Lesson 29
Position Sizing: From Equity to Whole Lots
Choose a loss basis, calculate the whole-lot limit, then check funding, open exposures and the assumptions behind growth models.

Does a whole lot fit the allowance?
Hypothetical NIFTY futures · entry 25,000 · planned exit 24,850 · 65-unit lot · estimates before costs
Does the account fit the quantity?
I’m Mr. Chartist. Let’s turn an account allowance into whole lots, then check the loss assumption, the funds and the combined exposure that the first division cannot settle.
By the end you will be able to answer
- What does the number of lots decide?
- How do you turn an allowance into whole lots?
- Does the account have the money for that many lots?
You have a view on NIFTY 50, the index of 50 large Indian companies, and you know where you would get out if the view is wrong. The order ticket then asks a different question: how many lots? The smallest quantity the exchange accepts can put more money at risk than you meant to risk on this trade. Being sure about direction does not fix that.
Position sizing connects three things: your account value, the loss you decided to accept, and the quantity you carry. First decide what the loss number means: a planned exit, the full premium of a bought option, or the worst loss of a finished spread. Then check whole lots, costs, free funds and the positions you already hold. Each check answers a different part of the question.
We follow a fictional ₹5,00,000 account with a 1% allowance and a NIFTY lot of 65 units. These are teaching numbers, not live contract details and not a recommended risk percentage. Later we look at a run of losses and at a separate model called Kelly, and we mark where their arithmetic stops and real trading begins.
Updated
What does the number of lots decide?
See how the number of lots sets the money at stake.
MayaMr. Chartist, I know my exit. Why does the order ticket still ask me how many lots?
Because the number of lots decides how much money one price move can take from you. Same entry, same exit, three lots lose three times as much.
So how do I pick the lots?
Allowance = equity × fraction. Then lots = allowance ÷ loss per lot, rounded down. In our ₹5,00,000 account with a 1% allowance, that is ₹5,000.
One lot could lose ₹9,750. So the answer is zero lots?
Yes, and zero is a valid answer. Do not pull the exit closer just to get one lot. That changes the plan to fit the answer.
Then check the funds, and the risk of all your open positions together.
Mr. ChartistShort answer: the number of lots decides how much money one price move can take from you. Picture two learners in the same NIFTY futures contract, with the same entry and the same exit. One holds one lot and the other holds three. Before costs, the second learner wins or loses three times as much. Direction is the same; size is the only thing that changed.
Start from your account equity: what the account is worth today, with open positions marked at their current value. Money you need for rent, bills or other goals stays outside this number. Then separate three ideas that beginners often mix up. A loss allowance (the Start course calls it a loss budget) is the amount you decide a trade may cost you. Collateral is the money or approved assets the broker holds against your obligations. Buying power is what the broker lets you take on. None of these is a cap on your loss. Margin, leverage and pledging explains the second and third.
Our account has ₹5,00,000 of equity and a 1% loss allowance, which is ₹5,000. Both are teaching numbers, not advice on what percentage suits you. We assume a NIFTY lot of 65 units. Check the real lot size for your contract and date before you use any calculation here. NIFTY is an index, so nothing is delivered into your demat account. The first lesson on this subject, risk management 101, builds the same idea for shares.
How do you turn an allowance into whole lots?
Turn an allowance into whole lots.
Short answer: divide the allowance by the loss on one lot, then round down. Allowance = equity × fraction. Lots = allowance ÷ loss per lot, rounded down to a whole number. If the answer is below one, you take zero lots. Rounding up quietly raises your allowance; it does not solve anything.
Take a long NIFTY futures lot bought at 25,000 with a planned exit at 24,850. The adverse move is 150 points. At 65 units that is 150 × 65 = ₹9,750 before costs. Your allowance is ₹5,000, and ₹5,000 ÷ ₹9,750 is about 0.513 of a lot. Rounded down, that is zero lots.
Round down before checking the funds
Same futures trade: entry 25,000, planned exit 24,850, 65-unit lot. One lot loses ₹9,750 before costs.
| Account equity | Assumed 1% allowance | Whole lots / planned loss | Unused allowance |
|---|---|---|---|
| ₹2,50,000 | Assumed 1% allowance₹2,500 | Whole lots / planned loss0 lots · ₹0 | Unused allowance₹2,500 |
| ₹5,00,000 | Assumed 1% allowance₹5,000 | Whole lots / planned loss0 lots · ₹0 | Unused allowance₹5,000 |
| ₹10,00,000 | Assumed 1% allowance₹10,000 | Whole lots / planned loss1 lots · ₹9,750 | Unused allowance₹250 |
The ₹5,00,000 account gives 0 lots. Rounding up would estimate ₹9,750 of loss, or 1.95% of that equity, against its ₹5,000 allowance. At ₹10,00,000, one lot leaves only ₹250 before costs.
Unused allowance is room on paper, not free cash. Costs are set to zero here, and a stop is not a guaranteed fill. The 1% and the 65 units are teaching assumptions.
The quotient is not the order quantity
Use a positive per-lot loss estimate, then take the largest whole number that fits. Do not round upward.
Allowance = ₹5,00,000 × 1% = ₹5,000Planned loss per lot = 150 futures-price points × 65 units = ₹9,750Risk-budget lots = floor(5,000 / 9,750) = 0
A planned exit is an estimate, not a ceiling. If the exit order fills at 24,750 instead of 24,850, the move is 250 points and one lot loses ₹16,250. Fees add to both numbers. The honest sizing question is therefore: what do I lose if the exit is a bit worse than planned? Risk management 101 shows the same point for shares: a stop decides when you sell, not the price you get.
Does the account have the money for that many lots?
Pass both the loss test and the funding test.
Short answer: the lot count must pass two tests. The loss test asks how much you could lose. The funding test asks how much money the position needs. The smaller answer wins.
Use a second, separate example: ₹10,00,000 of equity and a 2% allowance, which is ₹20,000. Suppose a bought-and-sold Call spread (a credit vertical) has a worst terminal loss of ₹4,550 per lot before costs. The loss test allows four lots, because 20,000 ÷ 4,550 is 4.396, rounded down to 4. Now suppose only ₹1,80,000 is free for this trade and each lot needs ₹1,80,000. The funding test allows one lot. One is the binding answer, and the planned terminal loss is ₹4,550.
Passing the allowance check does not supply the funds
A separate ₹10,00,000 account, 2% allowance, ₹4,550 spread loss per lot. Free funds ₹1,80,000; each lot needs ₹1,80,000.
| Constraint | Declared amount | Whole-lot limit |
|---|---|---|
| Loss allowance | Declared amount₹20,000 / ₹4,550 per lot | Whole-lot limit4 lots |
| Usable funding | Declared amount₹1,80,000 / ₹1,80,000 per lot | Whole-lot limit1 lot |
| Smaller whole-lot limit | Declared amountBoth constraints must hold | Whole-lot limit1 lot |
One lot uses ₹4,550 of the loss allowance and all ₹1,80,000 of the assumed usable funding. The remaining ₹15,450 allowance cannot fund another lot.
