Invention Grant
- Patent Title: Techniques to forecast financial data using deep learning
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Application No.: US16767291Application Date: 2019-03-15
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Publication No.: US11620589B2Publication Date: 2023-04-04
- Inventor: Dajun Wang , Qinxue Meng , Zhendi Chen
- Applicant: State Street Corporation
- Applicant Address: US MA Boston
- Assignee: State Street Corporation
- Current Assignee: State Street Corporation
- Current Assignee Address: US MA Boston
- Agency: Goodwin Procter LLP
- International Application: PCT/CN2019/078230 WO 20190315
- International Announcement: WO2020/186376 WO 20200924
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06Q10/04 ; G06K9/62 ; G06V10/75

Abstract:
The present disclosure describes techniques to forecast financial data using deep learning. These techniques are operative to transform time series data in a financial context into a machine learning model configured to predict future financial data. The machine learning model may implement a deep learning structure to account for a sequence-sequence prediction where a movement/distribution of the time series data is non-linear. The machine learning model may incorporate features related to one or more external factors affecting the future financial data. Other embodiments are described and claimed.
Public/Granted literature
- US20210224700A1 TECHNIQUES TO FORECAST FINANCIAL DATA USING DEEP LEARNING Public/Granted day:2021-07-22
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