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An econometric essay for the asymmetric volatility content of the portfolio flows: EGARCH evidence from the Turkish economy

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  • Korap, Levent

Abstract

In this paper, the information content of the volatility observed on portfolio flows is tried to be econometrically examined for the Turkish economy. Our findings employing EGARCH estimation methodology reveal that the volatility shocks on the portfolio flows seem to be of a quite persistent form and that the news impact extracted from the model is asymmetric such that the conditional variance of the net portfolio flows reacts more to past negative shocks than to positive innovations of the equal size. Such a result has been attributed to that inside the period under investigation an unanticipated decrease in net portfolio flows would lead to a higher level of uncertainty when compared with the uncertainty resulted from an unanticipated increase and that policy makers ought to be prudent against the increasing uncertainties in the economy especially if large portfolio outflows are to be experienced.

Suggested Citation

  • Korap, Levent, 2010. "An econometric essay for the asymmetric volatility content of the portfolio flows: EGARCH evidence from the Turkish economy," MPRA Paper 28752, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:28752
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    References listed on IDEAS

    as
    1. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. C. Emre Alper, Ismail Saglam, 2001. "The Transmission of a Sudden Capital Outflow: Evidence from Turkey," Eastern European Economics, Taylor & Francis Journals, vol. 39(2), pages 29-48, March.
    4. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. 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.
    7. 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)

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    More about this item

    Keywords

    Portfolio Flows; Asymmetric Volatility; EGARCH Modeling; Turkish Economy;
    All these keywords.

    JEL classification:

    • F32 - International Economics - - International Finance - - - Current Account Adjustment; Short-term Capital Movements
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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