Every funding number is made up. Real margin can change with your other positions and is not a fee or a maximum loss. Costs, premium cash and delivery need their own checks.
Take the smaller of two integer limits
The example calculator treats loss allowance and funding as separate constraints, using the declared inputs without inferring a live margin.
Risk lots = floor(20,000 / 4,550) = 4Funding lots = floor(1,80,000 / 1,80,000) = 1Permitted by these inputs = min(4, 1) = 1 lot
Real margin does not behave like this tidy division. It changes with your other positions, the hedges you hold, market conditions and broker rules, and the requirement for two lots is not always twice the requirement for one. This example does not calculate live SPAN or exposure margin. Check the actual requirement for the whole position you intend to hold, and remember that a margin figure is collateral, not a measure of loss.
What does a result of zero lots tell you?
Accept zero lots as a valid answer.
Short answer: for this account and this trade, the position is too big. Zero is a valid answer, not an error. In our example, one lot would put ₹9,750 at risk, which is 1.95% of a ₹5,00,000 account, against a 1% allowance.
You can change the trade. A different contract, a smaller structure or a different exit makes a different calculation. What you should not do is move your exit closer just to make the arithmetic return one lot. That changes the plan to fit the answer, and a tighter exit is more likely to be hit by ordinary movement.
A smaller structure such as a spread can fit the allowance, but check it as carefully as the first idea. A quoted credit is not a filled credit. A partly filled order can leave you with one leg only. The protective leg must match in underlying, expiry and quantity. If the limits still say zero, keep zero.
What happens to the allowance as the account shrinks?
Compare a percentage allowance with a fixed one.
Short answer: a percentage allowance gets smaller after every loss, and a fixed rupee allowance does not. To see this cleanly, allow any position size and assume every trade loses its full allowance. Start with ₹5,00,000. If each loss is 1% of the equity left, twenty losses leave about ₹4,08,953.47. If each loss is a fixed ₹5,000, twenty losses leave ₹4,00,000.
The next loss allowance changes with the account
Start with ₹5,00,000. Every trade loses its full allowance: 1% of the latest equity, or a fixed ₹5,000.
- Recalculated 1% loss allowance
- Constant ₹5,000 loss allowance
- Fixed rule risks more than 1%
₹910.47Fixed rule risks more than 1%: widest after 20 full losses, ₹4,089.53 against ₹5,000.
Axis cropped to ₹4,000–₹5,000 so the gap shows; it does not start at ₹0. The recalculated line is 1% of the equity left after that many full losses. Any position size, no costs, no gaps, no lot floors.
| Series | Number of assumed full-loss trades already taken | Loss allowance for the next trade · ₹ |
|---|---|---|
| Recalculated 1% loss allowance | 0 | 5,000 |
| Recalculated 1% loss allowance | 1 | 4,950 |
| Recalculated 1% loss allowance | 2 | 4,900.5 |
| Recalculated 1% loss allowance | 3 | 4,851.49 |
| Recalculated 1% loss allowance | 4 | 4,802.98 |
| Recalculated 1% loss allowance | 5 | 4,754.95 |
| Recalculated 1% loss allowance | 6 | 4,707.4 |
| Recalculated 1% loss allowance | 7 | 4,660.33 |
| Recalculated 1% loss allowance | 8 | 4,613.72 |
| Recalculated 1% loss allowance | 9 | 4,567.59 |
| Recalculated 1% loss allowance | 10 | 4,521.91 |
| Recalculated 1% loss allowance | 11 | 4,476.69 |
| Recalculated 1% loss allowance | 12 | 4,431.92 |
| Recalculated 1% loss allowance | 13 | 4,387.61 |
| Recalculated 1% loss allowance | 14 | 4,343.73 |
| Recalculated 1% loss allowance | 15 | 4,300.29 |
| Recalculated 1% loss allowance | 16 | 4,257.29 |
| Recalculated 1% loss allowance | 17 | 4,214.72 |
| Recalculated 1% loss allowance | 18 | 4,172.57 |
| Recalculated 1% loss allowance | 19 | 4,130.84 |
| Recalculated 1% loss allowance | 20 | 4,089.53 |
| Constant ₹5,000 loss allowance | 0 | 5,000 |
| Constant ₹5,000 loss allowance | 1 | 5,000 |
| Constant ₹5,000 loss allowance | 2 | 5,000 |
| Constant ₹5,000 loss allowance | 3 | 5,000 |
| Constant ₹5,000 loss allowance | 4 | 5,000 |
| Constant ₹5,000 loss allowance | 5 | 5,000 |
| Constant ₹5,000 loss allowance | 6 | 5,000 |
| Constant ₹5,000 loss allowance | 7 | 5,000 |
| Constant ₹5,000 loss allowance | 8 | 5,000 |
| Constant ₹5,000 loss allowance | 9 | 5,000 |
| Constant ₹5,000 loss allowance | 10 | 5,000 |
| Constant ₹5,000 loss allowance | 11 | 5,000 |
| Constant ₹5,000 loss allowance | 12 | 5,000 |
| Constant ₹5,000 loss allowance | 13 | 5,000 |
| Constant ₹5,000 loss allowance | 14 | 5,000 |
| Constant ₹5,000 loss allowance | 15 | 5,000 |
| Constant ₹5,000 loss allowance | 16 | 5,000 |
| Constant ₹5,000 loss allowance | 17 | 5,000 |
| Constant ₹5,000 loss allowance | 18 | 5,000 |
| Constant ₹5,000 loss allowance | 19 | 5,000 |
| Constant ₹5,000 loss allowance | 20 | 5,000 |
| Case after 20 losses | Remaining equity | Drawdown from start | Gain needed on remainder |
|---|---|---|---|
| Recalculated 1% | Remaining equity₹4,08,953.47 | Drawdown from start18.21% | Gain needed on remainder22.26% |
| Fixed ₹5,000 | Remaining equity₹4,00,000.00 | Drawdown from start20.00% | Gain needed on remainder25.00% |
| Separate case: recalculated 2% | Remaining equity₹3,33,803.99 | Drawdown from start33.24% | Gain needed on remainder49.79% |
| Separate case: fixed ₹10,000 | Remaining equity₹3,00,000.00 | Drawdown from start40.00% | Gain needed on remainder66.67% |
The 1% allowance shrinks after each loss. A fixed ₹5,000 takes a growing share of a shrinking account. The 2% rows are a separate comparison.
A made-up loss run with no probability. Positions can be any size, and costs, lots, gaps and deposits are left out. Neither percentage is a recommendation.
Inspect the two equity rules
Recalculate from full-precision equity; round money only for display.
Fixed fraction: E_n = E_0 × (1 − f)^nFixed cash: E_n = E_0 − n × L, where L stays constantAt 20 losses: 500000 × 0.99^20 = ₹4,08,953.47At 20 losses: 500000 − 20 × 5000 = ₹4,00,000.00
At a 2% fraction the same twenty losses leave about ₹3,33,803.99, against ₹3,00,000 for a fixed ₹10,000 loss. This is arithmetic, not a forecast. It is not a typical losing run, and it does not show that any sizing method will keep an account alive. Both paths lose money.
