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Spencer Li

Kelly Criterion Position Sizing: What the Formula Says, and Why Full Kelly Is Too Much

Risk & Money Management
Kelly criterion position sizing - position sizing

Last updated: 20 July 2026 · By Spencer Li, CFTe


The Kelly criterion is a formula for how much of your account to risk on each trade so that the account grows as fast as possible over the long run. For trading, it reads: Kelly % = W − (1 − W) ÷ R, where W is your win rate and R is your average win divided by your average loss.

A hypothetical example: a strategy wins 50% of the time and its average win is twice its average loss. Kelly says to risk 0.5 − 0.5 ÷ 2, which is 25% of the account on every trade. Most traders risk 1% to 2%.

That gap is the whole story of this post. Full Kelly is the mathematically fastest growth rate, and it comes with drawdowns almost nobody can sit through. Most traders who use Kelly at all use half of it or less, and treat it as a ceiling on their position size instead of a target.

Use Kelly as a ceiling, not a target. Summary card for the post: Kelly Criterion Position Sizing: What the Formula Says, and Why Full Kelly Is Too Much.

Where does the Kelly criterion come from?

From a 1956 paper by J. L. Kelly Jr., a researcher at Bell Labs, titled “A New Interpretation of Information Rate.” He was working on how a gambler with an edge should size bets to grow wealth fastest over many rounds. Traders borrowed it because a trade with a stop loss looks a lot like a bet: a known amount at risk, a chance of winning, and a payoff if it works.

The formula needs 3 inputs, the same 3 that give you your trading expectancy: the win rate, the average win and the average loss. Here is what it says for a few hypothetical strategies:

Win rateAverage win ÷ average lossKelly % (share of account to risk per trade)
30%2−5%, so do not trade it
40%210%
55%110%
40%2.516%
60%120%
50%225%
50%333.3%

Do note the first row. When a strategy has no edge, Kelly comes out at zero or below. That is the formula’s most useful answer, and it costs nothing to apply.

Why is full Kelly too much for real trading?

Because the fastest growth comes with brutal swings along the way. Take the 50% win rate, 2-to-1 strategy, where full Kelly is 25%.

At 25% risk, 4 losses in a row take the account down 68.4%. With a 50% win rate, the chance of at least one run of 4 straight losses somewhere in 100 trades is 97.3%. It will happen, probably more than once. At 1% risk the same 4 losses cost 3.9%.

I ran the same strategy through 1,000 simulated trades, thousands of times over, at different fractions of Kelly:

SizingRisk per tradeGrowth, as a share of full Kelly’sChance the account falls to half its startChance of a 50% fall from a peak
Full Kelly25%100%42.6%100%
Half Kelly12.5%76.1%10.8%100%
Quarter Kelly6.25%45.2%0.7%62.7%

Hypothetical, 50% win rate, average win 2R, each trade independent, 1,000 trades per run.

Half Kelly keeps about three quarters of the growth and cuts the chance of halving the account by about three quarters. That trade-off is why it is the common choice among traders who use Kelly at all. Even so, look at the last column. At half Kelly, a 50% drop from a high point still turned up in every single simulated run, which tells you how aggressive even “conservative” Kelly is for most people.

Going the other way is worse. At twice full Kelly the long-run growth rate falls to zero, and anything beyond that shrinks the account over time, even with a real edge.

Long-run growth against risk per trade: the curve peaks at full Kelly, half Kelly sits on the curve not far below the peak, and growth falls back to zero at twice Kelly
Half Kelly keeps about three quarters of full Kelly’s growth for far less risk.

If you want a daily routine that keeps every position inside your limits, the free 15-Minute Swing Trader’s Checklist is at the end of this post.

What if your win rate is wrong?

This is the strongest objection to Kelly, and it is a good one. A trader on r/algotrading titled his July 2025 post “The Flaw in the Kelly Criterion – Betting Under Uncertainty”. Kelly assumes you know your true win rate and payoff. You never do. You only have an estimate, taken from a limited number of past trades.

The concession matters, because Kelly punishes overestimates hard. Say you measured a 50% win rate at 2-to-1 and sized at 25%, but the true win rate is 45%. The true Kelly figure is 17.5%, so you are betting more than 1.4 times the right amount. In that case, half of your estimated Kelly, 12.5%, actually grows the account faster than the full 25% you calculated.

So the uncertainty itself is a reason to size down. A win rate measured over 30 trades can easily be several points off the truth, which is why the law of large numbers matters before any sizing formula does.

How should a swing trader actually use Kelly?

As a ceiling. Work out full Kelly from at least 100 recorded trades, then treat it as the absolute maximum you could ever justify risking on one trade. Your real risk per trade sits far below it.

This is Kelly as a ceiling, and it does 2 useful jobs. First, it is a quick edge test. A Kelly figure at or below zero tells you to stop and look at the strategy. Second, it is a sanity check on your sizing. If your risk per trade is anywhere near the Kelly figure, you are taking far more risk than you need to.

