A New Deep Learning-Based Zero-Inflated Duration Model for Financial Data Irregularly Spaced in Time

In stock trading markets, trade duration (i. e., inter-arrival times of trades) usually exhibits high uncertainty and excessive zero values. To forecast conditional distribution of trade duration, this study proposes a hybrid model called “DL-ZIACD” for short, which addresses the problem of excessiv...

Full description

Bibliographic Details

Published in:	Frontiers in Physics
Main Authors:	Yong Shi, Wei Dai, Wen Long
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2021-05-01
Subjects:	hybrid model deep learning conditional duration tick data distribution forecasting
Online Access:	https://www.frontiersin.org/articles/10.3389/fphy.2021.651528/full