The smooth curve ignores whole lots. With real lots the allowed quantity moves in steps, so the risk on one trade rarely equals the chosen percentage exactly, and it can fall to zero. Costs, gaps, deposits and withdrawals also change the path.
Why does a loss need a bigger gain to recover?
See why recovery is measured on a smaller account.
Short answer: the gain is measured on a smaller account. A drawdown is the fall from the highest value your account reached to a later, lower value. Start with ₹5 lakh and lose 20%, and you hold ₹4 lakh. To get the ₹1 lakh back, you must gain 25% on ₹4 lakh. The two percentages use different bases.
Recovery uses the smaller remaining balance
A fall is measured from the peak. The gain to recover is measured on what remains. No deposits or withdrawals.
- Required arithmetic recovery gainSolid line
Gain needed on remaining equity · %
Drawdown from reference equity · %
Both axes start at 0%. The curve stops at an 80% fall (400% gain); a 100% fall cannot be recovered.
| Series | Drawdown from reference equity · % | Gain needed on remaining equity · % |
|---|---|---|
| Required arithmetic recovery gain | 0 | 0 |
| Required arithmetic recovery gain | 1 | 1.0101010101 |
| Required arithmetic recovery gain | 2 | 2.0408163265 |
| Required arithmetic recovery gain | 3 | 3.0927835052 |
| Required arithmetic recovery gain | 4 | 4.1666666667 |
| Required arithmetic recovery gain | 5 | 5.2631578947 |
| Required arithmetic recovery gain | 6 | 6.3829787234 |
| Required arithmetic recovery gain | 7 | 7.5268817204 |
| Required arithmetic recovery gain | 8 | 8.6956521739 |
| Required arithmetic recovery gain | 9 | 9.8901098901 |
| Required arithmetic recovery gain | 10 | 11.1111111111 |
| Required arithmetic recovery gain | 11 | 12.3595505618 |
| Required arithmetic recovery gain | 12 | 13.6363636364 |
| Required arithmetic recovery gain | 13 | 14.9425287356 |
| Required arithmetic recovery gain | 14 | 16.2790697674 |
| Required arithmetic recovery gain | 15 | 17.6470588235 |
| Required arithmetic recovery gain | 16 | 19.0476190476 |
| Required arithmetic recovery gain | 17 | 20.4819277108 |
| Required arithmetic recovery gain | 18 | 21.9512195122 |
| Required arithmetic recovery gain | 19 | 23.4567901235 |
| Required arithmetic recovery gain | 20 | 25 |
| Required arithmetic recovery gain | 21 | 26.582278481 |
| Required arithmetic recovery gain | 22 | 28.2051282051 |
| Required arithmetic recovery gain | 23 | 29.8701298701 |
| Required arithmetic recovery gain | 24 | 31.5789473684 |
| Required arithmetic recovery gain | 25 | 33.3333333333 |
| Required arithmetic recovery gain | 26 | 35.1351351351 |
| Required arithmetic recovery gain | 27 | 36.9863013699 |
| Required arithmetic recovery gain | 28 | 38.8888888889 |
| Required arithmetic recovery gain | 29 | 40.8450704225 |
| Required arithmetic recovery gain | 30 | 42.8571428571 |
| Required arithmetic recovery gain | 31 | 44.9275362319 |
| Required arithmetic recovery gain | 32 | 47.0588235294 |
| Required arithmetic recovery gain | 33 | 49.2537313433 |
| Required arithmetic recovery gain | 34 | 51.5151515152 |
| Required arithmetic recovery gain | 35 | 53.8461538462 |
| Required arithmetic recovery gain | 36 | 56.25 |
| Required arithmetic recovery gain | 37 | 58.7301587302 |
| Required arithmetic recovery gain | 38 | 61.2903225806 |
| Required arithmetic recovery gain | 39 | 63.9344262295 |
| Required arithmetic recovery gain | 40 | 66.6666666667 |
| Required arithmetic recovery gain | 41 | 69.4915254237 |
| Required arithmetic recovery gain | 42 | 72.4137931034 |
| Required arithmetic recovery gain | 43 | 75.4385964912 |
| Required arithmetic recovery gain | 44 | 78.5714285714 |
| Required arithmetic recovery gain | 45 | 81.8181818182 |
| Required arithmetic recovery gain | 46 | 85.1851851852 |
| Required arithmetic recovery gain | 47 | 88.679245283 |
| Required arithmetic recovery gain | 48 | 92.3076923077 |
| Required arithmetic recovery gain | 49 | 96.0784313725 |
| Required arithmetic recovery gain | 50 | 100 |
| Required arithmetic recovery gain | 51 | 104.0816326531 |
| Required arithmetic recovery gain | 52 | 108.3333333333 |
| Required arithmetic recovery gain | 53 | 112.7659574468 |
| Required arithmetic recovery gain | 54 | 117.3913043478 |
| Required arithmetic recovery gain | 55 | 122.2222222222 |
| Required arithmetic recovery gain | 56 | 127.2727272727 |
| Required arithmetic recovery gain | 57 | 132.5581395349 |
| Required arithmetic recovery gain | 58 | 138.0952380952 |
| Required arithmetic recovery gain | 59 | 143.9024390244 |
| Required arithmetic recovery gain | 60 | 150 |
| Required arithmetic recovery gain | 61 | 156.4102564103 |
| Required arithmetic recovery gain | 62 | 163.1578947368 |
| Required arithmetic recovery gain | 63 | 170.2702702703 |
| Required arithmetic recovery gain | 64 | 177.7777777778 |
| Required arithmetic recovery gain | 65 | 185.7142857143 |
| Required arithmetic recovery gain | 66 | 194.1176470588 |
| Required arithmetic recovery gain | 67 | 203.0303030303 |
| Required arithmetic recovery gain | 68 | 212.5 |
| Required arithmetic recovery gain | 69 | 222.5806451613 |
| Required arithmetic recovery gain | 70 | 233.3333333333 |
| Required arithmetic recovery gain | 71 | 244.8275862069 |
| Required arithmetic recovery gain | 72 | 257.1428571429 |
| Required arithmetic recovery gain | 73 | 270.3703703704 |
| Required arithmetic recovery gain | 74 | 284.6153846154 |
| Required arithmetic recovery gain | 75 | 300 |
| Required arithmetic recovery gain | 76 | 316.6666666667 |
| Required arithmetic recovery gain | 77 | 334.7826086957 |
| Required arithmetic recovery gain | 78 | 354.5454545455 |
| Required arithmetic recovery gain | 79 | 376.1904761905 |
| Required arithmetic recovery gain | 80 | 400 |
| Drawdown from ₹5,00,000 | Remaining equity | Gain needed on remainder |
|---|---|---|
| 10.00% | Remaining equity₹4,50,000.00 | Gain needed on remainder11.11% |
| 20.00% | Remaining equity₹4,00,000.00 | Gain needed on remainder25.00% |
| 50.00% | Remaining equity₹2,50,000.00 | Gain needed on remainder100.00% |
| 80.00% | Remaining equity₹1,00,000.00 | Gain needed on remainder400.00% |
After a 20% loss, ₹4,00,000 remains. The missing ₹1,00,000 is 25% of that. A 50% loss needs a 100% gain.
