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Graham Quant Log

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Summary

This article discusses the potential use of ChatGPT, a large language model developed by OpenAI, in systematic trading. It explains the concept of natural language processing (NLP) and how it has been used to build signals for trading. The article also tests ChatGPT's ability to analyze two sentences from the financial news and provides a distribution of sentiment scores for each sentence. In conclusion, it is argued that ChatGPT's wide range of output for the same input makes it unsuitable for systematic trading decisions.

Q&As

What is ChatGPT?
ChatGPT is a "Large Language Model" (LLM) developed by OpenAI that has been trained on a massive dataset of text and has learned to generate human-like responses to various types of queries and prompts.

How has ChatGPT been used in relation to systematic trading?
Natural Language processing (NLP) has been used in some form or another in helping to build signals that can be used for trading stocks, futures and other financial markets. The "bag of words" approach is one of the simplest NLP techniques where text is scanned for keywords that are linked - typically by the user - to a positive or negative score.

What is the "bag of words" approach to NLP?
The "bag of words" approach to NLP is where text is scanned for keywords that are linked - typically by the user - to a positive or negative score.

How did ChatGPT respond to requests to analyze two sentences about gold and natural gas prices?
ChatGPT responded to the requests to analyze the two sentences about gold and natural gas prices by providing numerical sentiment scores between -100 and 100. For the gold sentence, the sentiment score was around -70, and for the natural gas sentence, the sentiment score was around -60.

Are ChatGPT's capabilities suitable in its current form for systematic trading?
No, ChatGPT's capabilities are not suitable in its current form for systematic trading due to the wide range in outputs for the same input, once non-trivial text inputs are used.

AI Comments

👍 This article provides a thorough analysis of the capabilities of OpenAI's ChatGPT and whether it can be used in systematic trading. The author explains the different techniques used in NLP and provides an example of how ChatGPT can be used to analyze a sentence.

👎 Despite the author's analysis, the article does not provide any concrete evidence to support the idea that ChatGPT can successfully be used in systematic trading. The author also fails to address the potential risks and challenges associated with using an AI-based system.

AI Discussion

Me: It's about ChatGPT, which is a new AI that has been released by OpenAI. It discusses whether ChatGPT, or algorithms like it, could be useful in systematic trading.

Friend: That's really interesting. What are the implications of this article?

Me: The article discusses the potential of using ChatGPT in systematic trading. It suggests that the tool can provide sophisticated responses to complex questions and may be able to replace certain types of professions. However, the article also cautions against using it as is due to its wide range of outputs for the same input. It also points out that transparency of decisions is important in systematic trading, which is something that modern machine learning algorithms may not provide.

Action items

Research other natural language processing techniques and their potential applications in systematic trading.
Experiment with ChatGPT to determine if it can be used in systematic trading strategies.
Develop a strategy for using ChatGPT to analyze complex sentences and determine numerical sentiment ratings.

Technical terms

Natural Language Processing (NLP): A field of computer science that uses algorithms to process and analyze natural language (i.e. human language).
Large Language Model (LLM): A type of artificial intelligence (AI) model that is trained on a large dataset of text and is able to generate human-like responses to various types of queries and prompts.
Bag of Words: A technique used in natural language processing where text is scanned for keywords that are linked to a positive or negative score.
Hawkish: A term used to describe a central bank's monetary policy that is more aggressive than usual.
Inventory Report: A report that provides information on the quantity of goods and materials held in stock by a company.
Supply/Demand Imbalance: A situation in which the demand for a product or service is greater than the supply, or vice versa.