| dc.contributor | 國貿系 | |
| dc.creator (作者) | 顏佑銘 | zh_TW |
| dc.creator (作者) | Linton, Oliver;Whang, Yoon-Jae;Yen, Yu-Min | |
| dc.date (日期) | 2016-09 | |
| dc.date.accessioned | 17-Apr-2017 12:20:50 (UTC+8) | - |
| dc.date.available | 17-Apr-2017 12:20:50 (UTC+8) | - |
| dc.date.issued (上傳時間) | 17-Apr-2017 12:20:50 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/108889 | - |
| dc.description.abstract (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. | |
| dc.format.extent | 3328491 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | Journal of Econometrics, 194(1), 153-186 | |
| dc.subject (關鍵詞) | Distribution function; Leverage effect; Gaussian process | |
| dc.title (題名) | A Nonparametric Test of a Strong Leverage Hypothesis | |
| dc.type (資料類型) | article | |
| dc.identifier.doi (DOI) | 10.1016/j.jeconom.2016.02.018 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1016/j.jeconom.2016.02.018 | |
