HSBC–IBM Quantum-Enabled Algorithmic Trading
Kartavya Desk Staff
Source: HSBC
Context: HSBC and IBM announced the world’s first quantum-enabled algorithmic bond trading trial.
About HSBC–IBM Quantum-Enabled Algorithmic Trading:
What It Is?
• The trial is the world’s first-known empirical evidence of using a hybrid quantum-classical computing approach to solve a real-world problem in algorithmic bond trading.
• It involved HSBC and IBM, using real, production-scale trading data from the European corporate bond market.
Features:
• Hybrid Approach: The teams utilized a combination of quantum and classical computing resources, rather than quantum computers alone.
• Quantum Augmentation: The IBM Heron quantum processor was used to augment classical computing workflows.
About Algorithmic Trading (Algo Trading):
What It Is?
• Algorithmic trading is the use of computer programs to automatically execute buy or sell orders for securities (like stocks, bonds, futures, or options) based on a predefined set of rules. These rules or criteria are coded based on factors like price, time, volume, or technical indicators.
How It Works:
• Strategy Definition: A trading strategy is designed using technical indicators, historical data, and quantitative models.
E.g., “Buy 100 shares if the 5-minute moving average crosses above the 20-minute moving average”.
• Coding: The strategy logic is converted into an automated computer code (often in Python, Java, or C++).
• Data Feed: The algorithm connects to a live data feed to continuously monitor market prices and conditions.
• Execution: When the predefined criteria are met, the algorithm automatically triggers and sends the order to the broker/exchange in milliseconds, with zero human intervention.
Key Features and Benefits:
• Speed: Executes trades in milliseconds, capturing fleeting price differences.
• Reduced Emotion: Removes human emotional biases (fear, greed) from trading decisions, ensuring consistency.
• Consistency: Adheres strictly to the pre-programmed rules every time.
• Scalability: Allows a trader to run and monitor multiple strategies and asset classes simultaneously.
• Backtesting: Enables strategies to be tested on historical data before live deployment.
Algorithmic vs. Manual Trading:
Feature | Algorithmic Trading | Manual Trading
Speed | Trades executed in milliseconds; ultra-fast. | Trades executed in seconds/minutes; limited by human speed.
Emotions | Zero emotional intervention; purely logic-based. | Susceptible to human emotions (fear, greed).
Consistency | Highly consistent; follows rules exactly. | Varies based on trader’s mood or market sentiment.
Scalability | Can manage multiple strategies and assets simultaneously. | Challenging to monitor and analyse multiple symbols at once.
SEBI Rules on Algo Trading (India):
• Recognised since 2008 and NSE introduced co-location & smart order routing (2011).
• SEBI now mandates: All algo strategies must be approved by exchanges and assigned unique IDs. Brokers responsible for risk controls, audit trails, and client consent. Discourages unauthorised third-party black-box algos.
• All algo strategies must be approved by exchanges and assigned unique IDs.
• Brokers responsible for risk controls, audit trails, and client consent.
• Discourages unauthorised third-party black-box algos.