Intuition The core idea in one breathYou will lose trades. That is not a bug — it's a feature of trading. The 1–2% rule says:
on any single trade , never let your loss be more than 1–2% of your total trading capital .
This makes any single loss survivable and keeps you in the game long enough for your edge to play out.
Definition Risk per tradeRisk per trade = the amount of money you lose if the trade goes wrong — i.e. if price hits your stop-loss .
It is NOT the amount of money you put into the trade (that's position size / capital deployed).
Risk = (entry price − stop price) × (number of shares).
The subtle trap: two traders can both "buy ₹1,00,000 of a stock" but have totally different risk , because their stop-losses are at different distances.
Losses compound against you asymmetrically. If you lose 50%, you don't need +50% to recover — you need +100% . So the goal is: never take a loss big enough to cripple compounding.
Let capital C C C r r r n n n consecutive losing trades. Capital after n n n
C n = C ( 1 − r ) n C_n = C\,(1-r)^n C n = C ( 1 − r ) n
Why this form? Each loss multiplies remaining capital by ( 1 − r ) (1-r) ( 1 − r )
Now ask: after a bad streak of 10 losses, how much survives?
C 10 C = ( 1 − r ) 10 \frac{C_{10}}{C} = (1-r)^{10} C C 10 = ( 1 − r ) 10
r r r Capital left after 10 losses
1%
( 0.99 ) 10 ≈ 90.4 % (0.99)^{10} \approx 90.4\% ( 0.99 ) 10 ≈ 90.4%
2%
( 0.98 ) 10 ≈ 81.7 % (0.98)^{10} \approx 81.7\% ( 0.98 ) 10 ≈ 81.7%
10%
( 0.90 ) 10 ≈ 34.9 % (0.90)^{10} \approx 34.9\% ( 0.90 ) 10 ≈ 34.9%
25%
( 0.75 ) 10 ≈ 5.6 % (0.75)^{10} \approx 5.6\% ( 0.75 ) 10 ≈ 5.6%
Why 1–2% wins: even a brutal 10-loss streak barely dents you (~18% max). At 25%, ten losses wipe you out . Small risk buys survival time for your edge.
Lose 10% → need 0.10 0.90 = 11.1 % \frac{0.10}{0.90}=11.1\% 0.90 0.10 = 11.1%
Lose 50% → need 0.50 0.50 = 100 % \frac{0.50}{0.50}=100\% 0.50 0.50 = 100%
Small per-trade risk keeps drawdowns small, so recovery stays easy.
Worked example Example 1 — basic sizingCapital C = ₹ 5 , 00 , 000 C = ₹5,00,000 C = ₹5 , 00 , 000 r = 1 % r = 1\% r = 1% P e = ₹ 200 P_e = ₹200 P e = ₹200 P s = ₹ 190 P_s = ₹190 P s = ₹190
Step 1: Risk amount R = 0.01 × 5,00,000 = ₹ 5,000 R = 0.01 \times 5{,}00{,}000 = ₹5{,}000 R = 0.01 × 5 , 00 , 000 = ₹5 , 000 Why? This is the max you allow yourself to lose here.Step 2: Stop distance = ∣ 200 − 190 ∣ = ₹ 10 = |200-190| = ₹10 = ∣200 − 190∣ = ₹10 Why? That's your loss per share if the trade fails.Step 3: Q = 5000 / 10 = 500 Q = 5000/10 = 500 Q = 5000/10 = 500 Why? 500 × ₹ 10 = ₹ 5000 = R 500 \times ₹10 = ₹5000 = R 500 × ₹10 = ₹5000 = R Capital deployed = 500 × 200 = ₹ 1,00,000 = 500 \times 200 = ₹1{,}00{,}000 = 500 × 200 = ₹1 , 00 , 000
Worked example Example 2 — tighter stop = bigger positionSame C = ₹ 5 , 00 , 000 C=₹5,00,000 C = ₹5 , 00 , 000 r = 1 % r=1\% r = 1%
R = ₹ 5000 R = ₹5000 R = ₹5000 = ₹ 2 = ₹2 = ₹2 Q = 5000 / 2 = 2500 Q = 5000/2 = 2500 Q = 5000/2 = 2500 = ₹ 5 , 00 , 000 = ₹5,00,000 = ₹5 , 00 , 000 Why bigger? Tighter stop → each share risks less → you can hold more shares for the same ₹5000 risk.Watch out: deployed capital ballooned; you may hit position-size or margin limits before risk limits. Cap by the smaller allowed number.
Worked example Example 3 — 2% on a volatile stockC = ₹ 2 , 00 , 000 C=₹2,00,000 C = ₹2 , 00 , 000 r = 2 % r=2\% r = 2%
R = 0.02 × 2,00,000 = ₹ 4000 R = 0.02\times 2{,}00{,}000 = ₹4000 R = 0.02 × 2 , 00 , 000 = ₹4000 Stop distance = ₹ 40 = ₹40 = ₹40
Q = 4000 / 40 = 100 Q = 4000/40 = 100 Q = 4000/40 = 100 = ₹ 50,000 = ₹50{,}000 = ₹50 , 000 Why 2% here? Higher-conviction setup; but volatile stocks need wide stops, which shrinks Q Q Q auto-adjusts size down for risky stops. That's the beauty.