For the day-to-day number, most swing traders use a fixed fraction of the account, typically 1% to 2% per trade. The 2% money management rule for position sizing walks through how to turn that into a share count. A fixed small fraction grows more slowly than Kelly in theory, and it keeps you far away from the drawdowns in the table above, which is where risk of ruin lives.

Personally, I treat Kelly as an upper bound and size well below it. The exact sizing rules we teach stay in the course, but the principle is simple enough to use today: if the formula and your nerves disagree, believe your nerves and bet smaller.

The full map of these ideas is in the practical guide to money and risk management.

The formula said 25%. It was right about the growth, and it said nothing about the morning you open the account to find two thirds of it gone.

FAQ

What is the Kelly criterion formula for trading?

Kelly % = W − (1 − W) ÷ R, where W is the win rate and R is the average win divided by the average loss. The answer is the share of the account to risk per trade.

Is the Kelly criterion good for trading?

It is useful as an edge test and as an upper limit on size. Used at full strength, it produces drawdowns most traders cannot sit through.

What is half Kelly?

Risking half of what the Kelly formula gives. In the example above it kept about 76% of the long-run growth while cutting the chance of halving the account from 42.6% to 10.8%.

What does a negative Kelly number mean?

It means the strategy has no edge on the numbers you entered. The formula’s answer is to risk nothing.

How many trades do I need before using Kelly?

At least 100, and more is better. A win rate measured on a small sample is often several points off, and Kelly turns that error into oversized bets.

Go deeper

The free 15-Minute Swing Trader’s Checklist has the daily routine, the questions to ask before every trade, and the five rules that keep you in the game.


About the author. Spencer Li is The 15-Minute Trader and the founder of Synapse Trading. He is a Certified Financial Technician (CFTe) with 15+ years of trading, run from 70+ countries. He holds a B.Acc and B.BM from SMU. Every trade he takes is public, dated, losses left in. He teaches low-risk swing trading in 15 minutes a day, one system for any market.

Educational content only, not personalised financial advice. Trading carries risk, including loss of capital. Past performance is not indicative of future results. Synapse Trading is not licensed or regulated by MAS.

by Spencer Li
https://synapsetrading.com/wp-content/uploads/2026/10/kelly-criterion-position-sizing-card.webp 630 1200 Spencer Li https://synapsetrading.com/wp-content/uploads/2026/10/synapse-logo-horizontal-light.png Spencer Li2026-06-29 17:21:112026-07-20 15:18:20Kelly Criterion Position Sizing: What the Formula Says, and Why Full Kelly Is Too Much
Spencer Li

Win Rate vs Risk Reward: Why a 70% Win Rate Can Still Lose Money

Risk & Money Management
Win rate vs risk reward - risk management

Last updated: 15 October 2026 · By Spencer Li, CFTe


A high win rate does not make a strategy profitable. Whether you make money depends on 2 numbers together: how often you win, and how big your average win is compared with your average loss. That second number is the reward-to-risk ratio.

The 2 are tied by one simple line. The win rate you need to break even is 1 divided by (1 + your reward-to-risk ratio). If your average win is twice your average loss, you need to win a little over 33% of the time. If your average win is only half your average loss, you need to win more than 66.7% of the time.

That is how a 70% win rate can still lose money. If the average win is smaller than about 0.43 times the average loss, 70% sits below the line. And a 30% win rate can make money, as long as the winners are big enough.

A 70% win rate can still lose money. Summary card for the post: Win Rate vs Risk Reward: Why a 70% Win Rate Can Still Lose Money.

Why can a 70% win rate still lose money?

Because the wins are too small to pay for the losses. A trader on r/Daytrading summed up the problem in January 2026: a “70% Win rate” and “still not profitable.”

Here is how that happens, with one hypothetical set of round numbers. You make 100 trades and win 70 of them. Each win makes 0.4R, where R is the amount you risk on a trade. Each loss costs the full 1R.

  • 70 wins × 0.4R = 28R
  • 30 losses × 1R = 30R
  • Net after 100 trades: −2R

Most days end green. Most weeks feel like progress. And after 100 trades the account is a little smaller than where it started. The pattern is common in strategies that grab small profits fast and let losing trades run all the way to the stop, or past it.

A column of 70 thin wins stacked beside a column of 30 full losses; the stacked losses stand slightly taller
Seventy small wins can still add up to less than thirty full losses.

What win rate do you need at each reward-to-risk ratio?

This is the breakeven line, worked out for the ratios traders use most:

Reward-to-risk (average win ÷ average loss)Breakeven win rate
0.2580%
0.566.7%
150%
1.540%
233.3%
325%

The formula behind it: breakeven win rate = 1 ÷ (1 + reward-to-risk). At 2 to 1, that is 1 ÷ 3, or 33.3%.

Read each row as the floor, since a real strategy needs to sit comfortably above it once commissions, spreads and slippage have come off the top of every single trade you take over a year. A strategy that only just clears its breakeven line on paper usually falls below it in a live account.

