In this paper, the trading volume duration sequence derived from high-frequency tick-by-tick data is analyzed by Copula method. The auto-dependence structure of several consecutive trading volume durations is estimated by multivariate vine Copula, then, a new estimating method about conditional density function forecasting is also proposed. Moreover, a new forecasting method of the volume duration is put forward. Empirical results of Sinopec show that the predictive ability of our model is much better than that of EACD, which can also be demonstrated from the density forecasting test.
YE Wu-Yi, LI Xiao-ying, MIAO Bai-Qi
. Auto-dependence Structure Estimating and Forecasting of Duration Based on Vine Copula[J]. Chinese Journal of Management Science, 2015
, 23(11)
: 29
-38
.
DOI: 10.16381/j.cnki.issn1003-207x.2015.11.004
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