کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5069217 | 1476982 | 2017 | 7 صفحه PDF | دانلود رایگان |
- An extension of the standard bipower variation based jump detection test is proposed.
- The new test significantly outperforms the standard method in a Monte Carlo setting.
- Empirical analysis of a million trading days shows improved detection capability.
We present a statistical test to identify significant events in financial price time series. In contrast to “jumps,” we define “events” as non-instantaneous, but nevertheless unusually fast and large, price changes. We show that non-parametric tests perform badly in detecting events so defined. We propose a new approach to explore the dependence of jump detection statistics on the sampling method used and find that our method improves the event detection rate of the standard test by a factor of three.
Journal: Finance Research Letters - Volume 22, August 2017, Pages 42-48