Trade Order Processing With Theoretical Price Indicators
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Solution Overview
Problem
Current trading systems provide insufficient information for investors to make informed trading decisions due to the complexity of modern financial instruments, limiting their ability to assess profitability and risk effectively.
Innovation Solution
A system and method that calculates a theoretical price based on market data and pricing parameters, compares proposed trades with this price, and visually displays profitability and risk indicators to facilitate intelligent trading decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current trading systems display only basic market data (bid/ask), then the system complexity remains low, but the information sufficiency for informed trading decisions deteriorates
Solution Approach 1:
The system segments information presentation by separating theoretical price calculations from market data display. The interface divides profitability indicators (theoretical price vs. market price comparisons) from risk indicators (delta, gamma, vega), allowing comprehensive information delivery without overwhelming complexity. Each segment serves a specific analytical purpose.
Solution Approach 2:
The system adds a new dimension to traditional trading displays by introducing visual spatial relationships. Theoretical price indicators are positioned relative to market bid/ask prices on a graphical interface, creating a visual spectrum that instantly communicates profitability. This dimensional transformation converts abstract numerical comparisons into intuitive spatial relationships.
2Reliability
If comprehensive trade analysis information is provided, then the quality of trading decisions improves, but the ease of operation deteriorates due to information overload
Solution Approach 1:
The interface applies local quality by giving different visual prominence to different types of information based on their importance for quick decision-making. Profitability indicators (theoretical price vs. market price) receive primary visual emphasis, while risk parameters (delta, gamma, vega) are displayed with secondary emphasis. This hierarchical visual organization allows traders to quickly grasp essential information while having access to comprehensive data.
Solution Approach 2:
The system uses color changes to encode profitability status and risk levels. Theoretical price indicators display different colors based on whether they exceed market prices (profitable) or fall below (unprofitable). Visual color coding transforms complex numerical analysis into immediate intuitive understanding, maintaining ease of operation while enhancing decision quality.
3Measurement precision
If theoretical price calculations are performed in real-time, then the profitability assessment accuracy improves, but the processing time increases
Solution Approach 1:
The system performs preliminary action by pre-calculating theoretical prices based on input parameters (spot price, strike price, volatility, interest rates) before the trader needs to assess profitability. The pricing engine continuously updates theoretical prices in the background, so when a trader inputs market data, the comparison is already prepared. This eliminates real-time calculation delays during the decision-making moment.
Solution Approach 2:
The system replaces manual mechanical calculation methods with automated electronic pricing engines. Complex options pricing models (Black-Scholes, binomial trees) are executed automatically by computer algorithms rather than manual calculation, achieving both high precision and rapid processing. This substitution enables real-time theoretical price generation without sacrificing accuracy.
Data Source
AI summary
Systems and apparatus for processing a trade order include a computer configured for receiving market data for a financial asset, receiving pricing parameters and receiving proposed order quantity and price data. The computer is further configured for constructing proposed trades based on the proposed order quantity and price data, and for calculating a theoretical price for the financial asset based on the market data, pricing parameters as well as the proposed order price data. In addition, the computer is configured for comparing the constructed trades with the theoretical price, and displaying market data indicators relative to the theoretical price indicators based on the comparison.