Common mistake "Risk = money I invested"Why it feels right: if you put ₹1,00,000 in and the stock could theoretically go to zero, ₹1,00,000 is the max loss.
The fix: in practice you exit at a stop-loss , not at ₹0. Real risk = shares × stop distance, usually a tiny slice of capital deployed. Sizing off "invested amount" makes you take way too little size, or worse, no stop at all.
Common mistake "I'll widen the stop so I don't get stopped out"Why it feels right: a wider stop = fewer premature exits = feels safer.
The fix: to keep risk at 1%, a wider stop forces a smaller position . If you widen the stop and keep the same shares, your risk silently jumps to 3–4%. Always re-solve Q = R / distance Q = R/\text{distance} Q = R / distance
Common mistake "One great trade — let me risk 20% this once"Why it feels right: high conviction; big win feels deserved.
The fix: you can't tell winners from losers in advance . One 20% loss needs a 25% gain to recover; a streak of them ends your account (see table). Edge only pays off over many trades — you must survive to trade them.
Recall Feynman: explain to a 12-year-oldImagine you have 100 gold coins and you play a betting game you're pretty good at but not perfect. If you bet almost all your coins each round, one unlucky round leaves you broke — game over. So instead you bet only 1 or 2 coins per round. Even if you lose 10 times in a row, you still have ~80 coins left to keep playing until your skill wins. The 1–2% rule is just "bet small enough that a bad streak can't kick you out of the game."
"Risk small, live long — 1 to 2, that's all you throw."
And for sizing: R.S.D. = Risk ÷ Stop Distance = Shares.
Is "risk per trade" the money invested or the money lost at stop? Why?
Derive the shares formula from the risk amount.
Why does a 50% loss need a 100% gain to recover?
Tighter stop — does position size go up or down? Why?
What does "risk per trade" measure? The money you lose if price hits your stop-loss, = shares × stop-distance — NOT the capital deployed.
State the 1–2% rule. Never risk more than 1–2% of total trading capital on a single trade.
Formula for position size from the rule? Q = (r·C) / |P_e − P_s|, where r is risk fraction, C capital, P_e entry, P_s stop.
Why divide risk amount by stop distance? Because shares × stop-distance equals the loss if stopped out; setting that = allowed risk gives the share count.
Capital left after 10 losses at 2% risk each? (0.98)^10 ≈ 81.7%.
Gain needed to recover a loss of fraction L? g = L/(1−L); e.g. 50% loss needs 100% gain.
If you widen your stop but keep risk at 1%, what happens to size? Position size shrinks (fewer shares) since each share now risks more.
Why is 25% risk per trade fatal? (0.75)^10 ≈ 5.6% — a 10-loss streak nearly wipes the account.
Stop-Loss Placement — supplies the P s P_s P s Position Sizing — the direct application of Q = R / distance Q = R/\text{distance} Q = R / distance Risk-Reward Ratio — pairs with per-trade risk to define expectancy.Drawdown and Recovery — the asymmetry that justifies small risk.Kelly Criterion — a formal optimum; 1–2% is a safe "fractional Kelly."Trading Psychology — small risk keeps emotions (and revenge trades) in check.
Q equals rC over stop distance
entry minus stop times shares
Position size / capital deployed
Multiplicative loss model
Drawdown recovery asymmetry
Intuition Hinglish mein samjhoDekho, trading me har ek trade jeetna possible nahi hai — losses aayenge hi. Isliye smart traders ek simple rule follow karte hain: kisi bhi ek trade me apna total capital ka sirf 1–2% risk karo . Yaha "risk" ka matlab hai — agar trade galat gaya aur stop-loss hit hua to kitna paisa doobega — na ki kitna paisa aapne lagaya. Ye do alag cheezein hain. Aap ₹1,00,000 ka stock kharid sakte ho lekin risk sirf ₹5,000 ho, agar stop-loss pass me lagaya ho.
Ye 1–2% kyun? Kyunki losses multiply hote hain. Agar aap 25% per trade risk karo aur lagataar 10 trades haar jao, to ( 0.75 ) 10 (0.75)^{10} ( 0.75 ) 10 100% gain chahiye — ye asymmetry hi hai jo chhota risk lene par majboor karti hai.
Position size nikalne ka formula seedha hai: Shares = (risk amount) ÷ (stop distance) . Yaani Q = r C / ∣ P e − P s ∣ Q = rC / |P_e - P_s| Q = r C /∣ P e − P s ∣
Yaad rakho: chhota risk lene se aap "boring" nahi ban rahe, aap survive kar rahe ho. Aur trading me survive karna hi asli jeet hai, kyunki aapka edge tabhi kaam karega jab aap game me bane rahoge. "Risk small, live long."
