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Software that finds patterns in market data on its own and refines its guesses as it sees more data, instead of following rules a person wrote by hand.
Why It Matters
In a rules-based algorithm, a human writes the logic. In a machine-learning approach, the human instead feeds the software many examples and lets it infer the pattern — the way a spam filter learns from labeled emails. Applied to markets it's powerful but slippery: financial data is noisy, mostly randomness, and constantly shifting, which makes overfitting extremely easy and honest edges rare. Machine learning is a tool for finding patterns, not a machine that prints money.
Key Points
- Learns patterns from data instead of following hand-written rules
- Markets are noisy and change, so overfitting is a constant danger
- A pattern-finding tool, not a guaranteed edge
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Where AI & Machine Learning Fit
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Common Questions
Software that finds patterns in market data on its own and refines its guesses as it sees more data, instead of following rules a person wrote by hand. In a rules-based algorithm, a human writes the logic. In a machine-learning approach, the human instead feeds the software many examples and lets it infer the pattern — the way a spam filter learns from labeled emails.
In a rules-based algorithm, a human writes the logic. In a machine-learning approach, the human instead feeds the software many examples and lets it infer the pattern — the way a spam filter learns from labeled emails. Applied to markets it's powerful but slippery: financial data is noisy, mostly randomness, and constantly shifting, which makes overfitting extremely easy and honest edges rare. Machine learning is a tool for finding patterns, not a machine that prints money.
Learns patterns from data instead of following hand-written rules
Markets are noisy and change, so overfitting is a constant danger
A pattern-finding tool, not a guaranteed edge