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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/108889


    Title: A Nonparametric Test of a Strong Leverage Hypothesis
    Authors: 顏佑銘
    Linton, Oliver;Whang, Yoon-Jae;Yen, Yu-Min
    Contributors: 國貿系
    Keywords: Distribution function;Leverage effect;Gaussian process
    Date: 2016-09
    Issue Date: 2017-04-17 12:20:50 (UTC+8)
    Abstract: 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.
    Relation: Journal of Econometrics, 194(1), 153-186
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.jeconom.2016.02.018
    DOI: 10.1016/j.jeconom.2016.02.018
    Appears in Collections:[國際經營與貿易學系 ] 期刊論文

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