The part of trading that determines whether edge survives.

Risk per trade is the amount of capital a trader is willing to lose on a single position if the stop-loss is hit, usually expressed as a percentage of total trading capital rather than a fixed rupee amount, so it scales automatically as the account grows or shrinks.

A common convention is capping risk per trade at 1-2% of capital, which means a string of consecutive losses erodes the account gradually rather than catastrophically — ten losing trades at 1% risk each reduces capital by roughly 10%, not 100%.

Risk per trade is defined by the stop-loss distance and position size together, not by the position size alone — the same position size carries very different risk depending on how far away the stop is set.

A standard position sizing approach works backward from risk: position size = (account capital × risk % per trade) ÷ (entry price − stop-loss price). This ensures that regardless of how far or close the stop is set, the rupee amount at risk stays constant at the intended percentage.

This means a trade with a tight stop-loss (a stock with lower volatility, or a well-defined support level) allows a larger position size for the same dollar risk, while a trade with a wider stop requires a smaller position size — the position size adapts to the setup's risk, not the other way around.

More advanced approaches, like the Kelly criterion, size positions based on both the probability of winning and the payoff ratio, aiming to maximize long-run capital growth — but full Kelly sizing is aggressive and prone to large drawdowns, which is why many traders use a fraction of the calculated Kelly size in practice.

Maximum drawdown is the largest peak-to-trough decline in an account's equity curve over a given period — if capital grows from ₹10 lakh to ₹15 lakh, then falls to ₹11 lakh before recovering, the drawdown is roughly 27% (the decline from the ₹15 lakh peak to the ₹11 lakh trough).

It's one of the more important risk metrics for evaluating a strategy, because a strategy's average return says nothing about how painful the ride to get there was — two strategies with identical average annual returns can have very different maximum drawdowns, and the one with the smaller drawdown is generally easier to actually stick with.

Recovering from a drawdown requires a disproportionately larger gain than the drawdown itself — a 50% drawdown requires a 100% gain just to get back to the prior peak, which is part of why limiting drawdown size is treated as more important than maximizing average returns in most risk frameworks.

Risk of ruin is the probability that a trading strategy, given its win rate, payoff ratio, and position sizing, eventually depletes an account to a level from which it can't realistically recover, purely from a normal sequence of losses rather than a single catastrophic event.

It's driven heavily by position sizing relative to edge — a genuinely profitable strategy can still carry a meaningful risk of ruin if positions are sized too aggressively relative to how much variance the strategy's returns actually have.

Reducing risk of ruin is one of the main practical justifications for capping risk per trade at a small percentage, since risk of ruin drops sharply as position size relative to capital decreases, even for the same underlying strategy edge.

Diversification reduces portfolio risk by holding positions that don't all move together — the benefit comes specifically from low or negative correlation between positions, not simply from holding a larger number of them.

Holding ten different stocks in the same sector provides much less real diversification than holding the same number spread across unrelated sectors, since sector-wide moves tend to affect correlated stocks similarly regardless of how many individual names are held.

Correlation between positions isn't fixed — it tends to increase during market stress, when many asset classes and sectors sell off together, which is why diversification that looks solid in calm markets can provide less protection than expected during a sharp broad decline.

An R-multiple expresses a trade's result as a multiple of the initial risk taken, rather than in absolute rupee terms — a trade that risked ₹1,000 and made ₹3,000 is a +3R trade; one that risked ₹1,000 and lost ₹1,000 is a −1R trade.

Measuring results in R-multiples makes performance comparable across trades of different sizes and different instruments, since it normalizes for how much was actually at risk rather than how much capital was deployed.

Tracking the distribution of R-multiples across many trades — not just the win rate — shows whether a strategy's edge comes from winning often with small gains, or winning less often with larger gains per win, which changes how the strategy should be evaluated and where its risk actually concentrates.