Automated Financial Event Detection System
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Solution Overview
Problem
Current financial analysis methods, particularly technical analysis, rely heavily on manual interpretation of price charts and patterns, leading to inefficiencies in identifying and characterizing technical events, which limits the ability to automate the detection of trading opportunities and provide reliable signals to investors.
Innovation Solution
A system and method for providing a financial event identification service using a database that automates the detection and characterization of technical and fundamental events by employing data fusion, neural networks, and genetic algorithms to analyze market data, indicators, and oscillators, reducing false positives and enabling personalized alerts based on client profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual interpretation of price charts and patterns is used, then flexibility in analysis is maintained, but productivity and speed of identifying trading opportunities deteriorate
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated computer-based system that uses data fusion, neural networks, and genetic algorithms to detect technical events. This substitution maintains analytical flexibility through configurable parameters and multiple analysis methods while dramatically increasing productivity by automatically scanning market data without human intervention.
Solution Approach 2:
The system enables self-service by allowing users to define their own analysis criteria, indicators, and oscillators through configurable parameters. The automated engine then independently executes the analysis and generates trading signals without requiring continuous manual oversight, thus maintaining operational flexibility while improving speed.
2Adaptability or versatility
If manual analysis methods are used, then subjectivity in interpretation is preserved, but measurement precision and reliability of event detection deteriorate
Solution Approach 1:
The patent allows users to modify analysis parameters including indicator periods, oscillator thresholds, and pattern recognition criteria. This configurability preserves the adaptability and subjectivity needed for different trading strategies while the automated execution ensures precise and consistent detection of technical events without human error.
Solution Approach 2:
The system incorporates feedback mechanisms where detection results are continuously refined through neural network learning and genetic algorithm optimization. This allows the system to adapt to different market conditions and user preferences while maintaining high measurement precision through automated validation and adjustment of detection criteria.
3Loss of information
If comprehensive market data is analyzed manually, then completeness of information is maintained, but loss of time and efficiency deteriorate
Solution Approach 1:
The system performs preliminary actions by continuously pre-processing and storing market data in optimized formats before analysis is needed. Technical events are detected in real-time as data becomes available, eliminating the time required for manual data collection and preparation while ensuring all relevant information is captured and analyzed.
Solution Approach 2:
By replacing manual analysis with automated computer-based processing, the system can analyze comprehensive market data including multiple indicators, oscillators, and price patterns simultaneously without the time constraints of human analysis, thus maintaining information completeness while dramatically reducing analysis time.
4Productivity
If automated detection systems are implemented, then productivity increases, but device complexity and false positives worsen
Solution Approach 1:
The patent segments the analysis system into distinct modular components: data collection modules, indicator calculation modules, oscillator analysis modules, pattern recognition modules, and signal generation modules. This segmentation manages device complexity by organizing functions into independent units while maintaining high productivity through coordinated automated operation of all segments.
Solution Approach 2:
The system uses intermediary elements such as standardized data structures, configuration files, and abstraction layers between different analysis components. These intermediaries simplify the interface between complex modules, making the overall system more manageable while preserving the automated detection capabilities that drive productivity.
5Reliability
If multiple indicators and oscillators are analyzed, then reliability of signals improves, but device complexity and processing requirements worsen
Solution Approach 1:
The patent merges multiple indicator and oscillator analyses into a unified technical event detection framework. By combining data from multiple sources and applying data fusion techniques, the system improves signal reliability through cross-validation while managing processing complexity through integrated architecture that handles multiple analyses simultaneously rather than sequentially.
Data Source
AI summary
A method of providing a financial event identification service using a database of fundamental event data or technical event data comprises: receiving a request for fundamental event data or technical event data from a from a client application; querying the database based on the request and client application specific selection criteria to obtain suitable fundamental event data or technical event data; and transmitting the fundamental event data or technical event data to the client application.