Which matters more, win rate or reward-to-risk?

Neither one, on its own. What matters is the combination, and the number that captures it is expectancy: the average amount you make or lose per trade, measured in R.

Expectancy = (win rate × average win) − (loss rate × average loss)

Here are 4 hypothetical strategies, each risking 1R per trade:

StrategyWin rateAverage winAverage lossExpectancy per trade
A, the frequent winner70%0.4R1R−0.02R
B, the coin flip50%2R1R+0.5R
C, the rare winner30%3R1R+0.2R
D, the even split40%1.5R1R0

Strategy A wins most often and is the only one that loses money. Strategy C loses 7 trades in every 10 and still comes out ahead. The full method, including how to work out your own numbers, is in the trading expectancy formula.

If you want a daily routine that checks the ratio before every trade, the free 15-Minute Swing Trader’s Checklist is at the end of this post.

Is a higher reward-to-risk ratio always better?

Here is the strongest case against chasing big ratios, and it deserves a fair hearing. In December 2025 a trader on r/Daytrading said that holding out for targets 3 times the risk “is psychological torture”. He described taking 8 losses in a row while waiting for one big winner, and how it wore down his confidence. He switched to a high win rate style and felt far better.

He has a point, and the maths backs him up. Low win rates bring long losing streaks, and they bring them often. Here is the chance of at least one run of 8 straight losses somewhere in 100 trades, assuming each trade is independent:

Win rateChance of 8 or more losses in a row within 100 trades
30%85.8%
33.3%75.3%
40%49.0%
50%17.0%
70%0.4%

At a 33% win rate, a streak like his is more likely than not. If that streak makes you skip the next setup, or abandon the plan halfway through a rough month, the reward-to-risk ratio that looked so good on paper never actually reaches your trading account.

So the right balance is the one you can actually follow. Where I differ from him is on the fix. Choose your trade-off on purpose, measure it, and size each trade small enough that a long streak is survivable. At 1% risk per trade, 8 straight losses cost about 7.7% of the account. That hurts. It does not end anything.

Personally, I sit in the middle. My closed trades win roughly half the time, and the average win has been about 3 times the average loss. The record is public: every trade since April 2024, dated, losses left in.

How do you change your reward-to-risk ratio?

Through where your stop and target sit, and through what you do once the trade is open.

  • The stop. A stop placed inside the normal noise gets hit often, which drags the win rate down. How to place it beyond the level that matters is in where to put your stop loss and take profit.
  • The target. Set it near the closest level where the move is likely to stall, and pass on trades where that level sits less than about 2R away.
  • The loss you let run. Moving the stop further away “to give it room” turns a 1R loss into a 2R loss. It is the fastest way to wreck a good ratio, and the psychology of the stoploss explains why it is so tempting.

Do note that the 2 numbers pull against each other. A wider target usually lowers the win rate, and a tighter one raises it. You do not get to set both. The market sets the trade-off, and you choose where on it to stand.

You only know your own 2 numbers if you write every trade down, which is the case for keeping a trading journal. For the full map of these ideas, read the practical guide to money and risk management.

Strategy A would have felt like the best of the 4 for most of the year, right up to the evening someone added up the R.

FAQ

What is a good win rate for trading?

There is no good win rate on its own. A 40% win rate is strong with winners twice the size of the losers, while 70% loses money if the winners are under 0.43 times the losers.

What is a good risk-reward ratio?

Many swing traders aim for at least 2 to 1. That ratio needs a win rate above 33.3% to break even, before costs.

How do you calculate the breakeven win rate?

Divide 1 by 1 plus your reward-to-risk ratio. At 1.5 to 1, that is 1 ÷ 2.5, which is 40%.

Can you be profitable with a 30% win rate?

Yes, if the average win is comfortably more than about 2.33 times the average loss. Expect long losing streaks along the way.

Is a 1 to 1 risk-reward ratio good?

It can work, but it needs a win rate clearly above 50% after costs. That leaves very little room for error.

Go deeper

The free 15-Minute Swing Trader’s Checklist has the daily routine, the questions to ask before every trade, and the five rules that keep you in the game.


About the author. Spencer Li is The 15-Minute Trader and the founder of Synapse Trading. He is a Certified Financial Technician (CFTe) with 15+ years of trading, run from 70+ countries. He holds a B.Acc and B.BM from SMU. Every trade he takes is public, dated, losses left in. He teaches low-risk swing trading in 15 minutes a day, one system for any market.

