The strategy that made ₹10 lakhs and the one that lost ₹10 lakhs are often the same strategy. The difference is size and discipline. How much to bet, when to stop, and how to survive the drawdowns everyone eventually faces.
You cannot make money if you’re not in the game.
Blowing up your account isn’t a bad trade — it’s the end of your trading. Everything in this chapter is about survival first, profit second.
Growth peaks at Kelly, but the curve is brutally asymmetric — go past Kelly and you lose faster than you'd gain. Most retail traders should stay left of the ¼ Kelly mark. Below 30% win-rate or negative R/R, all sizes lose long-run.
Adjust the win rate and R/R above — the blue curve shows the long-run growth rate at each bet size. The 2% rule (green line) is conservatively left of Kelly for a reason: the curve is deadly asymmetric. Full Kelly maximizes growth in theory, but a single miscalibration in win-rate destroys years of compounding.
Never risk more than 2% of your account on a single trade.
For an options trade, “risk” means the maximum loss if things go wrong. For a bought call: premium paid. For a short strangle: potential adverse move (NOT just premium collected).
Account: ₹5,00,000. Max risk per trade: 2% = ₹10,000.
Considering a Nifty iron condor with 200-point wings:
How many lots? 10,000 / 7,150 = 1 lot — barely fits inside the 2% budget.
Solutions to add capacity: wider wings (300-500 points, lower max loss density), or a Sensex condor (lot 20, smaller absolute risk per lot), or accept 3% risk knowing the cost.
Even with 2% per trade, five losing trades in a week = 10% down. Add a weekly limit:
Never lose more than 6% of your account in a single week. If you hit that, stop trading for the week. Review. Come back Monday.
If your account is ever down 20% from its peak, stop trading entirely for at least 30 days.
The single most common way retail traders die: hitting drawdown, doubling size to recover fast, then losing everything.
Down 20% → need +25% to recover. Down 50% → need +100%. Down 80% → need +400%. The bigger your drawdown, the harder recovery becomes. Small sizing prevents big drawdowns before they happen.
The curve is convex — small drawdowns are easy to recover, big ones become mathematically brutal. Beyond 50% drawdown, recovery in reasonable time requires taking bigger risks — exactly the opposite of what you should do. Best strategy: avoid deep drawdowns in the first place via sizing discipline.
Beyond per-trade limits, cap total exposure:
Before every trade:
If any answer is no, don’t trade.
Streaks happen. You WILL have 5 losing trades in a row. The math:
When it happens:
Indian retail costs per options round-trip: ~₹40-70. If your average profit per trade is ₹500 and you take 20 trades/month, fees = ₹800-1,400 = 8-14% drag.
Sizing and frequency choices should factor this in.
The mathematically optimal position size for a repeating bet with known edge and payoff.
Kelly fraction = (bp − q) / b
Where: b = payoff ratio (win amount / loss amount) p = probability of winning q = probability of losing = 1 − p
Your iron condor:
Kelly fraction = (0.818 × 0.85 − 0.15) / 0.818 = 0.666 → 67% per trade
This is far too aggressive for real trading.
Kelly assumes:
Overestimate win rate by 10% → Kelly recommends 2-3× too much → blow-up.
Professional practice:
For the iron condor above:
Quarter Kelly is still 8× the 2% rule. That’s the trade-off — higher returns, bigger swings.
Kelly works ONLY if edge estimates are accurate. For 95%+ of retail traders, edge estimates are optimistic (survivorship bias, hindsight bias, small samples).
Realistic recommendation:
Instead of fixed % per trade, scale size inversely to volatility:
Position size = Target vol × Account ÷ Position’s expected std deviation
Account ₹5,00,000. Target 1% daily portfolio vol.
Iron condor’s expected daily P&L std (from backtest): ₹1,200 per lot.
Position: (0.01 × 5,00,000) / 1,200 = 4 lots
If Nifty vol spikes and iron condor daily P&L std doubles to ₹2,400/lot:
Automatic reduction when environment gets riskier.
Simple version — scale by VIX regime:
Prevents catastrophic vol at maximum leverage.
Running iron condors + calendars + cash-secured puts?
Treat total portfolio exposure as ONE budget:
Correlations matter — three strategies can go bad simultaneously in a big Nifty move.
Beyond simple sizing, monitor aggregate exposure:
| Greek | Interpretation | Sensible limit |
|---|---|---|
| Total delta | Net directional | ±10 delta per ₹1L account |
| Total theta | Daily time decay P/L | Positive OK; ensure earned not paid |
| Total vega | Sensitivity to IV | Cap at ±0.5% account per IV point |
| Total gamma | Delta change speed | Cap so 2% Nifty move doesn’t blow past delta limit |
Rebalance when any breaches limit.
Some professionals size BELOW Kelly deliberately: never bet so much that a bad streak forces you out. Lower short-term returns for long-term survival.
Buffett’s insight: “Never lose money” isn’t literal — it means “never lose so much you can’t recover.”
Use in this order as sophistication grows:
Skip levels only when you have data to justify it. Most retail should stay at levels 2-3 forever.
No matter what math you use: never risk more than 20% of account across ALL open positions. Protects against correlated blow-ups.
Start:
After 12 months of tracked results:
Trading is 70% psychology, 30% strategy. What kills accounts:
The 2% rule protects against most of these. Small size doesn’t feel exciting → doesn’t trigger emotional swings → doesn’t force bad decisions.
Expectancy = (Win rate × Avg win) − (Loss rate × Avg loss)
Negative expectancy: no sizing saves the strategy. Positive expectancy: sizing determines survival.
Strategy A: 90% win, +₹500 wins, −₹4,000 losses Expectancy: 0.9 × 500 − 0.1 × 4,000 = 450 − 400 = +₹50/trade
Strategy B: 40% win, +₹800 wins, −₹400 losses Expectancy: 0.4 × 800 − 0.6 × 400 = 320 − 240 = +₹80/trade
Both positive. But A has 30% chance of 4-loss streak = ₹16,000 gone. B rarely loses 3 in a row (max ₹1,200 hit).
B is easier to size and survive. Same edge, better distribution.