Everything I teach, lesson by lesson.

You'll be able toKnow who takes the other side of your trade, what it costs before price moves a tick, and why your instrument decides how precisely you can size.

Almost every trader starts in the middle: a strategy, a broker, a chart. This part starts underneath that, at the mechanics nobody explains because they are not exciting enough to sell.

By the end of it you will know what you are actually buying when you place a trade, who is on the other side of it, what it costs you before the market has moved a single tick, and why the instrument you choose quietly decides how precisely you can manage risk later.

The pointYou begin every trade behind. An edge is not what makes you money, it is what has to be big enough to pay the costs first and still leave something over.

You'll be able toMeasure an edge the way professionals do: expectancy in R, and how many trades it takes before a result means anything.

This is the part that costs people the most to learn on their own, usually across several years and several blown accounts.

It replaces the idea of a good trade with the idea of a good process, and it introduces the single number that decides whether any strategy is worth trading at all. Everything after this part is machinery built to serve one idea from this one.

The pointExpectancy is the only number that decides whether a strategy is worth trading. Win rate on its own tells you nothing, and it is the number every beginner optimises first.

You'll be able toChoose between systematic and discretionary from an honest look at your time and your coding, then commit to one lane.

The most consequential decision in the program, and the one most people avoid making. Refusing to choose is itself a choice, and it is the one that produces a discretionary trader with a system's expectations.

This part defines both lanes honestly, kills the myth that discretionary means improvised, and then makes you commit. Every part after this one splits into a track.

The pointYou commit to one lane first, fully, and you are allowed to run the other later. What does not work is running both badly at once and blaming the market for the inconsistency.

You'll be able toTurn structure, liquidity, FVGs and SMT into a written setup or an EA, with every rule precise enough to be tested.

This is where a vague idea becomes a specification precise enough to be proven wrong. That precision is the entire point: an idea you cannot invalidate is not a strategy, it is a belief.

The theory here is deliberately compressed. You get exactly as much market structure as it takes to define one entry unambiguously, and not one lesson more of lore.

The pointWrite the strategy so precisely that a stranger reading it would take the same trades you would. Until it passes that test, it cannot be backtested honestly, because you will unconsciously interpret it in your own favour.

You'll be able toTest a strategy the way quant researchers do: out-of-sample data, walk-forward, deflated Sharpe and the probability of overfitting.

Backtesting is not a formality you perform before trading a strategy you have already decided to trade. Done properly it kills most of your ideas, and that is what it is for.

This part covers both tracks, then spends real time on the ways a backtest lies to you, because a confidently wrong backtest is more expensive than no backtest at all.

The pointIf you tuned a parameter after seeing the result, that result is no longer evidence. Out-of-sample data is the only opinion in the room that has not been bribed.

You'll be able toSize every trade from your stop and the firm's limits, and feel your risk of ruin before a plan ever goes live.

An edge tells you whether you make money over a large sample. Risk decides whether you are still trading when that sample arrives. They are separate problems and the second one is more urgent.

This part is arithmetic, and it is the arithmetic that most funded accounts are lost to.

The pointSizing up when you are winning feels like confidence and behaves like a countdown. Static risk is not timidity, it is the only setting that lets a positive expectancy actually compound.

You'll be able toRead any firm's rulebook as arithmetic: the reward-to-risk it implies, how many losses you can afford, and when you actually get paid.

A prop firm is a business with a published set of constraints. Once you can read those constraints as arithmetic, an evaluation stops being a test of nerve and becomes a problem with a correct approach.

This part also covers the thing the industry does not advertise: that the firm is your counterparty, and counterparties can change rules, delay payouts, or fail.

The pointThe evaluation and the funded account are two different games with two different optimal strategies. Playing the funded account the way you played the evaluation is how most people lose the account they just earned.

You'll be able toMove from backtest to live in phases, and keep a journal that catches a broken strategy early.

Everything to this point can be done at a desk with no money at risk. This part is about the moment that stops being true.

The psychology here is grounded in decision-making rather than affirmations. The useful frame is borrowed from poker: judge the decision, not the outcome, because over a large enough sample only one of those is under your control.

The pointJudge the decision, not the outcome. A good trade that lost is still a good trade, and a rule you broke that happened to pay is the most expensive win you will ever have.

You'll be able toScale by adding funded accounts paid for by payouts, never by raising your risk.

The instinct once something works is to make it bigger by risking more per trade. That instinct has ended more funded accounts than any losing strategy.

Scaling here means more accounts, not more risk, and the arithmetic strongly favours it: adding accounts increases return while actually reducing the volatility of the total.

The pointPayouts buy evaluations, evaluations become funded accounts, funded accounts produce payouts. Risk per trade is a constant in that loop, and the moment it becomes a variable the loop breaks.