Anti-Martingale Strategy: Sizing Up When Your Trades Are Working

The anti-martingale strategy is a position-sizing rule that does the opposite of what most losing traders do by instinct. Instead of adding money after a loss to “win it back”, you put a little more at risk after a win and cut back after a loss. Your trade size rises when the account is doing well and shrinks when it isn’t. Simple to say. Surprisingly hard to stick to.

We’ll walk through where the idea comes from, how traders in India actually use it, two worked examples in rupees, and the one situation where it quietly hurts you. If you’ve read our piece on the martingale strategy, think of this as its mirror image.

What is the anti-martingale strategy?

The name comes from the gambling table. The classic martingale was a family of betting systems that became popular in 18th-century France. The simplest version had the player double the stake after every loss, so that the first win would recover all previous losses and leave a profit equal to the original bet. The Wikipedia entry on the martingale betting system describes the anti-martingale, also called the reverse martingale, as the flip: raise the bet after wins and reduce it after a loss.

The logic gamblers give for it is the “hot hand”. Press while you’re winning, pull back when you’re cold. That same entry is blunt about the casino version, though: in practice the anti-martingale system fails to generate a profit. That matters, and we’ll come back to it, because it tells you exactly what this rule can and can’t do for a trader.

Here’s the key point. A sizing rule changes how much you win or lose on each trade. It does not change whether your trades have an edge. At a roulette wheel, every bet has a negative expected value, so no way of sizing those bets turns the total positive. In trading, the sizing rule sits on top of your entries and exits. If those have no edge, no staking plan rescues them.

How traders use it in practice

Nobody sensible on Dalal Street doubles their position after every winning trade. What traders call anti-martingale usually looks like one of three gentler versions.

1. Risk a fixed percentage of current equity

This is the quiet, automatic version. You decide to risk, say, 1% of your account on each trade. When the account grows, 1% is a bigger rupee number, so position size rises. When the account shrinks, 1% is a smaller number, so you trade smaller. Our guide to fixed fractional position sizing covers the mechanics. It’s anti-martingale in spirit without any extra rules.

2. Step up after wins, reset after a loss

Here you set a base risk per trade and a ladder. After each win you move one step up. After any loss you drop straight back to the base. There’s always a ceiling so a long winning run can’t push you into a reckless size.

3. Add to a winning position

Some traders apply the idea inside a single trade. They start with a partial position and add only when price moves in their favour, never to a loser. This is usually called pyramiding. The total risk still has to be capped, and the stop on the full position has to move up as you add, or one sharp reversal wipes out the gains of the whole run.

A sizing rule decides how loud each trade is. It has no say in whether the trade was a good idea in the first place.

A quick word on “R”

The examples below use R, the amount you risk on a trade, meaning the rupee loss if your stop-loss is hit. A trade that makes twice what it risked is a +2R trade. A trade that hits its stop is a −1R trade. Using R lets us compare sizing rules without worrying about which stock or price level was involved. If you want to see how R ties into whether a system makes money over time, our post on trading expectancy goes into it.

Worked example 1: a trending stretch

All figures in both examples are hypothetical and chosen only to show the arithmetic.

Say a swing trader, call her Meera, starts with a ₹5,00,000 account. Her rules:

• Base risk: ₹5,000 per trade (1% of the starting account).
• After each win, raise the risk by ₹2,500.
• Ceiling: ₹10,000 per trade, however long the winning streak.
• After any loss, reset to ₹5,000.
• Every winner makes 2R. Every loser loses 1R.

Her next seven trades go: win, win, win, loss, win, loss, loss.

Net result: +₹32,500.

Now run the same seven trades with a flat ₹5,000 risk every time. Four wins at +₹10,000 each make ₹40,000. Three losses at −₹5,000 each cost ₹15,000. Net: +₹25,000.

So the step-up rule added ₹7,500 here. Why? Because the three wins came back to back at the start. Meera was at her largest size exactly when the trades were working. That’s the whole bet the anti-martingale makes: that good trades tend to cluster, usually because the market is trending and your setup suits a trend.

Worked example 2: a choppy stretch

Same rules, same account, but this time the market is going sideways and the results alternate: win, loss, win, loss, win, loss.

Net result: +₹7,500.

Flat sizing on the same six trades: three wins at +₹10,000 make ₹30,000, three losses at −₹5,000 cost ₹15,000. Net: +₹15,000.

