Accumulation Distribution Indicator for Financial Price Prediction
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Solution Overview
Problem
Current financial product pricing methods, relying on average closing prices, fail to provide comprehensive market information, leading to incomplete decision-making due to the lack of intra-market data analysis tools and manual processes for traders.
Innovation Solution
A method using the accumulation distribution indicator and interval to predict financial product prices, incorporating a flexible algorithm that calculates and displays real-time data, including breakout marks, to provide a reliable reference for price changes and enhance user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional average closing price method is used for pricing, then simplicity is maintained, but comprehensive market information is lost
Solution Approach 1:
The patent segments the price movement from opening to closing into multiple intervals, analyzing price distribution at different stages rather than treating the entire period as a single average value. This segmentation reveals intra-market information about active regions and volume distribution that the conventional method obscures.
Solution Approach 2:
The patent introduces a new dimension of analysis by creating accumulation distribution indicators that track volume-weighted price positions across different time intervals. This adds depth to the pricing information beyond simple time-based averaging, providing multi-dimensional market insights.
2Measurement precision
If manual processes are used to analyze intra-market information, then detailed price analysis is possible, but time consumption increases significantly
Solution Approach 1:
The system performs automated calculation and analysis of accumulation distribution indicators, volume-weighted average prices, and intra-market statistics without requiring manual data entry or analysis. The computational system serves itself by processing market data automatically, delivering precise analysis results instantly.
Solution Approach 2:
The patent replaces manual mechanical processes of recording and analyzing price data with automated computational algorithms. The system calculates accumulation distribution indicators and identifies active price regions automatically, substituting human analytical effort with machine-based processing that is both precise and time-efficient.
3Device complexity
If no systematic analysis tool is developed, then system complexity remains low, but decision-making reliability decreases
Solution Approach 1:
The system pre-calculates and stores accumulation distribution indicators, volume-weighted average prices, and identifies active price regions in advance, preparing reference information before trading decisions are needed. This preliminary analysis provides reliable data foundations for decision-making without requiring complex real-time computation during critical moments.
Solution Approach 2:
The patent introduces accumulation distribution indicators as intermediary elements that mediate between raw market data and trading decisions. These indicators serve as intermediate analytical products that translate complex market dynamics into actionable insights, improving decision reliability without requiring the end user to directly process raw data.
4Ease of operation
If average closing price is used as trade price, then ease of operation is maintained, but market fairness and accuracy are compromised
Solution Approach 1:
The patent changes the pricing parameter from simple time-based average closing price to volume-weighted accumulation distribution indicators. This parameter transformation maintains operational simplicity by providing clear reference prices while significantly improving accuracy by weighting prices according to actual trading volume and distribution across different time intervals.
Data Source
AI summary
A method for predicting a financial product price based on an accumulation distribution indicator includes the following steps: step S1: inputting, by a user, a ticker symbol; step S2: calculating, by a system, an accumulation distribution indicator value based on daily trade data; step S3: calculating an accumulation distribution interval and an average candlestick; step S4: determining whether the accumulation distribution indicator breaks through the accumulation distribution interval upward or downward; if the accumulation distribution indicator breaks through the accumulation distribution interval upward or downward, going to step S6, otherwise, going to step S5; step S5: displaying a chart with the average candlestick; and step S6: displaying a breakout mark, where the breakout mark is a rising mark if an upward breakout occurs or is a falling mark if a downward breakout occurs, and displaying the chart with the average candlestick.