What Is Backtesting and Why Every Trader Should Care
Backtesting replays your trading rules over historical data to answer one question: would this idea have actually made money?
Practical writing on backtesting, position sizing, AI-assisted trading, and strategy design. Written for novice and intermediate retail traders — not finance PhDs.
Backtesting replays your trading rules over historical data to answer one question: would this idea have actually made money?
Big losses get attention. The slow ones — oversizing, no plan, fees, FOMO, no journal — are what actually empty most retail accounts.
Which to start with depends on when you have time to trade, how much volatility you can stomach, and what you actually want to learn.
A strategy starts as a sentence. If you can say it out loud and have someone understand you, you are 80% of the way to a testable rule.
You can pick winners 70% of the time and still go broke if you size wrong. Position sizing is what keeps traders in the game long enough to compound.
Three biases — overfitting, look-ahead, and survivorship — show up in nearly every amateur backtest. Here's how to spot them.
Two of the three costs you pay on every trade are invisible on your statement. Here's how to see them — and what they do to your edge.
Which metric matters most depends entirely on what you are trying to build. Most beginners look at the wrong one first.
Almost every quantitative strategy is a flavor of one of two ideas. Pick the wrong family for the wrong market and you will be confused for months.
An AI agent is good at patience and consistency. It is bad at context and judgment. Knowing which one you are facing in any moment is the entire skill.
Trove turns one sentence into a live trading strategy. Backtest in 30 seconds, then let the AI run it for you.