The step-up rule earned half as much. Every loss landed right after a win, which meant every loss was taken at the bigger size, and every win was taken at the smaller one. Same hit rate, same 2:1 payoff, very different outcome.

In a trending market the anti-martingale puts your biggest size on your best run. In a choppy one it puts your biggest size on the trade right before the stop gets hit.

Where the edge really comes from

Put the two examples side by side and the pattern is clear. The anti-martingale does better when wins and losses come in streaks, and worse when they alternate. It doesn’t create profit. It shifts the outcome depending on the order in which results arrive.

That’s why the gambling version fails. In a fair or casino-weighted game, each spin is independent. The martingale entry on Wikipedia makes this point about all martingale-type systems: no amount of information about past bets can predict the next one better than chance, so there are no real streaks to exploit, only random ones.

Markets are not a roulette wheel, but traders shouldn’t assume streaks either. Whether your own results cluster is something you can check. Pull your last 50 or 100 trades from your journal and look at what tends to follow a win. If a win is no more likely to be followed by another win than a loss is, a step-up rule is mostly adding noise. If your wins really do bunch up during trending phases, the rule has something to work with.

The link with Kelly-style sizing

There’s a more formal cousin worth knowing. The Kelly criterion, described by Bell Labs researcher John Larry Kelly Jr. in 1956, sizes each bet as a fraction of current wealth so as to maximise long-run geometric growth. Because the bet is a fraction of what you have now, it grows as the account grows and shrinks after losses. That’s anti-martingale behaviour baked into the formula.

The same Wikipedia article makes two points that matter for traders. First, betting more than the Kelly amount increases the risk of ruin. Second, many gamblers deliberately bet a fraction of full Kelly, such as half or a quarter, to reduce the chance of ruin, cut volatility and allow for errors in their estimates, accepting slower growth in return. The lesson carries straight over to a trading account: whatever ladder you use, the ceiling matters more than the steps.

Rules that keep the anti-martingale from turning reckless

1. Set a hard ceiling. Decide the maximum risk per trade before the streak starts, when you’re calm. In our example it was 2% of the starting account. Don’t raise it mid-run because you “feel it”.
2. Reset fully after a loss. Halfway resets slowly turn the system back into flat sizing at a higher level, which is just more risk.
3. Keep the steps small. Going from ₹5,000 to ₹7,500 is a 50% jump in risk. That’s already aggressive for most retail accounts. Smaller steps reduce the damage when the choppy pattern from example 2 shows up.
4. Watch total open risk, not just per-trade risk. If you hold five positions at your top size and they’re all in the same sector, one bad day for that sector hits all of them together.
5. Respect leverage limits. In futures and options, a bigger position means a bigger margin block and bigger mark-to-market swings. A step-up rule can push you towards your margin limit faster than you expect.
6. Test it on your own history first. Replay your last year of trades with flat sizing and with your step-up rule. If the step-up only wins because of one lucky streak, treat that as a warning.

Anti-martingale versus martingale, briefly

The martingale adds risk after a loss. It feels comforting because most sequences end in a small win, but the rare long losing run grows the stake geometrically and can empty the account. The anti-martingale adds risk after a win. Its losses are capped by design, since you’re always back at base size after a loss, but it gives back profit when results alternate.

Between the two, the anti-martingale is the far safer habit for a trader, because the worst case is a slower equity curve, not a blown account. For most retail traders, though, the plainest version, a fixed small percentage of current equity, does most of the job with none of the temptation. Our pillar guide on risk management in trading lays out how that fits with stop-losses and overall exposure.

Is the anti-martingale strategy for you?

It suits traders whose method genuinely does better in trends, such as breakout and momentum traders, and who have the discipline to reset after a loss without arguing with themselves. It suits mean-reversion traders less, because their results often alternate by nature.

If you’re starting out, don’t begin with a ladder. Begin with fixed fractional sizing at a small percentage. Keep a clean trade journal for a few months. Then look at whether your wins cluster. If they do, a gentle step-up with a firm ceiling is a reasonable next experiment. If they don’t, you’ve saved yourself from adding complexity that only feels clever.

Sources

• Wikipedia: Martingale (betting system), including the anti-martingale section
• Wikipedia: Kelly criterion

Disclaimer: This article is for education only and is not investment advice. Meera and all figures in the worked examples are hypothetical. Trading in equities and derivatives involves risk of loss; consult a SEBI-registered investment adviser before making any investment decision.