This is arithmetic, not a forecast. Costs would add to the gain needed. A zero balance cannot be recovered by any percentage.
Inspect the recovery denominator
H is the reference equity, E is remaining equity and D is decimal drawdown.
D = (H − E) / HRequired gain = H / E − 1 = D / (1 − D)20% drawdown: 0.20 / 0.80 = 0.25 = 25%
If the drawdown is D, the gain needed to recover is D ÷ (1 − D). A 50% fall needs a 100% gain. An 80% fall needs a 400% gain. This assumes no deposits, withdrawals or costs on the way back, and it says nothing about whether or how soon you will recover. Risk management 101 draws the same climb for share investors; the next lesson in this series, risk per trade, handles account limits.
Which loss number belongs to which position?
Match each position to its own loss measure.
Short answer: each position has its own loss measure, and you must use the right one. A bought NIFTY Call at ₹100 per unit, paid for in full, costs 65 × ₹100 = ₹6,500. That is the most it can lose before costs, so on a full-premium basis it fits zero lots against a ₹5,000 allowance. If you plan to sell at ₹40, the estimated loss is ₹3,900, but that is a plan, not the ₹6,500 limit, and nobody guarantees a fill at ₹40. Index points and option premium rupees are different things, so a stop on the index cannot be dropped into an option loss formula.
A matched Call credit spread has a 100-point strike width and a filled net credit of ₹30 per unit. Its worst loss at expiry, before costs, is (100 − 30) × 65 = ₹4,550. One lot fits the ₹5,000 allowance. A debit spread uses its net debit as its worst loss. These limits only hold if you keep both legs and the legs match. They do not guarantee an exit price or cover delivery funds for stock options.
Name the loss basis before dividing
Four separate NIFTY positions, 65 assumed units each, before costs. An exit estimate, a payoff bound and a stress case mean different things.
| Position | Declared loss basis | One-lot amount | Boundary / funding check |
|---|---|---|---|
| Long futures | Declared loss basisPlanned exit 25,000 → 24,850: 150 futures-price points. | One-lot amount₹9,750 | Boundary / funding checkExit at 24,750 instead loses ₹16,250 before costs. Check collateral and MTM cash separately. |
| Bought cash-settled Call · C / CE | Declared loss basisStandalone index option; ₹100 premium per unit can be lost in full. | One-lot amount₹6,500 | Boundary / funding checkGross terminal maximum option loss before costs. 0 lots fit ₹5,000 on this basis. Pay premium upfront. |
| Call credit vertical · C / CE | Declared loss basisSame expiry; 100-point strike width less ₹30 net credit per unit. | One-lot amount₹4,550 | Boundary / funding checkGross expiry loss bound for both matched legs retained. 1 lot fits before costs; collateral remains separate. |
| Uncovered short Call · C / CE | Declared loss basisStrike 25,000, premium ₹100; assumed final reference 25,300. | One-lot amount₹13,000 stress loss | Boundary / funding checkOne constructed adverse outcome, not maximum loss. The model permits unbounded upside loss. Margin is not a loss cap. |
Only the bought option and the finished spread have a stated worst loss. The futures exit and the short Call stress case are estimates, not maximums.
Blue marks the Call contract, not profit. A spread bound needs both legs, the same underlying, expiry and quantity. Stock options can need delivery cash or shares, so a premium limit does not cap settlement funding.
Keep the units consistent
Futures-price distance and option-premium loss are different inputs. An underlying move is not an interchangeable option-premium move.
Bought Call full premium = 100 × 65 = ₹6,500Matched credit vertical = (100 − 30) × 65 = ₹4,550Short Call stress loss = (max(25,300 − 25,000, 0) − 100) × 65 = ₹13,000
A naked short Call has no upper limit on loss, because the index can keep rising. A naked short Put can lose a very large but finite amount, since the index cannot fall below zero. A stress loss at one chosen level is only that scenario, and margin is neither of these. A stock option that settles by delivery can ask for strike money or shares, so its premium limit does not cap the delivery funds or later losses on shares.
What does the Kelly formula answer, and what does it not?
Learn what the Kelly formula answers and its limits.
Short answer: Kelly finds the bet size that grows money fastest in a simple repeated game whose odds you already know. It does not tell you how much to risk in real options trading. Our game has two outcomes. You lose a fraction f of your equity, or you win b times that fraction, and the chance of winning is p.
For p between 0 and 1 and f below 1, expected log growth is p × ln(1 + bf) + (1 − p) × ln(1 − f). The best f is p − (1 − p) ÷ b. If that comes out negative, the best bet in this game is zero. If you do not know p, you cannot run the calculation, and the right input is not 50%.
A different assumed win probability moves the optimum
A two-outcome game: lose f of equity, or win 2 × f. Compare win chances of 50% and 40%.
- Win chance p = 50% · win pays 2×Solid line
- Win chance p = 40% · win pays 2×Dashed line
Expected log growth per trial · natural log, dimensionless
Fraction of equity lost on failure · %
- p = 50%: model maximum at 25.00%
- p = 40%: model maximum at 10.00%
Plotted from 0% to 60% in steps of 0.5 points. Growth falls without limit as the bet nears 100%, so that end is left off.
