Abstract
The monitoring and analysis algorithm of financial abnormal data based on data mining and neural network is a machine learning algorithm to monitor the abnormal data of financial market. It also uses historical stock price data to analyze the performance of various trading strategies to determine whether any strategy is better or lower than its benchmark. These algorithms are intended to be used as early warning systems for potential security problems in financial markets, such as fraud, insider trading, manipulation or other illegal activities. This technology uses AI to identify unusual trading patterns in the market, so that traders can make better decisions. What are the types of financial abnormal data monitoring and analysis algorithms based on data mining? There are two kinds of financial anomaly data monitoring and analysis algorithms based on Data Mining: time series anomaly detection and event based anomaly detection. Financial anomaly detection (fade) is a term that describes an automated process designed to detect abnormal patterns in financial market activities.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.