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

Author

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  • 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
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    References listed on IDEAS

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    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.
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    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)

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