Image 1 — AI Generated Image of Trading Price Action and Systems
A guide for beginning traders on how to turn market fundamentals into your first profitable trading system. Part 2 of a 3-part series on becoming a profitable trader.
In the first article of this series, I covered the three core fundamentals of the market that I stick to; Price, Volume and OrderFlow. They are the raw dynamics of how the markets move. I am thoroughly convinced that with knowledge of these concepts, any trader can come to a profitable trading system. Perhaps since reading the last article, you’ve already thought of some trading ideas, or even seen people share trading systems online that tackle similar fundamental concepts.
In this article, I discuss the steps I recommend any beginning trader takes towards building their first system. I do this based on my own system building experience, primarily based on all the mistakes I’ve made. These mistakes cost me a lot of unnecessary time. I hope by sharing these mistakes and this process, that you won’t have to go through them as I did.
To do so, I want to get a couple of beginner warnings out of the way. These are things that I see with a lot of beginning traders and that will slow you down a lot. Therefore, read them carefully!
There is no “Holy Grail” of systems
A beginning trader is often very susceptible to the feeling of the Grass is Greener on the other side.
It is most likely not.
You might see a trader online making a lot of money with their system. The reality is, that is most likely due to the trader, not due to the system. Profitability depends on the trader’s psychology, discipline, and understanding of their system and how price action relates to their system. That is true edge, not the system itself. 1000s of other traders likely have similar rules to those that you will have, but only a small part are able to operate them well and be profitable with it.
Continuously looking for better systems leads to “system hopping”. It’s probably what has lost me the most amount of time. Continuously chasing that rush of more profitability, but never actually getting good at a system, which results in the actual profitability.
Keep this Bruce Lee quote in mind: “I fear not the man who has practiced 10,000 kicks once, but I fear the man who has practiced one kick 10,000 times”. It holds especially true with trading. Get good at your own style, not someone else’s, the profitability will follow.
This also means that there’s no point endlessly optimising a system before taking it live. That’s backtesting paralysis, and it is rooted in wanting the perfect system that has no losses. There is no perfect system, losses are part of the game. As soon as you have something that shows profitability, take it to live testing to find out if it behaves similarly to what you tested.
There is no Holy Grail, get it out of your head.
Lower time frame is not always better
Lots of beginning traders are naturally drawn to scalping, which is trading very low time frame with very short trade times. You’re in and out. That draw is with good reason. Scalping is flashy. It promises excitement. It promises major profits. And if there’s one thing we humans don’t want is to spend a lifetime perfecting a skill to acquire the lifestyle that comes with it. We want to be rich now. Naturally, if scalping equals lots of trades, that’s what we’re drawn to.
I was in that same boat. In the beginning 2 years of my trading journey, I was focused on scalping only. The harsh truth, I never actually made any money with it. That being said, can scalping be profitable? Of course it can, but it requires a very specific psychological mindset, one that not many people have. I know I definitely don’t.
That is why I recommend any beginning trader to start on the higher timeframes, think the 4H, 8H, Daily or Weekly charts. Learn what it takes to operate those systems with discipline. Once you’ve got that down, and have proven consistency and profitability there, you can make the jump to a lower timeframe if that is still your preference.
You might be stubborn in believing me, I was too, and maybe you have to go through that process of realisation like I did. But in the end, scalping is not a quicker way to profits. And drawn out over a long time frame, profits are more easily made in the higher time frames.
Towards your first system
When we refer to a system or strategy in trading, it refers to having a set of specific rules which you use for entering and exiting a trade. You think of this set of rules, test these over a large enough sample, and check whether that system is profitable over that time period.
Each trader can have as many systems as they want, for specific markets, timeframes or even market environments. Personally, I have 4 trading systems that cover for me most of the market environments I aim to trade.
The more objective these rules are, the better they work for your trading psychology. This mostly comes into play when your system is going through a losing period, which it definitely will. When you’re constantly losing, the last thing you want is to doubt yourself. Doubting your own ability to trade is going to lead to worse trading, which by itself repeats the process. You’ll end up in a vicious cycle. When a system is completely objective, you always have the proven profitability of your backtesting to fall back on, and can take any losing period as motivation to figure out improvements for your system. You turn a losing period into a positive thing.
Here’s an example of what a completely objective system looks like, built on the three fundamentals from Part 1:
An example of an objective system
Asset: BTC or ES Futures
Timeframe: DailyEntry condition:
Price breaks above yesterday’s high and the candle closes above it.Three confirmations (all must be true):
Price: Today’s candle closes above yesterday’s high (not just a wick).
Volume: Today’s volume is higher than yesterday’s volume.
OrderFlow: More contracts traded on the Ask than the Bid.Entry: At the daily close.Stop Loss: Below today’s low.Take Profit: Fixed 2R.
