The Importance of Following a Rules-based Trading Framework
We at the Trade Risk are big believers in rules-based investing. Everything we do — from the way we analyze markets; build scans, trading tools, and quantitative systems — are all based on having rules. Throughout this article we’re going to make the case for why that’s so important and why you, too, should be a big believer in a rules-based investing approach.
I recorded a video overview of everything in this article, so if you prefer to sit back, relax, and watch instead of reading, hit play below. We also have timestamps in the description of the video in case you want to jump around.
Here’s an example of a fully rules-based trading system
It’ll be helpful to have a model trading system to reference throughout this blog post for illustration purposes so we’re going to use the trading strategy we built in Episode 2 of our Beyond the Charts series. It’s a 52-week high trading system, which was profitable and produced a return profile that looked like the following:
We’re going to reference these stats as we continue on in this article.
Rules-based investing can prevent you from betting too large and making a catastrophic mistake
One of the most common reasons traders “blow themselves up,” lose money, or otherwise fail to become consistently profitable comes down to risk management.
Risk management is one of those topics that most people nod their head yes to, but when they’re in the heat of the moment staring at charts, they lose sight of how much they are really risking on their next trade.
How does a rules-based approach help with risk management?
The benefits of a fully rules-based strategy is that you can test and observe what would happen if you risked varying amounts on your next trade. If you have the knowledge and skills to use computer software to backtest, then great! But even if you aren’t a coder, you can still put in some elbow grease, grab a pen and paper, and make note of how your buy/sell rules performed with various risk amounts.
Let’s pull in the stats from our model 52-week high breakout system and observe a couple of things: its win percentage is 47.41% and we noted its largest losing streak was 14 consecutive trades.
This already gives us a lot of information to make an informed decision about position size and how much we might want to risk on a trade.
Ask yourself, what kind of account equity drawdown makes you uncomfortable? Is it 10%? Well, given the system has shown the ability to lose 14 consecutive trades in a row, then you know you’re going to need to risk less than 1% of your account on every trade.
0.71% risk per trade X 14 losers = 9.94% drawdown
Maybe you are someone who can tolerate a 20% drawdown. Well, that means you could risk about 1.4% of your capital per trade to keep yourself comfortable.
Of course, these statistics only show the historic performance of the trading strategy, which means going forward into the future, it’s very possible you could run into a streak of 16, 18, or even 20+ losing trades in a row.
The bottom line: use your rules to simulate the past and get a sense of just how bad things can get. This will help you avoid one of the biggest landmines in trading.
Rules-based investing solves your self-sabotaging, overtrading, fear and greed, lizard brain
A close tie for second on why traders fail to find success in markets is due to their own self-destructive ways.
The market is really good at getting traders to make the exact wrong decision at the worst points in time.
Oh that stock looks beautiful, look at that breakout! Let’s get long.
Market proceeds to dump.
Oh never mind, time to reverse and short this failed breakout.
Stock finds support and then proceeds to make a run higher.
Well I’m not going to chase that again, I’m just going to exit my short to stop the losses.
Stock goes on to rally uncontrollably for the next 3 weeks on end, confirming the original trade idea.
Does this sound familiar to you? I basically pulled that sequence from my old trading journal, and it can be extremely frustrating. What’s worse, is that it can easily put you on tilt to make bad decisions like chasing stocks, revenge trading, or in other words, it can make you behave in a way that’s not part of your well thought out trading strategy.
How does a rules-based approach help with emotional control?
By having a fully rules-based trading strategy, or as close as possible, and as automated as possible, you can significantly reduce the chances of self-sabotage. Here’s the thing, in order for this to work, you actually need to follow your rules. This is often easier said than done, and we’ll talk more about this critical component later in the article.
This is where streamlining, automation and behavioral nudges come in to help you actually follow your strategy. If you have a fully rules-based approach that doesn’t require your judgement, then it’s time to set the strategy in motion and put things on autopilot as much as you can.
For instance, the two fully rules-based trading systems that I follow, Merlin and Lamorak, require zero input from me, and run entirely independently. I submit all the orders the night before in preparation for the next trading session, and that’s it.
I don’t place orders manually. I don’t stare at prices. I don’t second guess. I do the research ahead of time, build trust in the system, and then let them work.
If your trading does require some discretion by you, then try and figure out how to quickly make that decision and then get away from the screens or relinquish control. Remember, this is about preventing emotional self-destruction, so make your decisions and then remove yourself until you’re needed again.
We talk more about automation and streamlining trading strategies in this article: How to Maximize your Screen Time Adjusted Returns.
Rules-based investing will help you find a repeatable edge fastest
The really challenging part about discretionary trading is that it can be hard to separate what decisions of a trader’s framework are contributing to their edge.
For instance, let’s say a discretionary swing trader sees a stock breakout to new all-time highs on heavy volume and then buys the breakout for a trade.
