Sep 9 in General discussion
Uncovering Hidden Relationships in Finance Using AI and Graph Theory
I wanted to share something interesting I've been working on, combining AI and finance using graph theory to analyze how different financial assets influence each other. Essentially, what I’ve done is write code that looks at the relationships between stocks, currencies, and other assets to figure out which ones tend to "lead" or "lag" in their movements. It’s like a map of influence, showing how changes in one stock might predict changes in another. This can help us understand the market in a deeper way and even spot trends that aren’t immediately visible.
For example, imagine Apple tends to rise just before Microsoft. By analyzing historical data, the code will detect that relationship and show how Apple "leads" Microsoft. The cool part is that it visualizes these relationships in a network graph, so we can easily see how different assets are connected. It’s a way to simplify the massive amount of data we deal with in financial markets into something we can understand and act on.
This approach also allows us to group similar assets together. Using AI and clustering techniques, we can break down the complex financial web into more manageable clusters. Whether you're new to finance or AI, the goal is to use data and patterns to make better sense of the world around us. I’m excited to see how these tools can help us all understand the markets in new ways and make more informed decisions. Let me know what you think and if you have any questions!
We demonstrate the relationships with the past 2 years of data on the left, and how it has changed in the past 6 months on the right
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Uncovering Hidden Relationships in Finance Using AI and Graph Theory
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MarketMatrix AI is a community exploring the fusion of AI, finance, and knowledge graphs to simplify data and gain insights into human decision-making
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