## How to Trade with the Odds on Your Side

### The dos and don’ts when applying probability to your trading decisions

How often do you hear other traders touting on social media “This trade is high probability”, but never giving an exact figure of what that probability is? What they’re usually saying is “This trade really feels like it will work”.

But there’s a difference between a trade that’s high probability and one that just feels like it is. Our feelings about a trade are strongly influenced by recency bias – what our last few trades looked like. It’s easy to overestimate the probability when we’re on a winning streak, or underestimate it when we’re deep in drawdown.

Probability is a term that gets thrown around but is rarely recognised for how important it is to our edge as a trader. You hear a lot about win rates – the overall probability of a strategy – as this is easily measured. But few discretionary traders take the time to measure the probability of specific setups or price patterns, and apply this data to their trading.

There’s a good reason why. As a discretionary trader, it’s very difficult to say what the probability of the next trade you take is. There is so much nuance to each setup it would be impossible to know the odds historically of the exact setup you’re taking over a large enough sample size.

But having an idea of the probability of common price patterns can significantly enhance your edge as a discretionary trader. Certain price patterns just work better in certain markets. The only way of knowing this (besides trading the same markets for several years) is through collecting data on their probability.

Having access to these probabilities can put you ahead of the competition, but only if used correctly. Applying statistics to a discretionary trading strategy is an art. Do it right, and you can enhance a profitable trading strategy. But do it wrong, and you can quickly turn a profitable strategy into a losing one.

When I first armed myself with probabilities of dozens of different price patterns across 42 different markets, I thought I would be more profitable than ever. But instead, I quickly learned that knowing probability in itself was not enough to make money. I had to learn how to apply it correctly…

### Black-and-white thinking

If I told you that daily bullish engulfing candles in crude oil have a 73% probability of a close higher the next day, what would you do with that information?

Knowing the odds are in your favour, you could buy the close of the next bullish engulfing, hold until the next day’s close, and see how much profit you end up with. Putting aside the issue of where to place your stop (these probabilities tell you nothing about how far price could travel against you before closing higher), you can see how knowing a statistic like this immediately has you thinking in black and white. 73% probability? If the reward to risk is sufficient shouldn’t you just take it?

But our role as discretionary traders isn’t to systematically trade setups, even if the odds are historically in our favour. Instead, we need to figure out if this situation right in front of us is one of the 83% of occasions where price will close higher, or the 27% of occasions where price will close lower.

The 83% figure tends to immediately cloud our judgement and make us think “This is an unmissable opportunity!”. But when we start to break this figure down it becomes less clear.

Of those 83% of occasions, some will travel far enough against us to stop us out before closing higher, and some will only close marginally higher and not allow us to bank much of a profit.

So it doesn’t translate into a 73% probability of our trade working. For our trade to work, price not only has to close higher, but it has to reach our target before taking our stop. And the probability of that occurring is unknown.

When I started using statistics like this in my trading, I would often get led astray with this way of thinking. I’d take a shitty setup because I’d see a jaw-dropping statistic. Or I’d step aside an excellent setup because the odds didn’t appear to be in my favour. I’d end up thinking in black or white. High probability or low probability? I’d see a price pattern, go to my spreadsheet, and use that % figure as my key deciding factor.

Using probabilities in this way not only led me to lose money, but it derailed my entire trading process. And it was this process that my edge as a discretionary trader relied on.

### Systematic or discretionary?

To better understand what I’m talking about, let’s consider the difference between systematic and discretionary trading strategies.

Systematic traders find a statistical edge with a positive expectancy through back and forward testing and then trade it blindly. Their method of entry, stop loss, and target must be the same for each trade. This process is 100% systematic, so it can be written into an algorithm that executes trades automatically.

Their edge comes from knowing that this precise, systematic way of trading a setup has sufficient probability to make a profit over time. In other words, they have a positive trader’s equation:

*The trader’s equation = reward x probability of winning > risk x probability of losing*

Discretionary traders must also have a positive trader’s equation to be profitable over time. But the way they achieve this is very different.