A few days later, the discretionary trader sees another stock breakout to new all-time highs; however, they notice the S&P 500 starting to roll over, and so, fearing that selling pressure will make its way through more stocks, they pass on the trade.
The stock the trader passes on ends up trading higher and higher and so the next breakout the trader sees, they buy, despite the S&P 500 looking even weaker.
This time, the stock fails and reverses lower causing the trader to lose money.
As this situation repeats itself over and over again, and the trader uses circumstantial evidence with varying degrees of weighting to make trade decisions, it becomes uniquely difficult to figure out which factors are really making this trader money.
Did they just get lucky? Was the market in an uptrend doing all the stock picking work for them? Did they pass on a trade because of something they thought was important, but it didn’t really matter?
How does a rules-based approach help with finding edges?
Since every decision needs to be based on a black or white rule and applied uniformly without judgement, there is no disputing what is the driving factor for performance.
You can create a buy rule as long as all conditions are met:
- Stock closed at new all-time highs and
- Volume is above 50-day average and
- Market is an uptrend (trading over a 200SMA)
There’s your entry criteria and now you can test your results on historical data. How did the strategy perform with these rules? Okay, now let’s try removing rule #3 to see if that matters. Did results change significantly, or not much?
I’m not suggesting this is the proper rules-based development process. Rather, I’m illustrating there is power in having the cold hard facts of clear rules with measurable results.
When you trade using variable decisions, finding out what works gets complicated.
Save yourself time, stress, and decision-fatigue
Often overlooked, but probably one of my favorite reasons for transitioning to a fully rules-based framework was saving time, reducing stress, and eliminating decision-fatigue. When I was discretionarily day trading and swing trading several hours or more a day, I experienced so many more emotional highs and lows.
I took my performance personally, I beat myself up, and I felt very attached and responsible for my PNL at the end of the day. Part of evolving as a trader is understanding that this, of course, shouldn’t be the case for anyone, and while I worked hard to break that psychological link, nothing made such a shift in my mindset than effectively “outsourcing” the trading to my pre-planned rules.
As a fully rules-based trader, I no longer have any real-time input on a day-to-day basis. The switch flipped in my brain to not take results personally anymore. I’m not stressing about interpreting market action or wearing my PNL on my sleeve. I’m putting in the work ahead of time to research my strategies and then I let them trade the market independently.
My role as a trader has transformed to research and reviewing strategies rather than being the person responsible to make and execute on signals.
What’s required to be a fully rules-based trader
Are you sold on a fully rules-based trading framework? Doesn’t it sound great?
Well, there’s a couple of important details you’ll want to keep in mind when you go down this path. They are what make all the pros we just talked about possible.
Just because you have rules, doesn’t mean you’re done. It is up to you to actually follow those rules.
This is a big one.
We can all say we’re only going to buy a stock if conditions A, B, and C are met, but will you actually stick to those rules?
What happens when you follow your rules and the market hands you back five losing trades in a row? Are you going to abandon your process and go rogue — doubling down on whatever stock CNBC is broadcasting that day?
This topic deserves its own blog post altogether, so we’ll keep it short here, and just remind everyone that this only works if you actually follow your rules.
Not all rules are good rules.
Here’s the other big catch.
Let’s say you have a set of rules and you are confident you’ll follow them with 100% discipline and never deviate.
The issue now is that you might still have something that isn’t profitable!
Maybe your rules tell you to buy after conditions A, B, and C are met, but those could be lousy rules. They might not be profitable at all.
So just because you are rules-based and disciplined doesn’t just guarantee you’ll make money. You need to actually uncover a repeatable edge in the market.
This leads us right into the heart of strategy development, which we’ve written a lot about over the years. Here are a few helpful resources:
- How to develop simple swing trading strategies
- ‘Strategy Development’ articles in our learning center
- Stock scan and indicators to build your own trade setups
Why everyone should strive for rules-based trading
There you have it. The key benefits on why I believe everyone should strive to be as rules-based as possible. Keep in mind, if you’re a new trader just getting started, it’s going to take you some time to learn about the market, find a strategy, and then build confidence in it.
It took me nearly a decade of nonstop learning and strategy development to arrive at 100% rules-based strategies that I have complete confidence in. Don’t think you have to get there overnight.
Lastly, remember, having a little bit of discretion might be right for you. You could be a trader that likes to be 90% systematic, but you might give yourself a little wiggle room in deciding which of 3 signals to take, or how much conviction (size) to commit to a trade.
As always, everyone needs to find what works for them and make the process their own.
What are your thoughts? Are you rules-based? Fully rules-based? Leave your experience below, I’d love to read it.
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Posted in Article, Risk Management, Trading Education, Trading Psychology, Trading Success
Tagged with Backtests, Quantitative Trading, Systematic Trading, Trading Automation, Trading Psychology
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