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    題名: A Nonparametric Test of a Strong Leverage Hypothesis
    作者: 顏佑銘
    Linton, Oliver;Whang, Yoon-Jae;Yen, Yu-Min
    貢獻者: 國貿系
    關鍵詞: Distribution function;Leverage effect;Gaussian process
    日期: 2016-09
    上傳時間: 2017-04-17 12:20:50 (UTC+8)
    摘要: The so-called leverage hypothesis is that negative shocks to prices/returns affect volatility more than equal positive shocks. Whether this is attributable to changing financial leverage is still subject to dispute but the terminology is in wide use. There are many tests of the leverage hypothesis using discrete time data. These typically involve fitting of a general parametric or semiparametric model to conditional volatility and then testing the implied restrictions on parameters or curves. We propose an alternative way of testing this hypothesis using realized volatility as an alternative direct nonparametric measure. Our null hypothesis is of conditional distributional dominance and so is much stronger than the usual hypotheses considered previously. We implement our test on individual stocks and a stock index using intraday data over a long span. We find only very weak evidence against our hypothesis.
    關聯: Journal of Econometrics, 194(1), 153-186
    資料類型: article
    DOI 連結: http://dx.doi.org/10.1016/j.jeconom.2016.02.018
    DOI: 10.1016/j.jeconom.2016.02.018
    顯示於類別:[國際經營與貿易學系 ] 期刊論文

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