IDEAS home Printed from https://ideas.repec.org/a/erh/journl/v14y2022i1p1-20.html
   My bibliography  Save this article

Deterministic Effects of Volatility on Mixed Frequency GARCH in Means MIDAS Model: Evidence from Turkey

Author

Listed:
  • Fehmi Özsoy

    (Haci Bayram Veli University, Emniyet Mahallesi Muammer Yaþar Bostanci Caddesi, No:4, Beþevler/Ankara, Turkey.)

  • Nükhet Doðan

    (Haci Bayram Veli University, Emniyet Mahallesi Muammer Yaþar Bostanci Caddesi, No:4, Beþevler/Ankara, Turkey.)

Abstract

Volatility is a key concept for understanding the dual relationships between the economic variables since it is inversely related to the stability of economies. Many models such as GARCH models have been constructed through time to understand which determinants and conditions can affect the volatility. These models mostly show the significant relationships between the volatilities generated by the low frequency macroeconomic activities and the high frequency financial variables in a stochastic way. However, it is required to check whether there exist deterministic effects of volatilities on high frequency economic variables. In order to reveal these deterministic effects, we developed a new component-wise model, namely GARCH-M MIDAS model. We formulate this model on stock prices and exchange rates, in which the long run volatility is driven by consumer price and industrial production indexes in a separate way. Hence, our empirical analyses support that both types of volatilities have statistically significant deterministic effects on the asset pricing of high frequency financial variables. We also find that macroeconomic activities have a significant role on the asset pricing in long horizons.

Suggested Citation

  • Fehmi Özsoy & Nükhet Doðan, 2022. "Deterministic Effects of Volatility on Mixed Frequency GARCH in Means MIDAS Model: Evidence from Turkey," International Econometric Review (IER), Econometric Research Association, vol. 14(1), pages 1-20, March.
  • Handle: RePEc:erh:journl:v:14:y:2022:i:1:p:1-20
    as

