Yazar "Omay, Tolga" seçeneğine göre listele

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    An empirical examination of the generalized Fisher effect using cross-sectional correlation robust tests for panel cointegration
    (Elsevier Science BV, 2015-03) Omay, Tolga; Yüksel, Aslı; Yüksel, Sadettin Aydın
    This study examines the generalized Fisher hypothesis as applied to common stocks by using the recently proposed second generation panel cointegration tests. Unlike their predecessors, these new tests assume the existence of cross-section dependence in the data. For the sample analyzed, we report that these new tests, but not their predecessors, provide strong support for the existence of cointegration between stock and goods prices. Moreover, further analysis cannot reject the hypothesis that the cointegration relation is linear. Finally, our Fisher coefficient estimates are in the range between 0.68 and 1.27 and give support to the generalized Fisher hypothesis.
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    Global risk aversion and emerging market return comovements
    (Elsevier Science SA, 2018-12) Demirer, Rıza; Omay, Tolga; Yüksel, Aslı; Yüksel, Sadettin Aydın
    Utilizing the recently developed measure of global risk aversion by Xu (2017), we show that global risk aversion is a significant determinant of international equity correlations, consistently across all emerging markets examined. The positive effect of risk aversion on emerging market comovements is particularly strong for South Africa and Turkey and is consistent with contagion effects. The results underscore the importance of non-cash flow shocks in models of contagion and portfolio risk.
  • Küçük Resim
    Yayın
    A note on the examination of the fisher hypothesis by using panel co-integration tests with break
    (Institute foe Economic Forecasting, 2016) Omay, Tolga; Hasanov, Mübariz; Yüksel, Aslı; Yüksel, Aydın
    One problem encountered when examining the Fisher hypothesis is that various policy changes and economic shocks may induce structural shifts in the long-run relation. We explore the argument that panel cointegration tests based on common correlated effect estimators have reasonably good power and size properties, even in the presence of structural breaks, if the timing of structural shifts roughly coincide to each other across individual group members. Using the data from Omay et al. (2015), which pays special attention to cross-section dependence issue but ignores the possibility of structural break in the data, we provide support to the argument above.