| Series | Fraction of equity lost on failure · % | Expected log growth per trial · natural log, dimensionless |
|---|---|---|
| Win chance p = 50% · win pays 2× | 0 | 0 |
| Win chance p = 50% · win pays 2× | 0.5 | 0.0024688945 |
| Win chance p = 50% · win pays 2× | 1 | 0.0048761457 |
| Win chance p = 50% · win pays 2× | 1.5 | 0.0072225822 |
| Win chance p = 50% · win pays 2× | 2 | 0.0095090029 |
| Win chance p = 50% · win pays 2× | 2.5 | 0.0117361781 |
| Win chance p = 50% · win pays 2× | 3 | 0.0139048503 |
| Win chance p = 50% · win pays 2× | 3.5 | 0.0160157354 |
| Win chance p = 50% · win pays 2× | 4 | 0.0180695233 |
| Win chance p = 50% · win pays 2× | 4.5 | 0.0200668789 |
| Win chance p = 50% · win pays 2× | 5 | 0.0220084427 |
| Win chance p = 50% · win pays 2× | 5.5 | 0.0238948319 |
| Win chance p = 50% · win pays 2× | 6 | 0.0257266408 |
| Win chance p = 50% · win pays 2× | 6.5 | 0.0275044415 |
| Win chance p = 50% · win pays 2× | 7 | 0.0292287848 |
| Win chance p = 50% · win pays 2× | 7.5 | 0.0309002005 |
| Win chance p = 50% · win pays 2× | 8 | 0.0325191981 |
| Win chance p = 50% · win pays 2× | 8.5 | 0.0340862676 |
| Win chance p = 50% · win pays 2× | 9 | 0.0356018795 |
| Win chance p = 50% · win pays 2× | 9.5 | 0.0370664859 |
| Win chance p = 50% · win pays 2× | 10 | 0.0384805206 |
| Win chance p = 50% · win pays 2× | 10.5 | 0.0398443995 |
| Win chance p = 50% · win pays 2× | 11 | 0.0411585212 |
| Win chance p = 50% · win pays 2× | 11.5 | 0.0424232677 |
| Win chance p = 50% · win pays 2× | 12 | 0.0436390041 |
| Win chance p = 50% · win pays 2× | 12.5 | 0.0448060793 |
| Win chance p = 50% · win pays 2× | 13 | 0.0459248268 |
| Win chance p = 50% · win pays 2× | 13.5 | 0.0469955642 |
| Win chance p = 50% · win pays 2× | 14 | 0.0480185941 |
| Win chance p = 50% · win pays 2× | 14.5 | 0.0489942042 |
| Win chance p = 50% · win pays 2× | 15 | 0.0499226675 |
| Win chance p = 50% · win pays 2× | 15.5 | 0.0508042428 |
| Win chance p = 50% · win pays 2× | 16 | 0.0516391747 |
| Win chance p = 50% · win pays 2× | 16.5 | 0.0524276941 |
| Win chance p = 50% · win pays 2× | 17 | 0.0531700179 |
| Win chance p = 50% · win pays 2× | 17.5 | 0.0538663499 |
| Win chance p = 50% · win pays 2× | 18 | 0.0545168805 |
| Win chance p = 50% · win pays 2× | 18.5 | 0.055121787 |
| Win chance p = 50% · win pays 2× | 19 | 0.0556812339 |
| Win chance p = 50% · win pays 2× | 19.5 | 0.0561953728 |
| Win chance p = 50% · win pays 2× | 20 | 0.0566643427 |
| Win chance p = 50% · win pays 2× | 20.5 | 0.05708827 |
| Win chance p = 50% · win pays 2× | 21 | 0.057467269 |
| Win chance p = 50% · win pays 2× | 21.5 | 0.0578014415 |
| Win chance p = 50% · win pays 2× | 22 | 0.0580908771 |
| Win chance p = 50% · win pays 2× | 22.5 | 0.0583356534 |
| Win chance p = 50% · win pays 2× | 23 | 0.0585358358 |
| Win chance p = 50% · win pays 2× | 23.5 | 0.0586914778 |
| Win chance p = 50% · win pays 2× | 24 | 0.058802621 |
| Win chance p = 50% · win pays 2× | 24.5 | 0.0588692951 |
| Win chance p = 50% · win pays 2× | 25 | 0.0588915178 |
| Win chance p = 50% · win pays 2× | 25.5 | 0.0588692951 |
| Win chance p = 50% · win pays 2× | 26 | 0.058802621 |
| Win chance p = 50% · win pays 2× | 26.5 | 0.0586914778 |
| Win chance p = 50% · win pays 2× | 27 | 0.0585358358 |
| Win chance p = 50% · win pays 2× | 27.5 | 0.0583356534 |
| Win chance p = 50% · win pays 2× | 28 | 0.0580908771 |
| Win chance p = 50% · win pays 2× | 28.5 | 0.0578014415 |
| Win chance p = 50% · win pays 2× | 29 | 0.057467269 |
| Win chance p = 50% · win pays 2× | 29.5 | 0.05708827 |
| Win chance p = 50% · win pays 2× | 30 | 0.0566643427 |
| Win chance p = 50% · win pays 2× | 30.5 | 0.0561953728 |
| Win chance p = 50% · win pays 2× | 31 | 0.0556812339 |
| Win chance p = 50% · win pays 2× | 31.5 | 0.055121787 |
| Win chance p = 50% · win pays 2× | 32 | 0.0545168805 |
| Win chance p = 50% · win pays 2× | 32.5 | 0.0538663499 |
| Win chance p = 50% · win pays 2× | 33 | 0.0531700179 |
| Win chance p = 50% · win pays 2× | 33.5 | 0.0524276941 |
| Win chance p = 50% · win pays 2× | 34 | 0.0516391747 |
| Win chance p = 50% · win pays 2× | 34.5 | 0.0508042428 |
| Win chance p = 50% · win pays 2× | 35 | 0.0499226675 |
| Win chance p = 50% · win pays 2× | 35.5 | 0.0489942042 |
| Win chance p = 50% · win pays 2× | 36 | 0.0480185941 |
| Win chance p = 50% · win pays 2× | 36.5 | 0.0469955642 |
| Win chance p = 50% · win pays 2× | 37 | 0.0459248268 |
| Win chance p = 50% · win pays 2× | 37.5 | 0.0448060793 |
| Win chance p = 50% · win pays 2× | 38 | 0.0436390041 |
| Win chance p = 50% · win pays 2× | 38.5 | 0.0424232677 |
| Win chance p = 50% · win pays 2× | 39 | 0.0411585212 |
| Win chance p = 50% · win pays 2× | 39.5 | 0.0398443995 |
| Win chance p = 50% · win pays 2× | 40 | 0.0384805206 |
| Win chance p = 50% · win pays 2× | 40.5 | 0.0370664859 |
| Win chance p = 50% · win pays 2× | 41 | 0.0356018795 |
| Win chance p = 50% · win pays 2× | 41.5 | 0.0340862676 |
| Win chance p = 50% · win pays 2× | 42 | 0.0325191981 |
| Win chance p = 50% · win pays 2× | 42.5 | 0.0309002005 |
| Win chance p = 50% · win pays 2× | 43 | 0.0292287848 |
| Win chance p = 50% · win pays 2× | 43.5 | 0.0275044415 |
| Win chance p = 50% · win pays 2× | 44 | 0.0257266408 |
| Win chance p = 50% · win pays 2× | 44.5 | 0.0238948319 |
| Win chance p = 50% · win pays 2× | 45 | 0.0220084427 |
| Win chance p = 50% · win pays 2× | 45.5 | 0.0200668789 |
| Win chance p = 50% · win pays 2× | 46 | 0.0180695233 |
| Win chance p = 50% · win pays 2× | 46.5 | 0.0160157354 |
| Win chance p = 50% · win pays 2× | 47 | 0.0139048503 |
| Win chance p = 50% · win pays 2× | 47.5 | 0.0117361781 |
| Win chance p = 50% · win pays 2× | 48 | 0.0095090029 |
