Neural Network Trading System with Fuzzy Logic Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing trading systems lack the ability to dynamically analyze market behavior, generate effective trading strategies, and incorporate fundamental analysis and news impact in real-time, leading to inefficiencies in detecting profitable patterns and calculating correlations between financial symbols and pairs.
Innovation Solution
A computer-implemented system utilizing a neural network with multiple layers processes financial market data to generate technical analysis, trading signals, and market reports, incorporating a strategy generator, technical analysis processor, fundamental analysis, and correlation coefficient calculations to provide dynamic trading strategies and real-time notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional trading systems use static and fixed strategies with limited patterns and indicators, then the system structure is simple and easy to implement, but the success rate of trading signals is lost over time and the system cannot adapt to changing market conditions
Solution Approach 1:
The patent implements dynamic strategies that automatically adapt to changing market conditions by using multiple timeframes and regenerating strategies based on current market state. The system transitions from static fixed strategies to dynamic adaptive strategies that evolve with market behavior, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The patent applies nesting by incorporating multiple levels of analysis within the trading system - multiple timeframes (M1, M5, M15, M30, H1, H4, D1) are nested within each other, and multiple indicators are nested within strategies. This nested structure enables adaptability while organizing complexity in a manageable hierarchical framework.
2Measurement precision
If traders manually monitor financial market price charts to detect suitable spots for placing orders, then the analysis can be thorough and consider multiple factors, but traders have insufficient time to monitor all symbols and pairs
Solution Approach 1:
The system implements self-service by automatically generating trading signals and analyzing market conditions without requiring continuous manual monitoring. The automated system performs detection and analysis functions that would otherwise require human traders to spend extensive time watching charts, thereby resolving the contradiction between detection accuracy and monitoring efficiency.
Solution Approach 2:
The patent replaces the mechanical manual monitoring process with an automated computer-based system that uses algorithms and indicators to detect trading patterns. This substitution maintains high detection accuracy while dramatically improving productivity by eliminating the time constraint of manual chart watching.
3Reliability
If traders rely on years of profound experience and financial knowledge to place orders on distinguishing technical analysis patterns, then the trading strategy can be well-informed and robust, but the system cannot operate without human expertise and is difficult to scale
Solution Approach 1:
The patent copies the knowledge and expertise of experienced traders into a computer-based system through predefined indicators, patterns, and strategies. Instead of requiring human traders to possess years of experience, the system embeds this expertise in programmable forms that can be replicated and executed automatically, thereby increasing both automation level and maintaining reliability.
Solution Approach 2:
The system transforms qualitative trading knowledge into quantitative parameters and measurable indicators that can be processed computationally. By converting expert judgment into measurable parameters like RSI values, MACD signals, and pattern recognition metrics, the system achieves high reliability through automation without requiring human expertise for each trading decision.
4Productivity
If conventional systems generate technical analysis and trading signals based on limited patterns and indicators with static strategies, then the system is simple to implement, but the success rate is lost over time due to static structure
Solution Approach 1:
The patent implements dynamic strategy generation that adapts to current market conditions rather than relying on static predefined strategies. The system regenerates trading signals based on real-time market state across multiple timeframes, maintaining high success rates over time while preserving rapid signal generation capability.
Solution Approach 2:
The system ensures continuous generation and updating of trading signals based on ongoing market analysis. Rather than using fixed strategies that become obsolete, the system continuously adapts and regenerates signals, maintaining both high productivity in signal generation and sustained reliability over time through uninterrupted adaptive analysis.
Data Source
AI summary
A system for intelligent market trading implemented with a neural network system (Machine Learning) comprising an input, one or more processors and an output. The input comprises a database of price of a symbol and a pair in a timeframe. The first processor is configured to receive the respective input to generate a technical analysis, a trading signal, and a market report with a probability value. The second processor generates a coefficient for regulating the probability value of the generated trading signals and technical analysis using fuzzy logic systems alongside of a neural network system. The third processor computes the correlation coefficient of symbols under Mesh topology and regulates the resultant probability value of each trading signals and technical analysis. The output comprises a processor to receive and evaluate the individual resultant probability values of the generated trading signals and technical analysis and delivers an output data. The output data is sent via notification to a user for detecting a suitable spot for placing their orders in the financial market.