20240046352. MODULAR BLOCKCHAIN-IMPLEMENTED COMPONENTS FOR ALGORITHMIC TRADING simplified abstract (Tradegen LLC)

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MODULAR BLOCKCHAIN-IMPLEMENTED COMPONENTS FOR ALGORITHMIC TRADING

Organization Name

Tradegen LLC

Inventor(s)

Xavier Enrique Negron of Austin TX (US)

MODULAR BLOCKCHAIN-IMPLEMENTED COMPONENTS FOR ALGORITHMIC TRADING - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240046352 titled 'MODULAR BLOCKCHAIN-IMPLEMENTED COMPONENTS FOR ALGORITHMIC TRADING

Simplified Explanation

The patent application describes a method and system for algorithmic trading using self-executing contracts on a blockchain network. Here are the key points:

  • Self-executing contracts are deployed on a blockchain network to provide indicators and comparators.
  • Indicators process external asset data to obtain indicator values.
  • Comparators process indicator values to determine if a comparator condition is met.
  • A trading bot is generated on the blockchain network to implement predetermined trading rules based on the output of the comparators.
  • The trading bot can execute simulated trades according to the predetermined trading rules.

Potential applications of this technology:

  • Algorithmic trading: The system can be used to automate trading decisions based on predefined rules and indicators.
  • Financial markets: The technology can be applied to various financial markets, such as stocks, cryptocurrencies, and commodities.

Problems solved by this technology:

  • Manual trading: The system eliminates the need for manual trading decisions by automating the process based on predefined rules.
  • Emotional bias: By relying on objective indicators and comparators, the system reduces the impact of emotional bias in trading decisions.

Benefits of this technology:

  • Efficiency: Algorithmic trading allows for faster execution of trades compared to manual trading.
  • Accuracy: The system uses objective indicators and comparators to make trading decisions, reducing the potential for human error.
  • Consistency: The predetermined trading rules ensure consistent execution of trades without being influenced by emotions or external factors.


Original Abstract Submitted

example methods and systems are directed to providing an algorithmic trading system. one or more self-executing contracts are deployed on a blockchain network to provide at least one indicator and at least one comparator. each indicator processes external asset data to obtain indicator values. each comparator processes one or more of the indicator values to obtain output indicating whether a comparator condition is met. a trading bot is generated on the blockchain network to implement predetermined trading rules by using the output of at least one comparator. the trading bot may execute simulated trades according to the predetermined trading rules.

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