| Win chance p = 50% · win pays 2× | 48.5 | 0.0072225822 |
| Win chance p = 50% · win pays 2× | 49 | 0.0048761457 |
| Win chance p = 50% · win pays 2× | 49.5 | 0.0024688945 |
| Win chance p = 50% · win pays 2× | 50 | 0 |
| Win chance p = 50% · win pays 2× | 50.5 | −0.0025313972 |
| Win chance p = 50% · win pays 2× | 51 | −0.0051261882 |
| Win chance p = 50% · win pays 2× | 51.5 | −0.0077852975 |
| Win chance p = 50% · win pays 2× | 52 | −0.0105096836 |
| Win chance p = 50% · win pays 2× | 52.5 | −0.0133003409 |
| Win chance p = 50% · win pays 2× | 53 | −0.0161583007 |
| Win chance p = 50% · win pays 2× | 53.5 | −0.0190846331 |
| Win chance p = 50% · win pays 2× | 54 | −0.0220804479 |
| Win chance p = 50% · win pays 2× | 54.5 | −0.025146897 |
| Win chance p = 50% · win pays 2× | 55 | −0.0282851757 |
| Win chance p = 50% · win pays 2× | 55.5 | −0.0314965247 |
| Win chance p = 50% · win pays 2× | 56 | −0.0347822317 |
| Win chance p = 50% · win pays 2× | 56.5 | −0.0381436341 |
| Win chance p = 50% · win pays 2× | 57 | −0.0415821206 |
| Win chance p = 50% · win pays 2× | 57.5 | −0.045099134 |
| Win chance p = 50% · win pays 2× | 58 | −0.048696173 |
| Win chance p = 50% · win pays 2× | 58.5 | −0.0523747956 |
| Win chance p = 50% · win pays 2× | 59 | −0.0561366212 |
| Win chance p = 50% · win pays 2× | 59.5 | −0.059983334 |
| Win chance p = 50% · win pays 2× | 60 | −0.0639166858 |
| Win chance p = 40% · win pays 2× | 0 | 0 |
| Win chance p = 40% · win pays 2× | 0.5 | 0.0009726072 |
| Win chance p = 40% · win pays 2× | 1 | 0.0018908494 |
| Win chance p = 40% · win pays 2× | 1.5 | 0.0027553382 |
| Win chance p = 40% · win pays 2× | 2 | 0.0035666609 |
| Win chance p = 40% · win pays 2× | 2.5 | 0.0043253809 |
| Win chance p = 40% · win pays 2× | 3 | 0.0050320388 |
| Win chance p = 40% · win pays 2× | 3.5 | 0.0056871528 |
| Win chance p = 40% · win pays 2× | 4 | 0.0062912197 |
| Win chance p = 40% · win pays 2× | 4.5 | 0.0068447154 |
| Win chance p = 40% · win pays 2× | 5 | 0.0073480953 |
| Win chance p = 40% · win pays 2× | 5.5 | 0.0078017952 |
| Win chance p = 40% · win pays 2× | 6 | 0.0082062319 |
| Win chance p = 40% · win pays 2× | 6.5 | 0.0085618033 |
| Win chance p = 40% · win pays 2× | 7 | 0.0088688893 |
| Win chance p = 40% · win pays 2× | 7.5 | 0.0091278521 |
| Win chance p = 40% · win pays 2× | 8 | 0.0093390367 |
| Win chance p = 40% · win pays 2× | 8.5 | 0.0095027713 |
| Win chance p = 40% · win pays 2× | 9 | 0.0096193677 |
| Win chance p = 40% · win pays 2× | 9.5 | 0.0096891217 |
| Win chance p = 40% · win pays 2× | 10 | 0.0097123133 |
| Win chance p = 40% · win pays 2× | 10.5 | 0.0096892074 |
| Win chance p = 40% · win pays 2× | 11 | 0.0096200537 |
| Win chance p = 40% · win pays 2× | 11.5 | 0.0095050874 |
| Win chance p = 40% · win pays 2× | 12 | 0.0093445289 |
| Win chance p = 40% · win pays 2× | 12.5 | 0.009138585 |
| Win chance p = 40% · win pays 2× | 13 | 0.008887448 |
| Win chance p = 40% · win pays 2× | 13.5 | 0.008591297 |
| Win chance p = 40% · win pays 2× | 14 | 0.0082502973 |
| Win chance p = 40% · win pays 2× | 14.5 | 0.0078646013 |
| Win chance p = 40% · win pays 2× | 15 | 0.0074343481 |
| Win chance p = 40% · win pays 2× | 15.5 | 0.0069596639 |
| Win chance p = 40% · win pays 2× | 16 | 0.0064406624 |
| Win chance p = 40% · win pays 2× | 16.5 | 0.0058774444 |
| Win chance p = 40% · win pays 2× | 17 | 0.0052700987 |
| Win chance p = 40% · win pays 2× | 17.5 | 0.0046187014 |
| Win chance p = 40% · win pays 2× | 18 | 0.0039233167 |
| Win chance p = 40% · win pays 2× | 18.5 | 0.0031839965 |
| Win chance p = 40% · win pays 2× | 19 | 0.0024007809 |
| Win chance p = 40% · win pays 2× | 19.5 | 0.0015736979 |
| Win chance p = 40% · win pays 2× | 20 | 0.0007027639 |
| Win chance p = 40% · win pays 2× | 20.5 | −0.0002120168 |
| Win chance p = 40% · win pays 2× | 21 | −0.0011706515 |
| Win chance p = 40% · win pays 2× | 21.5 | −0.002173159 |
| Win chance p = 40% · win pays 2× | 22 | −0.0032195701 |
| Win chance p = 40% · win pays 2× | 22.5 | −0.0043099272 |
| Win chance p = 40% · win pays 2× | 23 | −0.0054442842 |
| Win chance p = 40% · win pays 2× | 23.5 | −0.0066227068 |
| Win chance p = 40% · win pays 2× | 24 | −0.0078452723 |
| Win chance p = 40% · win pays 2× | 24.5 | −0.0091120699 |
| Win chance p = 40% · win pays 2× | 25 | −0.0104232002 |
| Win chance p = 40% · win pays 2× | 25.5 | −0.011778776 |
| Win chance p = 40% · win pays 2× | 26 | −0.0131789217 |
| Win chance p = 40% · win pays 2× | 26.5 | −0.0146237737 |
| Win chance p = 40% · win pays 2× | 27 | −0.0161134803 |
| Win chance p = 40% · win pays 2× | 27.5 | −0.0176482021 |
| Win chance p = 40% · win pays 2× | 28 | −0.0192281117 |
| Win chance p = 40% · win pays 2× | 28.5 | −0.020853394 |
| Win chance p = 40% · win pays 2× | 29 | −0.0225242466 |
| Win chance p = 40% · win pays 2× | 29.5 | −0.0242408792 |
| Win chance p = 40% · win pays 2× | 30 | −0.0260035147 |
| Win chance p = 40% · win pays 2× | 30.5 | −0.0278123885 |
| Win chance p = 40% · win pays 2× | 31 | −0.0296677491 |
| Win chance p = 40% · win pays 2× | 31.5 | −0.0315698585 |
| Win chance p = 40% · win pays 2× | 32 | −0.0335189918 |
| Win chance p = 40% · win pays 2× | 32.5 | −0.0355154377 |
| Win chance p = 40% · win pays 2× | 33 | −0.037559499 |
| Win chance p = 40% · win pays 2× | 33.5 | −0.0396514924 |
| Win chance p = 40% · win pays 2× | 34 | −0.041791749 |
| Win chance p = 40% · win pays 2× | 34.5 | −0.0439806144 |
| Win chance p = 40% · win pays 2× | 35 | −0.0462184492 |
| Win chance p = 40% · win pays 2× | 35.5 | −0.0485056291 |
| Win chance p = 40% · win pays 2× | 36 | −0.0508425452 |
| Win chance p = 40% · win pays 2× | 36.5 | −0.0532296046 |
