Multi-Stage Stock Filtering for Volatile Market Selection
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Solution Overview
Problem
The increasing volatility in trading markets has made long-term buy and hold strategies less effective, while more dynamic strategies are often complex and exclusive to trained professionals, posing challenges for traders in managing risk and navigating market fluctuations.
Innovation Solution
A program and method to analyze prior day trading stocks, filtering out a small list of stocks with high probability of significant price changes, using multiple sub-filters to identify stocks with deep valleys and high peaks, and dynamically updating their performance metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic trading strategies are used to adapt to market volatility, then trading performance can be improved, but the complexity of the strategy increases making it accessible only to trained professionals
Solution Approach 1:
The patent segments the complex task of stock selection into multiple filter stages (primary filter, secondary filter, tertiary filter), each handling specific aspects of analysis. This breaks down the professional-grade strategy into manageable components that can be systematically applied without requiring deep expertise in each individual filter criterion.
Solution Approach 2:
The patent introduces an intermediary filtering system that sits between the overwhelming amount of raw stock data and the trader's decision-making process. This intermediary automatically applies multiple layers of filtering criteria, translating complex market analysis into a simple list of recommended stocks that traders can act on without needing to understand the underlying complexity.
2Measurement precision
If comprehensive stock analysis is performed on a large number of stocks, then the quality of trading decisions improves, but the time and computational resources required increase significantly
Solution Approach 1:
The patent divides the analysis of hundreds of stocks into sequential filter stages, where each stage processes a subset of stocks with specific criteria. This segmentation allows comprehensive analysis to be performed systematically across the entire universe of stocks without requiring all analyses to be completed simultaneously, thereby reducing total analysis time while maintaining thoroughness.
Solution Approach 2:
The patent performs preliminary filtering actions before detailed analysis. The primary and secondary filters eliminate clearly unsuitable stocks early in the process, so that comprehensive analysis resources are concentrated only on the most promising candidates. This preliminary action maintains high analysis quality for relevant stocks while avoiding waste of time on unlikely candidates.
3Measurement precision
If multiple filtering criteria are applied to narrow down stock selections, then the accuracy of identifying favorable stocks increases, but the complexity of the filtering system increases
Solution Approach 1:
The patent segments multiple filtering criteria into distinct, organized filter stages (primary, secondary, tertiary), with each stage containing specific criteria grouped by their functional purpose. This segmentation maintains high selection accuracy by applying all necessary criteria while organizing them in a structured manner that reduces perceived and actual system complexity.
Solution Approach 2:
The patent implements dynamic filtering where the application and weighting of criteria can adapt based on market conditions and stock characteristics. This dynamic approach maintains high accuracy by adjusting to different scenarios while keeping the system manageable through automated decision rules that reduce the cognitive complexity for users.
Data Source
AI summary
A method for stock monitoring and trading, where an unfiltered set of potential stocks of interest each having a unique stock identifier is established. The unfiltered set contains greater than one hundred unique stocks. The unfiltered set is filtered via a primary filter to create a post-primary-filtered stock set having a primary quantity. The primary filter substantially ensures that the post-primary-filtered stock set contains unique stocks with an average (close-low) percentage change greater than three (3) percent (%). The primary quantity is at most five (5). The post-primary-filtered stock set simultaneously displays unique stocks contained therein for a given day. That is, the displaying simultaneously displays and recurringly updates for each unique stock in the post-primary-filtered stock set at least percentage change from low and a percentage change from high for each of the unique stocks in the first filtered set.