I like to think of it as the human brain versus a computer. The computer uses its vast computing power to find a statistical edge and then trades this edge systematically, at lightning speed. The human brain doesn’t have the same computing power, accuracy, or speed. Instead, it relies on careful judgment and intuition. Its process of trade selection and execution is very different.

The human brain looks at the candlesticks on the chart and sees a story. Accessing memories of past market observations, it uses pattern recognition to carefully analyse the narrative of price action. Where has price been? Where is the logical place for price to travel to next? It looks for confluence factors – telltale price patterns or signs from indicators – that suggest price is more likely to head in a certain direction. It zooms out and looks at the broader market: correlations, upcoming news events, the current economic climate, and anything that is driving market forces. Finally, it combines all this information and decides if there is a trade opportunity there. If there is, it decides on a suitable entry, stop loss, and target, and assesses if the payoff is worth the risk.

If it starts to think in black and white – high probability or low probability – you can see how this entire process could get derailed. What results is a systematic strategy that is poorly thought out and hasn’t been rigorously backtested.

This isn’t to say you can’t use probabilities to trade systematically. But you need to follow an entirely different process. A process that involves far more extensive data collection and backtesting, with a systematic way of placing entries, stops, and targets.

So how do we use probability as discretionary traders without interfering with our brain’s process of careful trade selection?

## Use probability as a confluence factor

Whenever we add another tool to our discretionary trading strategy, we have to be careful it doesn’t interfere with our trading process. The best way of doing this is to consider the new tool as a confluence factor.

A confluence factor is like evidence in a case. Each piece of evidence may help gain a conviction, but on its own, it isn’t going to win the case.

First, we form a clear idea of where price may be headed next. Then we look for signs that suggest our idea is more likely to be true – our confluence factors. You probably already use confluence factors as part of your process. You might use moving averages, RSI, ATR, Bollinger bands, MACD, the list is endless. But would you decide to take a trade based only on these indicators? Of course not. Probability should be viewed in the same way.

Let’s go back to our daily bullish engulfing candle in crude oil example. Before we’re even aware of the 83% figure we should have already assessed the setup from every angle and decided if there is a trade there or not. If the candle is in a poor location, or the price action suggests it’s more likely to be a trap, then we should pass on it without even checking the probability.

Let’s say the price action into the pattern is compelling, and the candle occurs off of significant daily structure. We like the way it looks, and there’s a compelling target above market. Now we can check our probabilities. Seeing there’s an 83% probability of a positive close the next day, we now have more conviction that this trade has the odds on its side.

But what if the odds weren’t in our favour? Let’s say the probability of a close higher is only 28%. If we believe the setup in front of us is high quality, and the payoff is high relative to risk, then we should still take the trade. Remember that this figure doesn’t tell us the probability of our exact trade. Price could hit your target and then close lower, in which case this 28% figure would be irrelevant. Or it could be one of the 28% of times when it does close higher.

If you’re on the fence, and the setup isn’t particularly strong, a figure like this can be helpful in your decision to trade or not to trade. Just as indicators add strength to the overall quality of a setup, probabilities can help you decide if a setup is worth taking. But remembering the limitations of probability, and using it only as a confluence factor, is crucial to success.

Doing what you can to improve your awareness of probability can really take your trading to the next level. You can do this by feel – trading the same patterns in the same market for years and over time getting a feel for what works and what doesn’t. Or you can speed this process up by using high-quality data on probability. You can collect this data yourself, or you can use OddsRadar.

OddsRadar is a subscription service that offers forex traders high-quality, probabilistic data through daily alerts of different price patterns. The data is collected using algorithms in InvestorRT, covering dozens of different price patterns across 42 markets, and goes into a lot more detail than the example in this article.

Sign up for a free 7-day trial today, and see how using probability as a confluence factor can enhance your edge in the market.