Strategy 5 – We’re cooking with gas now.
Finding an edge after the popular “Gap and Go” strategy. This strategy made $170k in the past two years (750 trades) with a 66% ROR, 15% MaxDD, 1.3 profit factor, and a 2.1 Sharpe ratio.
Disclaimer: the following post is an organized representation of my research and project notes. It doesn’t represent any type of advice, financial or otherwise. Its purpose is to be informative and educational. Backtest results are based on historical data, not real-time data. There is no guarantee that these hypothetical results will continue in the future. Day trading is extremely risky, and I do not suggest running any of these strategies live.
This strategy doesn’t use a single indicator we have discussed the past two months. Actually, it barely uses an indicator at all. This strategy uses an exponential moving average, but it’s hardly fair to call a moving average a trading indicator, exponential or not. Instead, this strategy uses a popular day trading strategy called the “Gap and Go”. This strategy was popularized by Ross Cameron (Warrior Trading), and you can find the criteria for this strategy all over the internet and on YouTube.
Here are a couple links:
The Simplest Day Trading Strategy: Gap and Go ↗️📈 #stockmarket #daytrading (youtube.com)
How To Trade Gap Up and Gap Down Strategy - YouTube
You can find different variations of this strategy all over the internet. I will focus on the version that Ross Cameron, an expert momentum trader, talks about and trades all the time.
Stocks have a market capital above 50 million and under 2 billion. This is referred to as a small-cap stock.
The stock has a low float, which is the number of shares available for trading by the public.
The stock has “gapped” up a certain percentage. This means that the stock’s open is above the previous bar’s close.
The stock’s price is usually under $100. This is not a hard rule. Ross Cameron will focus on the lower side of this (between $5-20) when discussing building a small account through day trading, and it is the price range I will focus on for this strategy.
That’s it. The beauty of this strategy is its adaptability. Certain parts can be adjusted, depending on the size of your account and risk tolerance. The part that might differ between traders is timing entry and what technical features you want to look at for planning a trade entry, giving you the power to tailor it to your needs.
I appreciate you breaking down the criteria of this trading strategy, Larry, but if this strategy is easily found on the internet for free, what makes your strategy different, and why do I care?
Because, other Larry, we don’t actually trade this strategy as intended. Instead, we use the criteria in this strategy to create a new strategy that doesn’t trade these stocks until after a successful “gap and go” trading day.
There is an old saying. Something about old dogs and new tricks?
Is this your way of prepping us for another…
Lesson from the Past
One of the many interesting people that I got to work with overseas was a man who used to be a Force Recon Marine. Let’s call him John. John was a cool dude. I’m not sure what he was doing working WPS contracts (yeah, I do, the money), but it was nice to have guys with his kind of experience working with us.
If you know anything about military guys, there is almost always a “no shit, there I was” story when you are sitting around waiting for too long. One of the stories John told me has always stuck with me. It was a story about a mission that almost happened.
Have you ever heard of Abu Musab al-Zarqawi? You may not know that name or his real name (Ahmad Fadhil Nazzal al-Khalaylah), but you have probably heard of ISIS. Zarqawi was the man who started ISIS and was one of the most deadly and sought-after terrorists in Iraq in the early/mid 2000’s.
John told me a story about how his team had been spun up to train for a ground assault mission in Iraq to go after an HVT (high-value target). Later, he discovered that the intended target was Zarqawi. He said that his team started training for the mission, and when the time got closer, they were stood down on the mission, and a Different group of special operations guys were chosen to run the mission instead.
This isn’t an unheard-of practice in the world of special operations. From my understanding, they will spin up several different teams for the same mission and then choose the more appropriate team to run the mission. I’m not sure what the criteria for choosing are (because I am not JSOC), but in this particular case, it didn’t matter.
At some point (right before the mission, according to John), it was decided that a ground assault wouldn’t be feasible. It’s easy to assume why this decision was made. The risk for failure and the risk for the operators on the ground were too significant to green-light a ground assault. So, they fell back on a faithful American favorite, a tried-and-true option.
The bomb.
The team intended for the ground mission became the team for body recovery and target identification instead.
Old dog, same tricks.
John always ended this story with some good old-fashioned shit talking about the team that was supposed to run the mission but ended up running recovery instead. According to him, his team could have pulled it off without using a bomb. I can’t speak to the accuracy of this statement. Still, a quick search online or reading any of the several books written about the US involvement in the Middle East confirms how the operation concluded.
Whether John was talking shit or whether he truly believed what he was saying is unknown. What is known is that there is ALWAYS a risk to operators when you assault the Alamo. There are three rules for close-quarters battle (CQB): surprise, speed, and violence of action. Once the “surprise” portion is gone, the risk assumed by the operators jumps up tremendously.
Back to the Present
When compared to trading, the risk in the above scenario can be connected to the drawdown and failure risk of a trade (albeit a bit more macabre). A trade strategy with a large failure risk, or a strategy with a large drawdown risk, might be an unacceptable risk for most traders. The gap-and-go strategy is no exception. There is a lot of risk associated with this type of trading strategy. It requires good scanners and a lot of practice to trade this system correctly. It can be turned into a automated trading strategy, but it would require a lot of streaming data and investment up front. It would also be competing with a lot of major funds for space. You would also need a way to find predictable catalysts. The list goes on. However, after some analysis, I have found an alternative strategy that could potentially mitigate these risks.
Like the Zarqawi mission, there is no need to take an unnecessary risk. We have good intel about our target’s location. In our case, that is the successful gap-and-go strategy. Instead of playing the same game as everyone else, I decided to see if there was another option that didn’t require as much risk. I was looking for a different edge. I wasn’t expecting to find that edge so quickly. It started as a simple idea I played with over the weekend. Since RealTest makes writing strategies quick, I figured I could type it out and see if there was anything there.
It turns out there is. I’m willing to bet I am not the first to find it, either.
Backtest Results
The backtest results shown here are for both the long and short sides of this strategy. Both sides are profitable, but the long side makes more trades than the short.
The results are also compared to a buy-and-hold benchmark strategy on SPY.
Trades are only held for a maximum of one day, so it is a day trade and not a swing trade strategy.
I used Norgate Data to test this strategy. They have a good trial offer for anyone interested in checking out their data. It gives you access to all data for the past two years, which is why this is tested on 2 years of data.
This strategy was tested using the RealTest platform. That means the code for this strategy is written in RealTest Script. This scripting language is pretty damn simple and can be adapted into any programming language as necessary.
I want to point out one big caveat to the previous statement; RealTest is one of the few backtesting platforms that makes testing multiple strategies on multiple assets easy. That is the superpower of this backtesting engine. Converting this to a different platform (NinjaTrader, TradeStation, etc) may not be as straightforward as it is here. It is possible; I just haven’t attempted to do so yet. As soon as one of you reaches out to me and asks me to see if I can replicate this on a different platform, I will find out exactly how difficult it is.
The best bet would be to convert it into a custom backtesting engine, such as the one found at HangukQuant’s Newsletter, or create your own backtesting engine (which I plan to start trying to do after this post).
Summary Stats:
Equity Graph:
Drawdown:
Monte Carlo Analysis: This shows the top/bottom 5 results out of 100 samples.
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The rest of this post is for paid subscribers. Paid subscribers will have access to the private GitHub where all the Hunt Gather Trade code and strategies live. It is continuously being worked on and will expand as we explore the world of automated trade systems.