
    20. Fang, Jiali & Jacobsen, Ben & Qin, Yafeng, 2014. "Predictability of the simple technical trading rules: An out-of-sample test," Review of Financial Economics, Elsevier, vol. 23(1), pages 30-45.

    More about this item

    Keywords

    Forecasting; currency market; liquidity management; volatility; correlation.;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    Statistics

    Access and download statistics

    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:ers:journl:v:xxvii:y:2024:i:2:p:952-966. 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: Marios Agiomavritis (email available below). General contact details of provider: https://ersj.eu/ .

    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.