    Download full text from publisher

    File URL: http://www.era.org.tr/makaleler/1053547.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    2. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    3. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.
    4. Pati, Pratap Chandra & Rajib, Prabina & Barai, Parama, 2019. "The role of the volatility index in asset pricing: The case of the Indian stock market," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 336-346.
    5. 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.
    6. Tobias Adrian & Joshua Rosenberg, 2008. "Stock Returns and Volatility: Pricing the Short‐Run and Long‐Run Components of Market Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2997-3030, December.
    7. Schwert, G William, 1981. "The Adjustment of Stock Prices to Information about Inflation," Journal of Finance, American Finance Association, vol. 36(1), pages 15-29, March.
    8. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    9. Eichler, Stefan & Littke, Helge C.N., 2018. "Central bank transparency and the volatility of exchange rates," Journal of International Money and Finance, Elsevier, vol. 89(C), pages 23-49.
    10. Apergis, Nicholas & Eleftheriou, Sophia, 2002. "Interest rates, inflation, and stock prices: the case of the Athens Stock Exchange," Journal of Policy Modeling, Elsevier, vol. 24(3), pages 231-236, June.
    11. Beltratti, A. & Morana, C., 2006. "Breaks and persistency: macroeconomic causes of stock market volatility," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 151-177.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. Clarida, Richard & Davis, Josh & Pedersen, Niels, 2009. "Currency carry trade regimes: Beyond the Fama regression," Journal of International Money and Finance, Elsevier, vol. 28(8), pages 1375-1389, December.
    14. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    15. Dupuy, Philippe & James, Jessica & Marsh, Ian W., 2021. "Attractive and non-attractive currencies," Journal of International Money and Finance, Elsevier, vol. 110(C).
    16. Adam, Tomáš & Benecká, Soňa & Matějů, Jakub, 2018. "Financial stress and its non-linear impact on CEE exchange rates," Journal of Financial Stability, Elsevier, vol. 36(C), pages 346-360.
    17. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    18. Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
    19. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    20. Andreas Humpe & Peter Macmillan, 2009. "Can macroeconomic variables explain long-term stock market movements? A comparison of the US and Japan," Applied Financial Economics, Taylor & Francis Journals, vol. 19(2), pages 111-119.
    21. Tsagkanos, Athanasios & Siriopoulos, Costas, 2015. "Stock markets and industrial production in north and south of Euro-zone: Asymmetric effects via threshold cointegration approach," The Journal of Economic Asymmetries, Elsevier, vol. 12(2), pages 162-172.
    22. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Bandi, Federico M. & Bretscher, Lorenzo & Tamoni, Andrea, 2023. "Return predictability with endogenous growth," Journal of Financial Economics, Elsevier, vol. 150(3).
    2. Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010. "Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
    3. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    4. Campbell, John Y. & Giglio, Stefano & Polk, Christopher & Turley, Robert, 2018. "An intertemporal CAPM with stochastic volatility," Journal of Financial Economics, Elsevier, vol. 128(2), pages 207-233.
    5. Kaminska, Iryna & Roberts-Sklar, Matt, 2018. "Volatility in equity markets and monetary policy rate uncertainty," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 68-83.
    6. Jon Danielsson & Marcela Valenzuela & Ilknur Zer, 2018. "Learning from History: Volatility and Financial Crises," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2774-2805.
    7. Yun-Shi Dai & Peng-Fei Dai & Wei-Xing Zhou, 2024. "The impact of geopolitical risk on the international agricultural market: Empirical analysis based on the GJR-GARCH-MIDAS model," Papers 2404.01641, arXiv.org.
    8. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    9. Belén Nieto & Alfonso Novales & Gonzalo Rubio, 2015. "Macroeconomic and Financial Determinants of the Volatility of Corporate Bond Returns," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-41, December.
    10. Pan, Zhiyuan & Wang, Yudong & Wu, Chongfeng & Yin, Libo, 2017. "Oil price volatility and macroeconomic fundamentals: A regime switching GARCH-MIDAS model," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 130-142.
    11. José Antonio Núñez-Mora & Roberto Joaquín Santillán-Salgado & Mario Iván Contreras-Valdez, 2022. "COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets," Mathematics, MDPI, vol. 10(9), pages 1-36, April.
    12. Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2015. "The impact of financial crises on the risk–return tradeoff and the leverage effect," Economic Modelling, Elsevier, vol. 49(C), pages 407-418.
    13. Duc Khuong Nguyen & Thomas Walther, 2020. "Modeling and forecasting commodity market volatility with long‐term economic and financial variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 126-142, March.
    14. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    15. Rangel, José Gonzalo, 2011. "Macroeconomic news, announcements, and stock market jump intensity dynamics," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1263-1276, May.
    16. Chee Wooi Hooy & Hui Boon Tan & Annuar Md Nassir, 2004. "Risk Sensitivity of Bank Stocks in Malaysia: Empirical Evidence Across the Asian Financial Crisis," Asian Economic Journal, East Asian Economic Association, vol. 18(3), pages 261-276, September.
    17. Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
    18. Philippe Goulet Coulombe & Mikael Frenette & Karin Klieber, 2023. "From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks," Working Papers 23-04, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Nov 2023.
    19. Choi, Jaewon & Richardson, Matthew, 2016. "The volatility of a firm's assets and the leverage effect," Journal of Financial Economics, Elsevier, vol. 121(2), pages 254-277.
    20. Cong, Ren & Lo, Alex Y., 2017. "Emission trading and carbon market performance in Shenzhen, China," Applied Energy, Elsevier, vol. 193(C), pages 414-425.

    More about this item

    Keywords

    MIDAS; GARCH-MIDAS; Long Run; Short Run; Deterministic Effects;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    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:erh:journl:v:14:y:2022:i:1:p:1-20. 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: M. F. Cosar (email available below). General contact details of provider: https://edirc.repec.org/data/eratrea.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.