These system rules are not interpretable. Every time the conditions are met, the entry and exit are the same. That’s what makes it objective. I haven’t backtested this system, and it’s not one I trade. It’s here purely to show you what a complete, objective system looks like using the three fundamentals from Part 1. If you want to use it as a starting point, make sure to test it thoroughly yourself before putting any money on the line.
TradingView is your best starting point for testing systems. It’s free and allows free backtesting. It lets you look back at historical price data, and crucially, it has a replay function that lets you simulate setting trades in real time as price unfolds, which makes your backtesting results far more reliable than simply looking back at charts in hindsight, as then there’s quickly bias involved.
Measurements to look for when testing a system
There are several ways to measure whether a system is profitable over time. The one I rely on most is Expected Value (EV), which is based on something called Sum of R. To get there, we first need to understand R:R.
R:R stands for Risk:Reward. It’s the ratio traders use to measure the profitability of a trade relative to the amount of risk you put on that particular trade.
Here’s how it works. Every trade you set has a risk, the amount you stand to lose if price hits your stop loss. That amount becomes your 1R. Your reward is then shown as a multiple of that risk.
For example: say you enter an asset at $100 with a stop loss at $90. Your risk is $10, that’s your 1R.
If your take profit is at $120, you’re targeting 2R, because the reward ($20) is twice your risk ($10).If your take profit is at $130, that’s a 3R trade.
In dollar terms, let’s assume you put $50 on that trade.
If the price of that asset reached $90, you’d have lost $50.If price has gone to your take profit for a 2R trade, you’d have made $100 profit (2x the risked $50).Had price gone to your 3R take profit, your returns would have been $150.
The actual dollar amount changes depending on your position size, but the R value stays consistent. That’s what makes it a useful measuring tool, it lets you compare trades fairly regardless of size.
A losing trade is expressed as -1R.
When you test a system across 200 trades, you end up with a list of results in R. Add them all together and you get the Sum of R, the total reward generated relative to your risk across the trades you took. For example, if across 5 trades your results are +2R, -1R, +3R, -1R, +1.5R, your Sum of R is +4.5R. If that number is positive, it means that, if you had taken every one of those trades, you would hypothetically have been profitable. I say hypothetically, because standard backtesting does not account for fees, slippage (where your orders fill at a slightly different price than intended), or mistakes. More on that later.
Divide that Sum of R by the number of trades and you get the Expected Value (EV). This is the metric I use most to compare systems. It tells you what the average trade earns you in R. A positive EV means that as long as you keep setting trades, the system will be profitable across a large enough sample. An EV of +0.2 means that, across every trade you make on average 0.2 times your risk per trade. An EV of +0.5 means that across every trade, you make on average 0.5 times your risk. This is always across a large amount of trades. The larger of a sample you test on, how your system performs across months or years instead of days or weeks, the more of a guarantee your have that across time, your system has positive results. If you take that system live, across a trading week that EV might be higher of lower than what you tested, but over a large data set it evens out.
That’s what trading is all about.
A final one I believe is relevant to an extent, win rate. Beginning traders often search for a system that wins a lot, because they believe this always makes them profitable. While there’s a sense of truth to that, it doesn’t always hold up. For example, look at the following scenario:
Trader #1 sets 2 trades, wins both of them for 1R each. So he’s up +2R.Trader #2 sets 2 trades, wins one and loses the other. The winner is 3R. The loser is -1R. In total he’s up +2R as well.
One trader has a worse win rate, but in terms of profitability they are the same.
There are systems out there that barely win, but the trades that win have a huge R. Other systems win quite a lot but with very low R. Both can be profitable.
This is where the personal preference comes in that I discussed. Some traders are very good at dealing with lots of losses, and other traders might not. You can choose to test for a high win rate system, if you believe that works better for you to mentally keep going. I did that myself and I’ve never looked back, but I get the appeal of low win rate systems with huge wins.
What kind of EV should I aim for?
When it comes to EV, any system you’ve tested that is profitable in backtesting is worth considering for live testing. Live testing is much different than backtesting, it’s where your psychology starts affecting your systems’ performance. So instead of endlessly testing a positive system and optimising it, test it once, and when profitable try to optimise it through live testing, which will reveal the actual EV.
When you go live, I recommend setting a fixed dollar amount as your risk per trade. Say you always risk $5. In live trading, your actual losses and wins won’t always land exactly where you planned, your stop loss might fill slightly worse than expected, or fees might eat into your profit. If you risked $5 but actually lost $5.50, that trade wasn’t -1R, it was -1.1R. If you targeted 3R but only made $14 instead of $15, that’s 2.8R, not 3R. Track the actual numbers. That’s your real system performance, and I’ll explain exactly why these differences happen in the next article.
