18210852. METHOD AND SYSTEM FOR SIMULATION OF LIMIT ORDER BOOK MARKETS simplified abstract (JPMORGAN CHASE BANK, N.A.)
Contents
- 1 METHOD AND SYSTEM FOR SIMULATION OF LIMIT ORDER BOOK MARKETS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND SYSTEM FOR SIMULATION OF LIMIT ORDER BOOK MARKETS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
METHOD AND SYSTEM FOR SIMULATION OF LIMIT ORDER BOOK MARKETS
Organization Name
Inventor(s)
Andrea Coletta of Ferentino (IT)
Svitlana Vyetrenko of Colts Neck NJ (US)
Tucker Richard Balch of Suwanee GA (US)
METHOD AND SYSTEM FOR SIMULATION OF LIMIT ORDER BOOK MARKETS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18210852 titled 'METHOD AND SYSTEM FOR SIMULATION OF LIMIT ORDER BOOK MARKETS
Simplified Explanation
The abstract describes a method for using an AI model to simulate a limit order book market for studying trading strategies.
- Receiving market information at a specific time
- Determining potential market actions using an AI algorithm
- Training the AI algorithm with historical market data
Potential Applications
This technology could be applied in financial research, algorithmic trading development, and risk management strategies.
Problems Solved
This technology helps in simulating market conditions accurately, testing trading strategies efficiently, and improving decision-making processes in trading.
Benefits
The benefits of this technology include enhanced trading strategy development, improved risk management, and better understanding of market dynamics.
Potential Commercial Applications
The potential commercial applications of this technology include financial institutions, trading firms, and investment companies looking to optimize their trading strategies and risk management processes.
Possible Prior Art
One possible prior art could be the use of traditional market simulation models in financial research and trading strategy development.
Unanswered Questions
How does this technology compare to existing market simulation models in terms of accuracy and efficiency?
This article does not provide a direct comparison with existing market simulation models, leaving the reader to wonder about the specific advantages of this AI-based approach.
What are the potential limitations or challenges in implementing this technology in real-world trading environments?
The article does not address the potential obstacles or limitations that may arise when implementing this technology in actual trading environments, leaving room for further exploration and analysis.
Original Abstract Submitted
A method for using an artificial intelligence (AI) model to simulate a limit order book market in order to facilitate study and evaluation of trading strategies is provided. The method includes: receiving information that relates to a state of the market at a particular time; and determining, based on the information, a potential market action that is expected to occur. The determination is made by applying an AI algorithm that implements a machine learning technique to determine the potential market action. The AI algorithm is trained by using historical data that relates to the market.