| Win chance p = 40% · win pays 2× | 37 | −0.0556672305 |
| Win chance p = 40% · win pays 2× | 37.5 | −0.0581558624 |
| Win chance p = 40% · win pays 2× | 38 | −0.0606959569 |
| Win chance p = 40% · win pays 2× | 38.5 | −0.0632879881 |
| Win chance p = 40% · win pays 2× | 39 | −0.0659324474 |
| Win chance p = 40% · win pays 2× | 39.5 | −0.0686298446 |
| Win chance p = 40% · win pays 2× | 40 | −0.0713807083 |
| Win chance p = 40% · win pays 2× | 40.5 | −0.074185586 |
| Win chance p = 40% · win pays 2× | 41 | −0.0770450448 |
| Win chance p = 40% · win pays 2× | 41.5 | −0.0799596723 |
| Win chance p = 40% · win pays 2× | 42 | −0.0829300766 |
| Win chance p = 40% · win pays 2× | 42.5 | −0.0859568873 |
| Win chance p = 40% · win pays 2× | 43 | −0.0890407558 |
| Win chance p = 40% · win pays 2× | 43.5 | −0.0921823564 |
| Win chance p = 40% · win pays 2× | 44 | −0.0953823864 |
| Win chance p = 40% · win pays 2× | 44.5 | −0.0986415675 |
| Win chance p = 40% · win pays 2× | 45 | −0.101960646 |
| Win chance p = 40% · win pays 2× | 45.5 | −0.1053403938 |
| Win chance p = 40% · win pays 2× | 46 | −0.1087816092 |
| Win chance p = 40% · win pays 2× | 46.5 | −0.1122851181 |
| Win chance p = 40% · win pays 2× | 47 | −0.1158517742 |
| Win chance p = 40% · win pays 2× | 47.5 | −0.1194824608 |
| Win chance p = 40% · win pays 2× | 48 | −0.1231780911 |
| Win chance p = 40% · win pays 2× | 48.5 | −0.1269396099 |
| Win chance p = 40% · win pays 2× | 49 | −0.1307679941 |
| Win chance p = 40% · win pays 2× | 49.5 | −0.1346642543 |
| Win chance p = 40% · win pays 2× | 50 | −0.1386294361 |
| Win chance p = 40% · win pays 2× | 50.5 | −0.142664621 |
| Win chance p = 40% · win pays 2× | 51 | −0.1467709282 |
| Win chance p = 40% · win pays 2× | 51.5 | −0.1509495156 |
| Win chance p = 40% · win pays 2× | 52 | −0.1552015819 |
| Win chance p = 40% · win pays 2× | 52.5 | −0.1595283677 |
| Win chance p = 40% · win pays 2× | 53 | −0.1639311574 |
| Win chance p = 40% · win pays 2× | 53.5 | −0.1684112811 |
| Win chance p = 40% · win pays 2× | 54 | −0.1729701162 |
| Win chance p = 40% · win pays 2× | 54.5 | −0.1776090896 |
| Win chance p = 40% · win pays 2× | 55 | −0.1823296798 |
| Win chance p = 40% · win pays 2× | 55.5 | −0.1871334191 |
| Win chance p = 40% · win pays 2× | 56 | −0.1920218958 |
| Win chance p = 40% · win pays 2× | 56.5 | −0.1969967568 |
| Win chance p = 40% · win pays 2× | 57 | −0.2020597106 |
| Win chance p = 40% · win pays 2× | 57.5 | −0.2072125292 |
| Win chance p = 40% · win pays 2× | 58 | −0.2124570519 |
| Win chance p = 40% · win pays 2× | 58.5 | −0.2177951882 |
| Win chance p = 40% · win pays 2× | 59 | −0.2232289208 |
| Win chance p = 40% · win pays 2× | 59.5 | −0.2287603096 |
| Win chance p = 40% · win pays 2× | 60 | −0.234391495 |
| Fraction lost on failure | Win / loss wealth multipliers | Log growth: p = 50% | Log growth: p = 40% |
|---|---|---|---|
| 0.00% | Win / loss wealth multipliers1.00 / 1.00 | Log growth: p = 50%0.000000 | Log growth: p = 40%0.000000 |
| 10.00% | Win / loss wealth multipliers1.20 / 0.90 | Log growth: p = 50%+0.038481 | Log growth: p = 40%+0.009712 |
| 25.00% | Win / loss wealth multipliers1.50 / 0.75 | Log growth: p = 50%+0.058892 | Log growth: p = 40%−0.010423 |
| 40.00% | Win / loss wealth multipliers1.80 / 0.60 | Log growth: p = 50%+0.038481 | Log growth: p = 40%−0.071381 |
| 60.00% | Win / loss wealth multipliers2.20 / 0.40 | Log growth: p = 50%−0.063917 | Log growth: p = 40%−0.234391 |
The best size falls from 25% to 10% when the win chance falls from 50% to 40%. At 25%, the second case already shrinks wealth.
Two fixed outcomes, known odds, any bet size, no costs. The odds are invented. Log growth is not a rupee or percentage return, and this does not show an options edge or an allocation.
Inspect the binary log-growth model
Natural logarithms act on the two wealth multipliers; b denotes net win divided by the amount lost.
g(f) = p × ln(1 + b × f) + (1 − p) × ln(1 − f)For 0 < p < 1 and b > 0: constrained optimum = max(0, p − (1 − p) / b)p = 0.50, b = 2: f* = 0.25; p = 0.40, b = 2: f* = 0.10A non-positive edge gives a zero non-negative-wager optimum; missing probability inputs give no calculation.
With p = 50% and b = 2, the best fraction is 25%. Expected log growth there is about 0.05889 per trial. At 10% or 40% it is about 0.03848, and at 60% it turns negative. These are log numbers for this toy game. They are not percentage returns and not advice to risk 25%.
Now change p to 40%, with b still 2. The best fraction drops to 10%, and the old 25% bet gives negative growth. A small error in the odds can turn a good size into a bad one. Real trades have costs, jumps and positions that move together. Full Kelly is not a safe ceiling, and betting less than Kelly does not guarantee survival. The curve offers no measured NIFTY edge.
How much do all your open positions risk together?
Add up the risk of all open positions together.
Short answer: add the allowances, then test one shared market move. Four positions that each carry a ₹5,000 allowance on a ₹5 lakh account carry ₹20,000 together, or 4%. That sum holds whether the positions are related or not. Relatedness matters for how they move together, not for the addition.
Add the allowances, then test a joint outcome
A ₹5,00,000 account, four positions, ₹5,000 allowance each. Two stress cases give every position the same loss.
Planned allowance ledger
- Four allowances of ₹5,000
- ₹20,000.00
4.00% of starting equity; the sum is unchanged by dependence between positions.
- Funds and clearing margin
- Separate check
No margin, premium availability or delivery-funding requirement is computed here.
