Description
Many real-world financial time series forecasting problems share a unique property: the focal variable of interests can be decomposed into a large number of accounting component variables. For example, company earnings are calculated from total revenue mi
Recommended Citation
Qiao, Mengke and Huang, Kewei, "Hierarchical Accounting Variables Forecasting by Deep Learning Methods" (2018). ICIS 2018 Proceedings. 7.
https://aisel.aisnet.org/icis2018/crypto/Presentations/7
Hierarchical Accounting Variables Forecasting by Deep Learning Methods
Many real-world financial time series forecasting problems share a unique property: the focal variable of interests can be decomposed into a large number of accounting component variables. For example, company earnings are calculated from total revenue mi