Educational content only, not personalised financial advice. Trading carries risk, including loss of capital. Past performance is not indicative of future results. Synapse Trading is not licensed or regulated by MAS.

by Spencer Li
https://synapsetrading.com/wp-content/uploads/2026/10/win-rate-vs-risk-reward-card.webp 630 1200 Spencer Li https://synapsetrading.com/wp-content/uploads/2026/10/synapse-logo-horizontal-light.png Spencer Li2026-06-19 19:32:212026-10-15 12:33:25Win Rate vs Risk Reward: Why a 70% Win Rate Can Still Lose Money
Spencer Li

Why Risk Management Is Important in Trading (More Than Your Strategy)

Risk & Money Management
Why risk management matters - risk management

Last updated: 27 September 2026 · By Spencer Li, CFTe


Risk management is important in trading because it decides whether you are still in the game when your strategy’s edge finally shows up. A strategy tells you which trades to take. Risk management tells you how much each one is allowed to cost, and that decides whether an ordinary run of losses is a dull month or the end of the account.

That is why 2 traders can run the exact same strategy and end up in very different places. The maths of losing is lopsided, since a 50% loss needs a 100% gain just to get back to where you started. And losing streaks are normal, even for a strategy that works. So the size of each bet ends up mattering more than the cleverness of each entry.

In this post I’ll show the arithmetic behind that, with round hypothetical numbers, and then the 3 things worth fixing first.

Size each bet to survive the losing streak. Summary card for the post: Why Risk Management Is Important in Trading (More Than Your Strategy).

What does risk management actually do for a trader?

It sets your limits before the trade, while you can still think clearly. In practice that means 4 numbers, written down. How much of the account you risk on each trade, where the stoploss goes, how much risk can be open at once, and how deep a drawdown you accept before you stop and review.

At Synapse Trading we teach trading as the 3 Ms: Method, Money and Mindset. Method is the strategy, the part everyone wants to talk about. Money is the risk management. Mindset is what lets you follow both while you are losing. Of the 3, Money is the one that keeps the other 2 alive. A method can only prove itself over many trades, and you only get many trades if no single trade, or single bad week, can knock you out.

The casino is the cleanest picture of this. Its edge on each bet is small, and it still never lets one table stake the whole building. That is the idea behind running your trading like a casino rather than a gambler.

How can 2 traders with the same strategy end up so far apart?

Imagine a strategy that wins half its trades. That is roughly a coin flip, and it is close to where our own trade log sits. Now ask a simple question. Over 100 trades, how likely is a run of losses in a row?

I worked it out exactly for a 50% win rate, and here is what comes back:

Losing streak, at leastChance of it happening within 100 trades
5 in a row81%
6 in a row55%
7 in a row32%
8 in a row17%
10 in a row4%

So a streak of 6 losses is more likely than not. It is the ordinary weather of trading, and it says nothing about whether the strategy is broken.

Now give that same streak to 2 traders. Trader A risks 2% of the account on each trade. Trader B risks 10%.

Risk per tradeAccount after 6 losses in a rowGain needed to get back
1%−5.9%+6.2%
2%−11.4%+12.9%
5%−26.5%+36.0%
10%−46.9%+88.2%

Same strategy, same streak. Trader A is down about 11% and mildly annoyed. Trader B has lost almost half the account and now needs to nearly double what is left, using a strategy that was only ever going to win half the time. Which of the 2 do you think still follows the rules on trade number 7?

Two staircases through the same 6 losses in a row: risking 2% a trade steps down a little, risking 10% a trade drops the account by almost half
Six losses in a row cost little at 2% risk a trade, and nearly half the account at 10%.

Why does a loss hurt more than the same-sized gain helps?

Because the recovery is earned on a smaller base. Lose 10% and you need 11.1% to get back. Lose 50% and you need 100%. Lose 80% and you need 400%, which, to put it politely, is no longer a trading plan.

LossGain needed to break even
10%11.1%
20%25%
30%42.9%
50%100%
80%400%

This is the asymmetry that makes small losses so valuable. Up to about 20%, the climb back is roughly the size of the fall. Past 50%, it gets steep very quickly, and it is steepest exactly when your confidence is lowest. The pain is uneven too, because a loss stings roughly twice as much as an equal gain pleases, which is the loss aversion bias at work.

If you want a daily routine with the risk rules built in, the free 15-Minute Swing Trader’s Checklist is at the end of this post.

Can a good strategy make up for poor risk management?

For a while it can. That is the danger. A trader on r/Daytrading wrote a frank post about this in July 2026. He had been profitable over 3 years of active trading, and only then spotted “the one thing I was doing badly”. In his words: “I had no method for position sizing.” He chose a position by feel, then put the stop wherever looked right, so one trade could risk 3 times as much as the next without his ever deciding that. He had also heard the “never risk more than 1%” line many times and misread it as a cap on how much money goes into one stock.

His strategy worked. That is what makes the story useful. A working strategy hid the gap for 3 years, while chance set the size of every loss.

I have my own version of this. In June 2026 my personal account was up about 7.5% for the year, concentrated in one group of related stocks. A hot jobs report on a Friday gapped the whole lot overnight, and within 2 sessions the year’s gains were nearly back to flat. My note in the journal that night read “discipline lapse, not strategy failure”. The rule to trim existed. I just did not use it. And about 10 days later I built the same concentration straight back up ahead of a Fed meeting, which, looking back, taught me more than the loss did.

