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Making trading decisions from math, data, and statistics rather than gut feeling or a story about a company.
Why It Matters
Quantitative (or 'quant') trading treats markets as a data problem. Instead of asking 'do I believe in this company?', a quant asks 'what does the data say tends to happen when these measurable conditions appear?' The approach leans on statistics, probability, and testing. Algorithmic trading is usually how a quant strategy gets executed — the quant designs the rules, and an algorithm runs them.
Key Points
- Decisions driven by data and statistics, not narrative or intuition
- Relies heavily on testing and probability rather than single predictions
- Often executed through algorithmic trading once the rules are set
Related Terms
Common Questions
Making trading decisions from math, data, and statistics rather than gut feeling or a story about a company. Quantitative (or 'quant') trading treats markets as a data problem. Instead of asking 'do I believe in this company?', a quant asks 'what does the data say tends to happen when these measurable conditions appear?' The approach leans on statistics, probability, and testing.
Quantitative (or 'quant') trading treats markets as a data problem. Instead of asking 'do I believe in this company?', a quant asks 'what does the data say tends to happen when these measurable conditions appear?' The approach leans on statistics, probability, and testing. Algorithmic trading is usually how a quant strategy gets executed — the quant designs the rules, and an algorithm runs them.
Decisions driven by data and statistics, not narrative or intuition
Relies heavily on testing and probability rather than single predictions
Often executed through algorithmic trading once the rules are set