Position sizing, stop placement, drawdown control and protecting your capital.

How moving your stop to entry removes a trade's risk — the real trade-offs, when to use it, and how to do it well.

How correlated pairs multiply your real exposure — and how to manage the hidden concentration.

Why the leverage you actually use — position size vs your equity — matters far more than the broker's maximum.

Why even a profitable system has long runs of losses, how win rate sets streak length, and how to survive them intact.

How scheduled events cause volatility, spread-widening, gaps and jumped stops — and how to defend your account.

Why your total open risk across all positions matters as much as per-trade risk.

How adding to a winning position can compound gains — the rules that keep it safe, and why it's the opposite of averaging down.

Expressing every trade as a multiple of its initial risk — the R-distribution and expectancy in R.

Why return per unit of risk matters — the Sharpe, Sortino and Calmar ratios, and their limitations.

Why controlling losses matters more than predicting wins — the foundation of lasting in the market.

The probability of blowing up — how edge and risk per trade decide whether you survive.

Why the order of your trades changes your drawdown and risk of ruin — and how to size to survive it.

Why a planned exit matters, the main ways to set a target, and the run-it vs lock-it tension.

Why your fill differs from your expected price, what causes it, and why stop-losses can slip.

Why stops cluster beyond obvious levels and get swept — manipulation or liquidity, and how to place stops better.

Why risking ≤1% of your account per trade keeps losing streaks survivable — and how to size positions by it.

Why too much leverage is the number-one account killer, and how position size is the real control.

How this classic metric measures return per unit of risk, why a smoother curve scores higher, and its limitations.

What to record, why it matters, and the feedback loop that turns trading into a skill.

How a stop that follows a winning trade locks in profit, plus break-even stops and the trade-off.

Why short-term results are luck, skill emerges over large samples, and you must judge process not outcomes.

Why adding to losers is so seductive and so dangerous — and how it differs from planned scaling.

Why markets have fat tails, why extremes happen more than expected, and how to survive them.

Reading the graph of your account over time as a diagnostic — and the limits of equity-curve trading.

Why win rate alone is meaningless and expectancy is the number that really decides profit.

Why weekend and event gaps can blow through a stop — and how to manage the risk.

How a GSLO caps your loss exactly even through gaps, the premium it costs, and when it's worth paying.

Direct and correlation hedges, their costs, and why good sizing usually beats hedging.

Placing the stop where the idea is wrong — and the cardinal rule of never moving it against you.

The risk of not trading at the price you expect — when liquidity thins (off-hours, holidays, news, exotics) and how to manage it.

Why doubling down after losses leads to ruin — and why the opposite approach is sound.

How MAE and MFE reveal whether your stops and targets fit your trades — and the danger of curve-fitting them.

How measuring the furthest a trade ran in your favour sharpens your targets and exits — the profit-side counterpart to MAE.

Reshuffling trades into thousands of paths to reveal the true range of drawdowns and risk of ruin.

Why a strategy tuned to past data fails live, how to spot curve-fitting, and how to build more robust systems.

Sizing a trade from your risk, not your conviction — the most powerful risk control there is.

Why drawdowns are normal, the disciplined process for climbing back, and why 'winning it back fast' deepens the hole.

How risk:reward and win rate combine into expectancy — and why you can lose most trades and still profit.

Building and exiting positions in stages — adding to winners, and the danger of averaging down.

Per-trade, daily and drawdown loss limits that protect your capital — and protect you from yourself.

Why a handful of trades proves nothing, how many you really need, and why testing many strategies inflates false positives.

Why you only see the winners — how survivorship bias distorts your sense of success and corrupts backtests.

A circuit breaker that stops you trading after a set daily loss — why it prevents tilt spirals, how to set one, and honouring it.

The formula for optimal bet size, why full Kelly is too aggressive, and fractional Kelly.

Why a loss needs a larger gain to recover — the asymmetry that makes capital preservation paramount.

How gross profit divided by gross loss measures a strategy's profitability — how to read it, and why a very high value can warn.

How spread, commission, swap and slippage erode every trade — and why a strategy must beat its costs to profit.

How VaR estimates a likely maximum loss — its three components, and the tail risk it dangerously ignores.

Using volatility (ATR) to set stops and size, keeping risk consistent across conditions.

How rolling optimise-then-test windows validate a strategy on unseen data, guarding against overfitting better than a single backtest.