Resources

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Plain guides on testing a trading idea, sizing a position, and passing a prop firm challenge. Written for traders, in ordinary words, with the maths shown where it matters.

What the research says 5

The numbers on how retail traders actually do, taken from regulators and peer reviewed studies rather than from anyone selling a course.

Why you sell winners and hold losers 10,000 accounts were examined. A position in profit was more than 50 percent more likely to be closed than one in loss, and it cost them 3.4 percent a year. What overconfidence costs a trader 35,000 households, split by expected confidence. The more confident group traded 45 percent more and gave up nearly a point more a year for it. What percentage of traders lose money Europe's regulator made brokers hand over their numbers. Between 74 and 89 percent of retail accounts lost money, and the average loss ran into thousands. Can you day trade for a living Two studies tracked hundreds of thousands of real day traders. 97 percent of those who kept at it lost money, and under 1 percent were reliably profitable. Does trading more often make you more money 66,465 households were tracked for six years. The ones who traded most earned 11.4 percent a year while the market returned 17.9 percent.

Backtesting 7

How to test a trading idea against history, and how to tell whether the result means anything.

What backtesting is, and what it can and cannot tell you Backtesting means checking a trading idea against history before you risk money on it. Here is what it proves, what it does not, and where it misleads people. How to backtest a trading strategy, step by step A plain walkthrough of manual backtesting. Write the rules down, pick the data, replay it bar by bar, record every trade, then read the result honestly. How many trades do you need before a backtest means anything Ten trades settle nothing. Here is why small samples mislead, and how to tell a real result from a lucky one. In sample and out of sample testing, explained simply Splitting the data is the cheapest way to catch a strategy that only works on the history it was built from. Here is the method and how to read the outcome. Overfitting: how to tell a real edge from a curve fit Overfitting is what happens when you tune a strategy until it fits the past perfectly. Here is what causes it and how to catch it in a result before trusting it. How far back should you backtest How much history a test needs depends on trade frequency and on which market conditions have to be covered. Here are the rough numbers and the reasoning. Why your backtest beat your live results Almost everyone trades worse live than in testing. Here are the seven reasons why, and which of them you can actually fix.

Risk and position sizing 4

How much to put on a trade, what a normal losing run looks like, and the maths that decides whether you survive one.

Position sizing, explained without the jargon How to work out how much to trade. The percent risk method, the maths behind it, and why sizing decides survival more than entries do. Risk of ruin, and the drawdown you should expect Even a winning strategy can lose everything at the wrong size. Here is what risk of ruin means, what drives it, and how to keep it near zero. Risk to reward and win rate: the trade off nobody explains A high win rate is not the goal. Here is how win rate and reward to risk fit together, and the break even table you can check your strategy against. What a normal losing streak looks like Long losing runs are a normal feature of a working strategy. Here is how long a run to expect at your win rate, and how to tell a normal one from a real problem.

Prop firm challenges 3

What the rules actually mean, why most people fail, and how to practise a challenge before you pay for one.

Why most people fail prop firm challenges It is rarely the profit target that stops people. Here are the real reasons challenges fail and what to do differently. Daily drawdown limits, and what trailing really means Static, trailing and end of day drawdown limits behave very differently. Here is how each one works with a worked example. Prop firm rules explained in plain words Profit targets, loss limits, minimum days, consistency rules and payout splits. What each rule means and which ones actually catch people out.

Test it on what actually happened

Replay any market from any date and find out whether the thing you believe about your trading is true.

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