Stock Price Support-Resistance Forecasting With Recursive Lines
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Solution Overview
Problem
Current stock market forecasting and analysis systems are rudimentary and lack the ability to accurately predict support and resistance levels, leading to suboptimal trading decisions.
Innovation Solution
A computer-based method using recursive line value variables and associated factors to analyze high, low, or closing prices, creating support and resistance lines that predict future price levels, with graphical display on a monitor screen.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If recursive line value variables with multiple factors are used to create support and resistance lines, then the accuracy of predicting support and resistance levels is improved, but the device complexity increases
Solution Approach 1:
The patent segments the analysis by creating multiple recursive line value variables (24 support lines and 24 resistance lines) with different associated factors. Each line represents a different prediction model with varying sensitivity and time-weighting characteristics, allowing the system to handle complex market behavior through divided, specialized components rather than a single monolithic model.
Solution Approach 2:
The patent applies parameter changes by varying the associated factors (from 2^-12 to 2^0) assigned to different recursive line variables. These factors control the weight and responsiveness of each line, allowing the system to adapt to different market conditions and time horizons. The factors transform the raw price data into multiple scaled predictions, enhancing accuracy without requiring a completely different analytical approach.
2Reliability
If multiple recursive line value variables with different factors are created, then the reliability of trading predictions is improved, but the ease of operation deteriorates
Solution Approach 1:
The patent creates a universal analysis system where the same recursive calculation framework can generate multiple types of predictions (support lines, resistance lines, extreme values, crossing indicators) using identical processing logic. This multi-functional approach allows the system to handle various prediction needs through a single unified methodology, maintaining ease of operation while improving reliability through comprehensive analysis.
Solution Approach 2:
The patent incorporates feedback mechanisms through crossing indicator variables that monitor when price interacts with the recursive lines. The system continuously updates line values based on incoming price data and uses crossing indicators to signal when predictions are most relevant. This feedback loop allows the system to maintain high reliability by adapting to real-time market conditions while keeping the operation simple through automated continuous processing.
3Productivity
If detailed recursive calculations with multiple factors are performed, then the productivity of trade decision-making is improved, but the loss of time in data processing increases
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing the recursive line values and crossing indicators as price data becomes available. The system continuously maintains the recursive lines in memory, so when a trading decision is needed, the analysis is already prepared. This allows rapid trade decision-making without requiring time-consuming real-time calculations, as the complex recursive mathematics are performed in advance as data streams in.
Solution Approach 2:
The patent ensures continuity of useful action by maintaining the recursive line value calculations as an ongoing process that runs continuously with incoming price data. Rather than performing calculations only when needed, the system continuously updates the 24 support and 24 resistance lines, keeping the analysis ready for immediate use. This continuous processing minimizes delays while maintaining the high productivity benefits of detailed recursive analysis.
Data Source
AI summary
The present invention provides improved methods for predicting the future price levels of a traded stock, commodity, index, foreign exchange (forex), or other asset. Advantageously, the invention provides results in graphical charts that are readily understood. By using the improved methods of the invention, stock technical analysts and traders can make better informed decisions about when to purchase or sell a stock, security, or other asset.


