IDEAS home Printed from https://ideas.repec.org/a/col/000520/018766.html
   My bibliography  Save this article

El comportamiento del precio del petróleo y la volatilidad en la tasa de cambio: análisis de impacto de las variaciones del WTI y de la tasa de interés referencia sobre la tasa de cambio nominal en Colombia, periodo 2013-2015

Author

Listed:
  • Rivera, Marcelo Meneses

    (Universidad de Nariño)

  • Toro, Jessica Stephany

    (Universidad de Nariño)

  • Riascos, Julio Cesár

    (Universidad de Mariana)

Abstract

El objetivo de esta investigación reside en relacionar la tasa de interés de referencia, las cotizaciones del precio del petróleo y la tasa de cambio nominal, para determinar en qué medida cada una de estas variables exógenas afectan la tasa de cambio. La metodología utilizada para tal propósito consiste en esgrimir la teoría planteada por Mauricio Cárdenas (Introducción a la Economía Colombiana, 2013) y la implementación del modelo Mundell-Fleming. El análisis se hace mediante la implementación de modelos de regresión por Mínimos Cuadrados Ordinarios, GARCH, EGARCH y VAR. El estudio advierte que la tasa de cambio se vio afectada por elementos como: la cotización más baja del WTI, el desplome de las principales bolsas de valores del mundo, la decisión del Banco Central de Estados Unidos de mantener su tasa de interés de referencia y la devaluación de la moneda china, Yuan. El estudio concluye que los precios del crudo y la tasa de cambio están relacionados de manera negativa (tal y como lo sugieren AUTORES), por lo que una desvalorización en los precios del petróleo conduce a una depreciación del peso. De manera análoga, la tasa de interés de referencia está relacionada de manera inversa con la tasa de cambio, permitiendo aceptar las derivaciones del modelo Mundell – Fleming.

Suggested Citation

  • Rivera, Marcelo Meneses & Toro, Jessica Stephany & Riascos, Julio Cesár, 2017. "El comportamiento del precio del petróleo y la volatilidad en la tasa de cambio: análisis de impacto de las variaciones del WTI y de la tasa de interés referencia sobre la tasa de cambio nominal en Co," Revista Tendencias, Universidad de Narino, vol. 18(1), pages 13-40, January.
  • Handle: RePEc:col:000520:018766
    DOI: 10.22267/rtend.171801.62
    as

    Download full text from publisher

    File URL: https://doi.org/10.22267/rtend.171801.62
    Download Restriction: no

    File URL: https://libkey.io/10.22267/rtend.171801.62?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
    ---><---

    References listed on IDEAS

    as
    1. Julio César Alonso C & Alejandro Cabrera, 2004. "La tasa de cambio nominal en Colombia," Apuntes de Economía 3082, Universidad Icesi.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Zheng, Xi & Lu, Xi & Chan, Felix T.S. & Deng, Yong & Wang, Zhen, 2015. "Bargaining models in opinion dynamics," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 162-168.
    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. Seiler, Volker, 2024. "The relationship between Chinese and FOB prices of rare earth elements – Evidence in the time and frequency domain," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 160-179.
    2. Beran, Jan & Feng, Yuanhua, 1999. "Local Polynomial Estimation with a FARIMA-GARCH Error Process," CoFE Discussion Papers 99/08, University of Konstanz, Center of Finance and Econometrics (CoFE).
    3. Corbet, Shaen & Larkin, Charles & McMullan, Caroline, 2020. "The impact of industrial incidents on stock market volatility," Research in International Business and Finance, Elsevier, vol. 52(C).
    4. Minot, Nicholas, 2014. "Food price volatility in sub-Saharan Africa: Has it really increased?," Food Policy, Elsevier, vol. 45(C), pages 45-56.
    5. Lahmiri, Salim & Bekiros, Stelios, 2017. "Disturbances and complexity in volatility time series," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 38-42.
    6. Tomanova, Lucie, 2013. "Exchange Rate Volatility and the Foreign Trade in CEEC," EY International Congress on Economics I (EYC2013), October 24-25, 2013, Ankara, Turkey 267, Ekonomik Yaklasim Association.
    7. Chang, Chia-Lin, 2015. "Modelling a latent daily Tourism Financial Conditions Index," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 113-126.
    8. Goncalves, Silvia & Kilian, Lutz, 2004. "Bootstrapping autoregressions with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 123(1), pages 89-120, November.
    9. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    10. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    11. Bentes, Sonia R. & Menezes, Rui, 2013. "On the predictability of realized volatility using feasible GLS," Journal of Asian Economics, Elsevier, vol. 28(C), pages 58-66.
    12. Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016. "Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution," International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
    13. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2016. "Efficient Gibbs sampling for Markov switching GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 37-57.
    14. SILVESTRINI, Andrea & VEREDAS, David, 2005. "Temporal aggregation of univariate linear time series models," LIDAM Discussion Papers CORE 2005059, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. repec:wyi:journl:002087 is not listed on IDEAS
    16. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    17. Dhanya Jothimani & Ravi Shankar & Surendra S. Yadav, 2016. "Discrete Wavelet Transform-Based Prediction of Stock Index: A Study on National Stock Exchange Fifty Index," Papers 1605.07278, arXiv.org.
    18. Mika Meitz & Pentti Saikkonen, 2008. "Stability of nonlinear AR‐GARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(3), pages 453-475, May.
    19. Mai, Nhat Chi, 2022. "Tác động của lạm phát đến hoạt động của thị trường chứng khoán ở Việt Nam: Kiểm chứng bằng mô hình GARCH," OSF Preprints azcqd, Center for Open Science.
    20. Mohamed Es-Sanoun & Jude Gohou & Mounir Benboubker, 2023. "Testing of Herd Behavior In african Stock Markets During COVID-19 Pandemic [Essai de vérification du comportement mimétique dans les marchés boursiers africains au cours de la crise de covid-19]," Post-Print hal-04144289, HAL.
    21. Angelidis, Dimitrios & Koulakiotis Athanasios & Kiohos Apostolos, 2018. "Feedback Trading Strategies: The Case of Greece and Cyprus," South East European Journal of Economics and Business, Sciendo, vol. 13(1), pages 93-99, June.

    More about this item

    Keywords

    modelo de Mundell – Fleming; modelo de Mínimos Cuadrados Ordinarios (MCO); modelos Autorregresivos Condicionados Por Heterocedasticidad Generalizada (GARCH); modelo Exponencial Generalizado Autorregresivo Condicionalmente Heterocedástico (EGARCH); modelos;
    All these keywords.

    JEL classification:

    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements
    • O24 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Trade Policy; Factor Movement; Foreign Exchange Policy

    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:col:000520:018766. 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: Universidad de Narino (email available below). General contact details of provider: https://edirc.repec.org/data/fenarco.html .

    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.