What should you fix first?

Personally, I think 3 things, in this order.

  1. Risk per trade, as a fixed percentage of the account. This is the most you accept losing if the stop is hit, which is quite a different number from how much money goes into the position. The 2% money management rule for position sizing walks through it, and plenty of traders sit well below 2%.
  2. The stop first, then the size. Put the stop where the trade idea is proven wrong, and let the position size fall out of it. Say you risk 1% of the account and the stop sits 5% below your entry. The position is then 20% of the account, because 1% divided by 5% is 20%. If the stop has to be 10% away, the position halves to 10%, and the risk stays the same 1% either way.
  3. A cap on the total. A limit on how much risk is open at once, plus a drawdown level at which you stop and review, keeps 5 related trades from turning into one big bet. That was exactly my June mistake.

Notice that none of the 3 asks you to predict anything better. They only decide how much a wrong prediction costs. Our own public trade log, every trade since April 2024, dated, losses left in, shows roughly half the closed trades as losers, with the average winner about 3 times the size of the average loser. That gap only works because the losers stay small, and past results do not predict future ones.

The full map, from risk versus volatility to sample size and the trade parameters, is in the practical guide to money and risk management. If the streak table surprised you, the next 2 reads are how many trades you need before judging a strategy and how to work out your risk of ruin.

Trader A and Trader B never disagreed about a single chart. They read the same setups and took the same trades. One of them simply sized each trade so that being wrong 6 times in a row was survivable. Over a few hundred trades, that is the only kind of trader still around to find out whether the strategy worked.

FAQ

What is risk management in trading?

It is deciding, before you enter, how much a trade is allowed to cost. That covers your risk per trade, where the stop goes, how much risk is open at once, and the drawdown at which you stop and review.

How much should I risk per trade?

A small, fixed percentage of the account, the same on every trade. The textbook ceiling is 1% to 2%, and many traders start well below it while they learn.

Is risk management more important than strategy?

For survival, yes. A strategy needs many trades to show its edge, and only sensible sizing gets you through the losing streaks that come before it shows.

Does risk management reduce profits?

It makes each win smaller, in exchange for keeping you trading through the losses. A smaller position on every trade is the price of still being there for trade 200.

What is the difference between risk per trade and position size?

Risk per trade is the share of the account you lose if the stop is hit. Position size follows from it: divide that risk by the distance from your entry to your stop.

Go deeper

The free 15-Minute Swing Trader’s Checklist has the daily routine, the questions to ask before every trade, and the five rules that keep you in the game.


About the author. Spencer Li is The 15-Minute Trader and the founder of Synapse Trading. He is a Certified Financial Technician (CFTe) with 15+ years of trading, run from 70+ countries. He holds a B.Acc and B.BM from SMU. Every trade he takes is public, dated, losses left in. He teaches low-risk swing trading in 15 minutes a day, one system for any market.

Educational content only, not personalised financial advice. Trading carries risk, including loss of capital. Past performance is not indicative of future results. Synapse Trading is not licensed or regulated by MAS.

by Spencer Li
https://synapsetrading.com/wp-content/uploads/2026/10/why-risk-management-is-important-in-trading-card.webp 630 1200 Spencer Li https://synapsetrading.com/wp-content/uploads/2026/10/synapse-logo-horizontal-light.png Spencer Li2026-05-28 18:05:072026-09-27 18:47:14Why Risk Management Is Important in Trading (More Than Your Strategy)
Spencer Li

Order Types in Trading: Market, Limit, Stop and Stop-Limit Explained

Risk & Money Management
Order types explained - trading basics

What each one guarantees, what it gives up, and which to use when a stock gaps through your stop

Published: 16 October 2026 · Last updated: 13 August 2026 · By Spencer Li, CFTe


Most beginners pick an order type the way they pick a seat on the bus, which is whichever one is free. That works until the day the price runs straight through a stop-loss and the order does something they did not expect.

There are four core order types. A market order buys or sells right away at the best price available, so it promises a fill and does not promise the price. A limit order only trades at your price or better, so it promises the price and does not promise a fill. A stop order waits until the price reaches a trigger, then turns into a market order, which is how most stop-losses work. A stop-limit order waits for the same trigger, then turns into a limit order, so you control the price and risk not getting out at all. Every order type is a choice between those two certainties, the fill or the price, and you can rarely have both.

Below, each one is worked through, along with the one situation where the choice really matters: a gap.

Every order picks the fill or the price. Summary card for the post: Order Types in Trading: Market, Limit, Stop and Stop-Limit Explained.

What does each order type guarantee?

Here they are side by side.