Generally, low time frame systems have lower EV than high time frame systems, but that is because they tend to trigger much more often, and has more false signals. A candle close on the daily is a much stronger signal than a candle close on the 1minute chart. A system that triggers 10x per day and has a NET EV (meaning including fees, mistakes and slippage, a.k.a. live tested) of 0.1, basically means that each trading day on average you’d earn 1R (10 * 0.1 = 1R). That would be a lot.
The simple breakout system I shared, if it were to be backtested and resulted in an EV of say +1.5, that would mean on average every trade has an EV of 1.5R. That might seem amazing, but on a daily chart you might only get 30 trades a year that meet all your objective conditions. Imagine going a few months with only 10 trades.
That is what I mean with, a trading system has to suit you. With such a system, you have to be okay with barely trading and sitting on your hands a lot.
Similarly, with a system of 10 trades per day, you have to be okay with periods where you lose a lot and constantly.
Another thing to watch out for is the EV people share of their systems, or in general people sharing the big trading winners they have. This is where the Grass is Greener feeling comes in. Let me start by saying, that feeling is ALWAYS wrong.
I am here to tell you that any EV is good as long as it is positive. There will be people out there that share systems with 4EV, or a scalping system with 1EV. That can lead you to think your 0.2EV system is not good enough. Don’t let that feeling drive you to backtesting paralysis.
Let me give you one of my favorite EV comparisons, the roulette casino EV. In Roulette, there are 37 total slots that you can bet on. That means on average, once every 37 bets you win. When you win, you get a payout of 35 times your bet. So let’s say you bet $1 every time. Once every 37 bets, you win $35 dollar. But to get there, you lose $36 dollar (the other 36/37 bets). You basically lose on average, $1 for every 37 bets. That’s a loss of 2.7% over what you’ve bet entirely.
That is the casino EV right there. For every dollar that a customer risks, the casino makes 2.7%. That’s an EV of 0.027. That might seem like nothing, and to an extent that’s true. It only becomes something due to the large amount of bets people place at casinos. The 2.7% is so statistically proven due to how the game works, that across a large enough sample, casinos make a lot of money on roulette.
Trading works exactly the same. Except your EV is likely much better than 0.027, you just have fewer bets per day. A system with a net EV of 0.2 is almost 7.5 times more powerful than what keeps a casino in business. Let that sink in. You don’t need a Holy Grail. You need a small, proven edge and the patience to let it play out.
What makes a bad system?
What makes a bad system can generally be divided in three ways:
A system that uses too many indicators and is unnecessarily difficult. In my early days as a trader, I was told that “Simple Trading is Good Trading”, and that’s exactly how it is. A system does not have to be crazily difficult or have to make you feel sophisticated. Simple rules executed well will always beat complex rules executed poorly. And the algorithms used by institutions in the market will play on overly complex indicator setups anyway, and outperform you in those any day of the week.A system that is unable to be executed realistically (by you). This can be, systems that operate on the 15s timeframe, systems that require you to be behind a screen 24H a day while you work a full time job, systems that have such tight stop losses that fees eat up the majority of your profits (especially happens in Crypto), etcetera. Don’t go backtesting something that beforehand you know is likely not implementable in real life.A system that is discretionary. Discretionary means that your entries depend on your personal interpretation of the chart in the moment, rather than on fixed, repeatable rules. Trading is all about sticking to very specific rules, that you’ve tested, across a large number of trades, and then being profitable. If your rules are discretionary and you encounter a drawdown period, you will start doubting your trades and yourself, because you have no objective data to fall back on. The testing you’ve done really doesn’t say anything, because it depends on how you interpret the market at that moment.
When you’re more advanced, a bit of discretion in your trading is doable, but in the beginning, make it perfectly objective. This also works if at one point you want to automate your trading (Algorithmic trading), in which case your rules also need to be perfectly objective.
Concluding
You now know what a trading system actually is, how to measure if it works, and what traps to avoid while building one. You know that profitability isn’t about finding the perfect system. It’s about finding a positive EV system and having the discipline to execute it consistently.
But that’s also where the hardest part of trading comes in, taking your system live, and eventually scaling up risk. That’s where real money, real emotions, real psychology comes in. It’s also where most traders either break through or fall apart.
In the next and final article of this guide, I’ll walk you through what live testing actually looks like, how to scale your risk without blowing up your accounts, and how your own psychology is the final boss of trading. It’s the thing you’ll be working on for a long time.
Until then, if you’ve got a system idea, open TradingView, or any other analysis platform that has your preference, and get busy testing. Don’t aim for perfection, aim for profitable.
From Market Fundamentals to your First Trading System. What to do. was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.