The Quant
"Mathematical modeler who finds edge in data."
To you, the market is just a math problem. Emotions are noise; data is truth.
The Numbers Don't Lie
These are the stats that matter for your trading type. Know them. Respect them.
of strategies that look good in a backtest fail in live trading. Overfitting is the silent killer.
Events (which shouldn't happen in a million years) happen every decade. Your risk model underestimates tail risk.
Correlation. In a crash, all correlations go to 1. Your diversification is an illusion when you need it most.
The amount of intuition allowed in a true quant system. If you intervene, you are the bug.
How You Think
You see the matrix. Price isn't value—it's a data point. You trust backtests more than news headlines. You believe that with enough data, you can predict the probability of any outcome.
The Lies Quants Tell Themselves
You've probably said one of these. Here's why it's costing you money.
"I can predict the future with enough data."
You can't. You can only identify probabilities. The market is a complex adaptive system, not a physics problem. Past performance is not indicative of future results.
"If the model loses, the market is wrong."
The market is the reality. Your model is the map. If the map doesn't match the terrain, the map is wrong. Always.
"More variables equals a better model."
This is called "overfitting". A model with too many variables describes the past perfectly and predicts the future terribly. Simplicity is robustness.
Your Superpower
Probability Thinking
You never think in "right or wrong," only in expected value. This makes you nearly immune to emotional tilt.
Your Kryptonite
Curve Fitting
You build models that work perfectly in the past but fail in the future. You struggle when human emotion breaks your algorithm.
Trading Styles That Fit Your DNA
Your Zone
Avoid These
A Day In The Life
You are a scientist in a lab, not a gambler in a casino.
System Check
Verify servers are running. Verify data feeds are connected. The machine does the work.
Research & Alpha Generation
Reading papers, testing a new hypothesis. You aren't watching charts; you're watching code.
Performance Monitoring
Checking the "Expected vs Actual" of your models. Is the slippage within tolerance?
Data Cleaning
Glamorous? No. Essential? Yes. Garbage in, garbage out. You spend 80% of your time here.
Backtesting
Running the new strategy against 10 years of data. Does it hold up?
Optimization
Refining the execution logic. Shaving 10ms off latency or saving 1 bps on fees.
Quants In The Wild
Learn from those who came before you. The wins AND the wipeouts.
Jim Simons
The "Man Who Solved the Market". Founder of Renaissance Technologies. Used code and math to generate 66% annualized returns for 30 years.
Edward Thorp
Beat the blackjack dealers with card counting, then beat the market with statistical arbitrage. The father of quantitative trading.
Long-Term Capital Management (LTCM)Warning
A fund run by Nobel laureates. They thought they had "solved" risk. They leveraged 100:1. They blew up the global financial system.
Red Flags
Be honest. How many of these sound familiar?
The Reality Check
Your Growth Path
Study behavioral finance to understand the "irrationality" your models miss.
Stop tweaking your model every time it has a drawdown.
Accept that black swan events break all gaussian models.
Explore More
Discover how different personalities and styles connect
Other Analysts
Data-driven decision makers
Archetypes You Can Learn From
Cover your blind spots by studying these