OrderWhen it fillsWhat it guaranteesWhat it gives upCommon use
MarketRight awayA fillThe priceGetting in or out now
LimitOnly at your price or betterThe priceThe fillEntries at a planned price, profit targets
StopOnce the trigger is reached, as a market orderA fill after the triggerThe priceStop-losses, breakout entries
Stop-limitOnce the trigger is reached, as a limit orderThe priceThe fillEntries where a bad price is worse than no trade

I call this Fill or Price, because that is the only real question each order answers. Once you see it, the four types stop being four things to memorise and become one decision.

Two boxes: market and stop orders guarantee the fill, limit and stop-limit orders guarantee the price, with a red or between them
Market and stop orders promise the fill; limit and stop-limit orders promise the price.

When should you use a market order?

When getting the trade done matters more than the last few cents. The US Securities and Exchange Commission puts it simply: a market order “guarantees that the order will be executed, but does not guarantee the execution price.”

The trap is the price you see on the screen. As the SEC notes, “the last-traded price is not necessarily the price at which a market order will be executed.” You buy at the seller’s asking price and sell at the buyer’s bid price, and the gap between the two is the spread. On a busy large-cap stock that gap is tiny. On a thinly traded small stock, or in the first minutes after the open, it can be wide, and a market order will cross it without asking you.

When should you use a limit order?

When the price matters more than whether you trade at all. In the SEC’s words, “a buy limit order can only be executed at the limit price or lower, and a sell limit order can only be executed at the limit price or higher.”

So the cost of a limit order is the trade you miss. Say you want to buy a stock at 40 and set your limit there. It drops to 40.05, turns and runs to 50 without you. You saved five cents a share and missed the whole move. That is a fine outcome when the plan only works at 40, and an annoying one when it would have worked at 41 too.

Limit orders are also the natural way to take profit at a planned target, because a target is a price you have already decided you are happy with.

How does a stop order work?

A stop order sits quietly until the price reaches your trigger, called the stop price. Then it wakes up. According to the SEC, “When the stop price is reached, a stop order becomes a market order.”

A sell stop sits below the current price and is how most people place a stop-loss on a long position. A buy stop sits above the current price. Short sellers use it as their stop-loss, and breakout traders use it to enter only if the price pushes through a level.

Because it becomes a market order, it inherits the market order’s weakness. The SEC’s bulletin on stop orders warns that one “may be triggered by a short-term, intraday price move that results in an execution price for the stop order that is substantially worse than the stock’s closing price for the day.” That is the experience behind a Reddit thread titled “Stopped out at the exact high/low repeatedly.” Brokers also differ on what counts as reaching the trigger, since “some brokerage firms use only last-sale prices to trigger a stop order, while others use quotation prices.”

A stop that follows the price up as a trade moves your way is a trailing stop, which has its own post: Trailing Stops: How They Work and When to Use Them.

Our free 15-Minute Swing Trader’s Checklist puts the stop, the target and the size on paper before any order goes in. Get the free checklist →

Stop-limit vs stop-loss: which one protects you in a gap?

A stop-limit order has two prices, the trigger and the limit. The SEC’s example is a sell stop-limit with a stop price of $3.00 and a limit of $2.50. It “would become an active limit order if market prices reach $3.00, however the order can only be executed at a price of $2.50 or better.”

Now picture the morning it matters. Here is a hypothetical, in round numbers. You own a stock at 50 and want out if it falls to 47. The company reports bad news overnight, and the stock opens at 42.

  • With a stop order at 47, the trigger fires at the open and you are sold at around 42. You lost more than you planned, and you are out.
  • With a stop-limit at 47, limit 46, the trigger fires, but nobody will pay 46. The order sits there unfilled. You are still holding a stock at 42, and if it slides to 38 by the close, the loss keeps growing while your “protection” waits for a price that has gone.

Neither outcome is pleasant. But only one of them has an end.

That is why a simple default helps: on the way in, insist on the price, and on the way out, insist on the fill. A missed entry costs you an opportunity. A missed exit can cost you the account. So stop-limit orders tend to suit entries, where a bad price is worse than no trade, and plain stop orders tend to suit protective exits. The exception is a very thin market, where a plain stop can fill at a silly price, and that is a reason to trade smaller there rather than to remove the stop.

How much you lose when a stop fills badly also depends on how big the position was to begin with, which is what the 2% money management rule is there to control.

How long does an order stay open?

Each order also carries a time instruction. Most are day orders. The SEC explains that day orders, “if not executed, generally cancel at the end of regular trading hours of the trading day that they are entered.” A good-til-canceled order “lasts until it is executed in full or it is canceled,” although the longest a broker will hold one varies by firm.

This matters more than people think if you trade US stocks from Singapore. The US market opens at 9.30 pm Singapore time in the American summer, and 10.30 pm in their winter. A stop-loss placed as a day order in the afternoon will protect you for one session and then quietly disappear. A good-til-canceled stop keeps protecting you while you sleep.

There are a few rarer instructions too. An immediate-or-cancel order fills what it can at once and cancels the rest. A fill-or-kill order must fill in full at once or not at all. And a bracket order (sometimes called one-cancels-the-other) pairs a stop-loss with a profit target, so that when one fills the other is cancelled. Our video on how to place orders and enter trades shows what these look like on an order ticket.