Separate assumed stress case 1
- Loss on each of four positions
- −₹3,500.00
- Combined account P&L
- −₹14,000.00
2.80% loss of starting equity; this is a scenario assumption, not a probability estimate.
Separate assumed stress case 2
- Loss on each of four positions
- −₹7,500.00
- Combined account P&L
- −₹30,000.00
6.00% loss of starting equity; this is a scenario assumption, not a probability estimate.
| Position | Planned allowance | Stress 1: assumed P&L | Stress 2: assumed P&L |
|---|---|---|---|
| Position 1 | Planned allowance₹5,000.00 | Stress 1: assumed P&L−₹3,500.00 | Stress 2: assumed P&L−₹7,500.00 |
| Position 2 | Planned allowance₹5,000.00 | Stress 1: assumed P&L−₹3,500.00 | Stress 2: assumed P&L−₹7,500.00 |
| Position 3 | Planned allowance₹5,000.00 | Stress 1: assumed P&L−₹3,500.00 | Stress 2: assumed P&L−₹7,500.00 |
| Position 4 | Planned allowance₹5,000.00 | Stress 1: assumed P&L−₹3,500.00 | Stress 2: assumed P&L−₹7,500.00 |
| Account total | Planned allowance₹20,000.00 | Stress 1: assumed P&L−₹14,000.00 | Stress 2: assumed P&L−₹30,000.00 |
Allowances add to ₹20,000, or 4%. The first stress loses ₹14,000 (2.80%); the second loses ₹30,000 (6.00%), more than the plan. Different names can share one driver.
Each case adds four losses from one assumed market state. These are made-up amounts, not forecasts or maximum losses. Real gaps, costs and fills can differ.
Inspect the account-wide addition
Allowances are positive planning amounts; scenario P&Ls carry their actual signs.
Planned sum = 4 × 5000 = ₹20,000.00 = 4.00% of starting equityStress 1 P&L = 4 × (−3500) = −₹14,000.00Stress 2 P&L = 4 × (−7500) = −₹30,000.00
A single NIFTY move can hit your Calls, your futures and your bank stocks at once. Pick one move, work out each position's own result, and add the signed rupees. In the separate example below, four scenario losses of ₹3,500 total ₹14,000, and four stress losses of ₹7,500 total ₹30,000, which is more than the combined allowance. Neither case claims a probability, or that everything always falls together.
Events, thin liquidity, costs and limited funds can all be reasons to trade smaller than the formula allows. A written account rule for what you do at a drawdown boundary helps, but it has costs too, and it does not promise a recovery. India VIX does not set your stop width. Keep your inputs, contracts, whole quantities and real fills on record. The next lesson separates a planned risk from a loss that actually happened.
Before you go
Check yourself
5 questions from this lesson. Pick an answer to see why, then slide on to the next.
Question 1 of 5
01The fictional ₹5,00,000 account uses a 1% allowance. A futures exit estimate is 150 points away, with 65 assumed units per lot. What quantity fits before costs and funding checks?
02In the separate one-lot futures execution scenario, entry is 25,000 and the actual exit is 24,750 for 65 assumed units. What is the result before costs?
03The separate ₹10,00,000 example assumes a 2% allowance, ₹4,550 spread loss per lot, and ₹1,80,000 funding both available and required per lot. What fits both simplified constraints?
04After one assumed ₹5,000 loss, equity is ₹4,95,000. What does recalculating the same hypothetical 1% allowance produce?
05In the separate binary model, a win earns twice the amount risked and the assumed win probability changes from 50% to 40%. What happens to the log-growth optimum?

0 of 5
Some questions are still open: go back and answer them.
Questions readers ask
Common questions
01How do I calculate whole lots for a hypothetical NIFTY futures position?
Multiply equity by your loss fraction to get the allowance. Divide it by the planned loss on one lot (points × units), then round down. In the example, ₹5,00,000 × 1% = ₹5,000, and 150 points × 65 units = ₹9,750 per lot. ₹5,000 ÷ ₹9,750 is about 0.513, so the answer is 0 lots. The 65-unit lot is an assumption; use the dated lot size of the contract you trade.
02What does zero lots mean in a position-sizing calculation?
It means this position does not fit this allowance. One lot would put 1.95% of the account at risk against a 1% allowance. Zero is a valid answer, not an error. Moving your exit closer only to force one lot changes the plan to fit the answer; it does not make the trade safer.
03Does a stop-loss order cap the loss at the amount used for sizing?
No. A stop triggers an order, but it does not fix the fill price. In the example, a fill at 24,750 after entry at 25,000 loses 250 × 65 = ₹16,250, not the ₹9,750 planned at 24,850. For an option, measure the loss in premium rupees, not index points.
04Is a bought option sized from its premium, and what changes for stock options?
Yes, for a standalone bought index Call the most you can lose is the premium: ₹100 × 65 = ₹6,500 before costs, which gives 0 lots against ₹5,000. A planned earlier sale can use a smaller estimate, but label it a plan, not the maximum. Stock options settle by delivery, so an exercised Call needs strike money and an exercised Put needs shares. The premium limit does not cap that funding or later losses on the shares.
05How does fixed-fraction sizing differ from fixed cash or fixed lots after a loss?
Fixed-fraction sizing recalculates the allowance from current equity: after a ₹5,000 loss, 1% of ₹4,95,000 is ₹4,950. Fixed cash keeps ₹5,000, a larger share of a smaller account. Fixed lots keep the quantity, and the rupee loss stays constant only if the per-unit loss does. None of these guarantees survival. Recovery is measured on what is left: a 20% loss needs a 25% gain.
06How do spread loss and available margin constrain the final lot count?
Take the smaller of two whole-lot limits. The Call spread loses at most (100 − 30) × 65 = ₹4,550 per lot, so a ₹20,000 allowance on ₹10,00,000 permits four lots. If only ₹1,80,000 is free and each lot needs ₹1,80,000, funding permits one. The answer is one. Real margin changes with your other positions and is collateral, not a loss cap.
07Can Kelly determine a suitable risk percentage for live options trading?
No. Kelly solves a simple repeated game with known odds. With a 50% win chance and a win twice the size of a loss, the best size is 25%; at a 40% chance it is 10%. Real trades have costs, jumps and unknown odds, and an unknown chance is not 50%. Treat Kelly as a way to see how sensitive size is to the odds, not as an allocation.
08Do separate positions each get an independent account risk allowance?
No. Look at the whole account. Two ₹5,000 allowances add to ₹10,000. Under a ₹12,000 account limit only ₹2,000 remains, so a third ₹5,000 fails. Positions with different names can share one driver, so test them together under one market move and check cash and collateral for all of them.
Sources for further reading
17 sources- nseindia.comNSE NIFTY 50 specifications — contract size defers to the dated contract file (read 6 November 2026)
- archives.nseindia.comNSE/FAOP/70616, 3 October 2025 — historical 75-to-65 NIFTY lot revision and transition dates
- sebi.gov.inSEBI 2024/132, 1 October 2024 — contract-value review band and upfront buyer premium; not account loss limits
