Quantitative Trading
A concise introduction to quantitative trading and how rule-based, data-driven workflows differ from discretionary or purely narrative decision making.
What is quantitative trading?
Quantitative trading uses data, rules, and systematic logic to evaluate or execute market ideas.
Instead of relying only on discretionary judgment, it tries to make the research or trading process more structured and repeatable.
What makes it “quantitative”
A workflow becomes quantitative when it can express assumptions in a measurable way, such as:
- signal thresholds
- scoring logic
- ranking systems
- historical comparisons
- rule-based triggers
Why people use it
Quantitative approaches can help reduce inconsistency and make assumptions easier to test.
They are often useful for:
- screening opportunities
- comparing many assets
- standardizing research logic
- studying how a rule behaves over time
What quantitative trading does not guarantee
Being systematic does not make a strategy safe. Poor rules, unstable data, or weak assumptions can still fail.
That is why quantitative workflows still need review, context, and risk management.
Related terms
Multi-Agent Trading
A high-level explanation of multi-agent trading workflows and why multiple specialized agents can be useful in AI-driven research systems.
Risk Management
A practical explanation of risk management in trading and research workflows, including why it matters even when signals look strong.
Technical Analysis
Learn what technical analysis means, what kinds of signals it relies on, and how it fits into a broader multi-agent research workflow.
How to cite this page
APA:
TradingAgents Team. (2026). Quantitative Trading. Retrieved from https://www.tradingagents-cn.com/en/glossary/quantitative-trading/ MLA:
TradingAgents Team. "Quantitative Trading." TradingAgents, 2026, www.tradingagents-cn.com/en/glossary/quantitative-trading/.
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