So, look at the open orders in your account right now. Which of them would still be there after the next close, and which of them would actually get you out if the stock opened 10% lower tomorrow?

FAQ

What are the four main order types in trading?

Market, limit, stop and stop-limit. A market order fills now at the best available price, and a limit order fills only at your price or better. A stop order becomes a market order at a trigger price, and a stop-limit order becomes a limit order at that trigger.

What is the difference between a stop-loss and a stop-limit order?

A stop-loss order becomes a market order when the trigger is hit, so it gets you out at whatever price is available. A stop-limit order becomes a limit order, so it only fills at your limit or better and may not fill at all if the price gaps past it.

Is a stop-limit order safer than a stop order?

For a protective exit, usually not. A stop-limit controls the price but can leave you holding a falling position after a gap, while a plain stop gets you out at a worse price.

Why did my market order fill at a different price than the screen showed?

Because the screen shows the last trade, and a market order fills against the best available bid or ask at that moment. In a fast or thin market the two can differ a lot.

What is a good-til-canceled order?

It is an order that stays open until it fills in full or you cancel it, rather than expiring at the day’s close. Brokers set their own limit on how long one can stay open, so check yours.

Go deeper

This post sits under our guide to money and risk management. If you would like the routine that decides your stop, target and size before any order goes in, the free 15-Minute Swing Trader’s Checklist is the place to start.


About the author. Spencer Li is The 15-Minute Trader and the founder of Synapse Trading. He is a Certified Financial Technician (CFTe) with 15+ years of trading, run from 70+ countries. He holds a B.Acc and B.BM from SMU. Every trade he takes is public, dated, losses left in. He teaches low-risk swing trading in 15 minutes a day, one system for any market.

Educational content only, not personalised financial advice. Trading carries risk, including loss of capital. Past performance is not indicative of future results. Synapse Trading is not licensed or regulated by MAS.

by Spencer Li
https://synapsetrading.com/wp-content/uploads/2026/10/order-types-trading-card.webp 630 1200 Spencer Li https://synapsetrading.com/wp-content/uploads/2026/10/synapse-logo-horizontal-light.png Spencer Li2026-05-27 18:21:432026-08-13 12:51:01Order Types in Trading: Market, Limit, Stop and Stop-Limit Explained
Spencer Li

Trading Expectancy Formula: How to Tell if a Strategy Is Worth Trading

Risk & Money Management
The expectancy formula - risk management

Last updated: 11 September 2026 · By Spencer Li, CFTe


Expectancy is the average amount a strategy makes or loses per trade. The formula is: expectancy = (win rate × average win) − (loss rate × average loss). Measure the wins and losses in R, where R is the amount you risk on each trade, and the answer tells you how many R the strategy earns or gives back on an average trade.

A hypothetical example: a strategy wins 40% of the time, its average win is 2.5R and its average loss is 1R. Its expectancy is 0.4 × 2.5 − 0.6 × 1, which comes to +0.4R per trade. Positive expectancy means the strategy has an edge. Zero or negative means it does not, however good the win rate looks.

Wins as a block as wide as how often you win and as tall as the average win, losses as a block below the line; the red top of the wins block, left over after matching the losses, is the edge
Weigh each win and loss by how often it happens; what the wins have left over is the edge.

Expectancy is the number that decides if a strategy is worth trading at all. It is also the number most traders never calculate, because it needs a written record of every trade.

Win rate feels good, but expectancy matters. Summary card for the post: Trading Expectancy Formula: How to Tell if a Strategy Is Worth Trading.

What does expectancy tell you that win rate cannot?

Win rate tells you how often you are right. Expectancy tells you if being right pays. The 2 can point in opposite directions.

In September 2026 a trader on r/Daytrading posted a short warning to newer traders: “you can lose money winning 90% of them”. He finished with the line that sums up this whole post: “Win rate feels good, but expectancy is what actually matters.”

Here is the hypothetical arithmetic behind his point. A strategy wins 90% of its trades, but each win makes only 0.1R, while each loss costs 1R. Its expectancy is 0.9 × 0.1 − 0.1 × 1, which is −0.01R per trade. It wins 9 trades in 10 and still loses money slowly.

This is why I call it the 3-number test. Before you trust any strategy, yours or anyone else’s, ask for 3 numbers: the win rate, the average win and the average loss. Those 3 give you expectancy. A win rate on its own gives you nothing you can use. How the first 2 trade off against each other is the subject of win rate versus reward-to-risk.

Why measure expectancy in R instead of money?

Because R makes every trade comparable. A loss of 1R is a loss of exactly what you planned to risk, whether your account is small or large and whatever the price of the stock. A win of 3R is 3 times what you risked.

To turn any closed trade into an R-multiple, divide the result by the amount you risked when you entered. Risk 1% of the account and make 2.5%, and that trade is +2.5R. Risk 1% and get stopped out for 1%, and it is −1R. Let a loser run past the stop to 1.5%, and it is −1.5R, which your journal should show honestly.

