Multi-User Stock Chart Analysis Weighting for Consistent Results
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Solution Overview
Problem
Technical analysis in stock trading is highly subjective and varies based on individual experience and skill levels, leading to inconsistent results and increased errors due to limited samples.
Innovation Solution
A chart analysis method and device that receives parameter values from multiple users, determines weights based on profitability and error rates, and provides optimized parameter values using a function or algorithm to ensure the weights sum to 1, thereby reducing errors and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If technical analysis is performed based on individual user experience and skill level, then analysis can be conducted, but the results vary and accuracy is reduced due to subjectivity
Solution Approach 1:
The patent combines parameter values from multiple users into a unified analysis result. By aggregating data from numerous users and applying weightage based on their profitability and error rates, the system merges individual subjective analyses into an objective collective intelligence result, thereby improving accuracy and consistency.
Solution Approach 2:
The system uses feedback mechanisms by calculating error rates and profitability for each user based on past performance, then applying these feedback results to determine weights. Users with lower error rates and higher profitability receive higher weights, creating a self-correcting system that continuously improves analysis accuracy.
2Measurement precision
If parameter values are collected from multiple users, then collective intelligence can be leveraged to improve accuracy, but the system complexity increases
Solution Approach 1:
The patent transforms the complexity management through parameter changes by introducing weightage parameters based on user profitability and error rates. Instead of treating all users equally, the system adjusts parameters dynamically to emphasize more reliable users, simplifying the aggregation process while maintaining high accuracy.
Solution Approach 2:
The system applies local quality by assigning different weights to different users based on their individual performance characteristics. Each user's contribution is weighted according to their specific error rate and profitability, allowing the system to handle variability in user quality without increasing overall system complexity.
3Measurement precision
If weightage is assigned to users based on profitability and error rates, then more accurate parameter values can be determined, but calculation complexity increases
Solution Approach 1:
The system performs preliminary action by pre-calculating user weights based on historical profitability and error rate data before conducting the actual analysis. This preliminary weight determination simplifies the main calculation process, as the system only needs to apply pre-computed weights rather than performing complex real-time optimization.
Data Source
AI summary
The present invention relates to a chart analysis method for successfully leading a transaction by reflecting market psychology, the method comprising the steps of: receiving, from each of a plurality of different users, parameter values for technical analysis of one type stock; determining the weight for each of the plurality of different users with respect to the received parameter values; determining optimum parameter values by using the determined weight and the parameter values received from the plurality of users; and providing the determined optimum parameter values to the users.