Estimated reading time: 6 minutes
Trading expectancy is a smart maths formula that instantly highlights the profit or loss an investor makes on each trade.
If the result is negative, you are a loser, but a positive means your strategy for picking that stock or crypto was a winner.
The trading expectancy calculation also shows how many trades are won and each strategy’s average loss or gain.
The key takeaways are:
- Serious investors keep records so they can analyse and adjust strategy
- Traders can lose regularly, but if their wins are much bigger than the losses, investing can give them a good income
- Traders can win nearly every trade but still pile up enormous losses if their gains are too low to outweigh what they lose
Table of contents
What Is The Magic Trade Expectancy Formula?
The trading expectancy formula is ideal for analysing stocks and shares trades and stretches to cover cryptocurrency and forex.
New traders rarely think about losing. Instead, they like the taste of victory and hope to win eight or more trades from every ten they make. Although winning is great, piling up wins does not make someone a profitable trader – the size of the victories counts just as much.
So let’s see how to calculate trading expectancy by working through the formula step-by-step and then looking at some examples.
The trading expectancy formula is:
(Win % x Average win size) – (Loss % x Average loss size)
What Trade Expectancy Tells Investors
Take a trader who wins around three out of ten trades, making $1,000 a time. If our trader loses, the average loss is $150.
The trading expectancy calculation is:
- (0.3 x $1,000) – (0.7 x $150) = $300 – $105 = $ 195
- 0.3 is the win percentage of 30 per cent.
- $1,000 is the average win
- 0.7 is the loss percentage – 100 per cent less the win percentage. The average win and loss percentage must add up to 100
- $150 is the average loss
The good news is the trader is making money because the trading expectancy is positive.
Over 10 trades, the profit is $1,950 (10 x $195), while the loss is $1,050 (10 x $150).
The workings show each trader’s average gain and loss and their win/loss rate.
Winners end up losers
For many new traders, the result is more complicated. Typically, new traders make smaller gains and larger losses.
This reflects in a negative score that reveals the true scale of losses even when the stats show a trader seems to be a winner.
This time, the trader wins 70 per cent of the time, making an average of $125, but the losses average $500.
The trade expectancy calculation is:
(0.7 x $125) – (0.3 x $500) = 87.5 – 150 = -62.5
This time, the negative result shows the trader is losing money and the higher the number, the bigger the loss.
The formula confirms the trader gains $875, winning seven out of ten trades, but the loss from the remaining three trades is $1,500, leaving the trader $625 in the red. The takeaway is that a trader can have a great win tally, but the losses can still mount if the profits are low.
Trade expectancy and scalping
Scalpers can fall foul of trade expectancy rules if they take lots of small gains from a large number of wins. The formula shows our trader loses $62.5 on average for every trade.
A negative expectancy score means the more trades an investor makes, the more money they will lose even though they seem to be winning. So, the target becomes making wins more profitable and losses less damaging.
One strategy the trader could introduce is a stop/loss order. An order reduces the risk of a large loss.
Picking The Best Trades
You are a trader who must pick the best strategy from two options:
- Trade with a 95 per cent chance of winning $10 but a 5 per cent chance of losing $1,000
- Trade with a 5 per cent chance of winning $1,000, but a 95 per cent chance of losing $10
Many new traders go for the first option to win lots of small amounts over time. The downside is one loss wipes out 100 wins, and the trade has a negative expectancy score.
The second option is best because the ratio has a positive score.
Here’s how it works over 100 trades:
- Option A works out as (0.95 x 10) – (0.05 x 1000) = 9.5 – 50 = -40.5
- Option B works out like this: (0.05 x 1000) – (0.95 x 10) = 50 – 9.5 = 40.5
Beware The Gambler’s Fallacy
The gambler’s – or Monte Carlo – fallacy is when a trader mistakenly believes a transaction will make a profit based on the outcome of a previous transaction or series of transactions.
The fallacy is that success will repeat under the same circumstances. Still, the reality is the result of past transactions don’t change the probability of what may occur in the future.
A good example is a lottery. Because a set of lucky numbers won the lottery last time does not mean they will win again.
To counter the fallacy, investors should try two courses of action:
- Treat every trade as an independent transaction
- Ensure the sample of trades used for calculating the trade expectancy ratio is from at least 100 transactions to give a robust score
Smaller samples may not be accurate, which is where the gambler’s fallacy comes into play.
How Trading Expectancy Helps Investors FAQ
As the expectancy ratio gives the average amount a trader should win or lose on every trade, it’s the only way a trader will ever know if their strategy turns a profit.vAny negative score shows a trader is losing money, so a good score must be positive.
Traders like at least a 0.2 score, although some prefer 0.5 or more.
A 0.2 score generates $2,000 profit from 100 trades, while a 0.5 score gains $5,000 from 100 trades.
If events are random and independent, it follows that the outcome of the events does not influence or otherwise predict what will happen to the next transaction. The fallacy is thinking the events are linked, and their result will affect what happens with the next transaction.
Trade expectancy strips away the smoke and mirrors of investing to show if investments are profitable or not over time. The expectancy ratio is helpful for investors trading stocks and shares, commodities, cryptocurrency and forex.
A trader will not win every trade but will try to ensure their wins are larger than their losses. This is called a ‘positive skew’. Regular traders realise they need to be right two or three times out of ten if they win large amounts each time.
New traders prefer to be right all the time, but they must understand the odds are against them.
Yes, the risk/reward ratio is the same as the trade expectancy ratio.
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