The casino idea from trading versus gambling is the same thing in different clothes. A casino’s house edge is its expectancy per bet. It is small, it is positive, and the casino lets the number of bets do the rest.

How do you calculate expectancy from your own trades?

Take your last batch of closed trades, write each one as an R-multiple, and average them. The average R-multiple is your expectancy. Here are 10 hypothetical trades:

TradeResult
1+2R
2−1R
3−1R
4+3R
5−1R
6+0.5R
7−1R
8+2R
9−1R
10−0.5R

The 10 results add up to +2R, so the average is +0.2R per trade. The formula gives the same answer. The win rate is 40%, the average win is 1.875R and the average loss is about 0.92R, and 0.4 × 1.875 − 0.6 × 0.92 comes to +0.2R.

Then take off your costs. Commissions, spreads and slippage can be written in R too. If they come to 0.05R a trade, a strategy at +0.2R is really earning +0.15R, and a thin edge can disappear entirely.

If you do not have the 10 rows yet, start there. Keeping a trading journal shows a simple way to record them.

If you want a daily routine that keeps every trade on the record, the free 15-Minute Swing Trader’s Checklist is at the end of this post.

How many trades does it take to trust the number?

More than most people expect. Ten trades tell you very little, even about a strategy with a real edge.

Take the +0.4R strategy from the top of this post and run it many times in a simulation. Here is how often the trader would see a flat or losing average, purely from the luck of the draw:

Trades recordedChance the average is zero or belowTypical range of the average (95%)
1017.1%−0.66R to +1.46R
309.8%−0.21R to +1.01R
1000.8%+0.06R to +0.74R
200under 0.1%+0.16R to +0.64R

Hypothetical, each trade independent, 20,000 simulated runs per row.

Read the second row again. After 30 trades, a genuinely good strategy still looks flat or negative about 1 time in 10. That is why we ask for 100 to 200 trades before judging a system, and why the law of large numbers gets a post of its own.

Can a positive expectancy stop working?

Yes, and this is the fair objection to everything above. Expectancy is measured on trades that already happened. A trader on r/algotrading posted in January 2026 about tracking “Strategy Decay”, the way an edge can fade as markets change.

He is right to worry about it, because a number measured on last year’s trades describes last year’s market, and the conditions that produced the edge can shift without any warning at all. Personally, I re-check expectancy on a rolling batch of recent trades as well as the full history. If the recent number drifts well below the long-run one, that is a reason to look harder at the method before the account forces the question.

2 more things expectancy does not tell you. It says nothing about how deep the losing streaks get along the way, which is what risk of ruin is for. And it is per trade, so frequency matters. A strategy at +0.2R that trades 100 times a year earns 20R, while one at +0.5R that trades 20 times earns 10R.

The full map of these ideas sits in the practical guide to money and risk management.

No casino has ever needed to know how the next spin will land. It only needs to know its number, and to keep the bets small enough that the number gets time to show up.

FAQ

What is the formula for expectancy in trading?

Expectancy = (win rate × average win) − (loss rate × average loss). With wins and losses in R, the answer is the average R made or lost per trade.

What is a good expectancy for a trading strategy?

Any figure that stays positive after costs over a large sample. How big it needs to be depends on how often the strategy trades.

Can a strategy with a high win rate have negative expectancy?

Yes. A strategy that wins 90% of the time at 0.1R and loses 1R on the rest has an expectancy of −0.01R per trade.

How many trades do I need to calculate expectancy?

At least 100 before trusting it, and ideally 200. Below 30 trades, luck can hide a good strategy or flatter a bad one.

Is expectancy the same as expected return?

They come from the same maths, the probability-weighted average outcome. Expected return is the investing term for an asset’s average return, while trading expectancy is measured per trade, in R.

Go deeper

The free 15-Minute Swing Trader’s Checklist has the daily routine, the questions to ask before every trade, and the five rules that keep you in the game.


About the author. Spencer Li is The 15-Minute Trader and the founder of Synapse Trading. He is a Certified Financial Technician (CFTe) with 15+ years of trading, run from 70+ countries. He holds a B.Acc and B.BM from SMU. Every trade he takes is public, dated, losses left in. He teaches low-risk swing trading in 15 minutes a day, one system for any market.

Educational content only, not personalised financial advice. Trading carries risk, including loss of capital. Past performance is not indicative of future results. Synapse Trading is not licensed or regulated by MAS.

by Spencer Li
https://synapsetrading.com/wp-content/uploads/2026/10/trading-expectancy-formula-card.webp 630 1200 Spencer Li https://synapsetrading.com/wp-content/uploads/2026/10/synapse-logo-horizontal-light.png Spencer Li2026-05-06 14:06:092026-09-11 14:55:13Trading Expectancy Formula: How to Tell if a Strategy Is Worth Trading
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