The path to quant trading

Is there actually a destination at the end?

There was a time when I first got into day trading that I thought, “oh, there are rules? This is going to be easy.” I started off well enough. I used a simple gap-and-go strategy, fast data, direct broker access, and hot keys. My first month I was up about 10k (amazing for how small my account was starting out), so I pulled what little I needed to pay bills for the next month and kept at it.

The first month led into summer and I made about two hundred dollars total the next 3 months with plenty of asshole puckering drawdowns in between. I decided this wasn’t the style of trading for me and did what any amateur (I am still one of those, don’t get it twisted) would do. I started looking for different ways to trade.

I switched platforms and started trading slower, with my mouse. This worked for a time, and then it didn’t. I switched again.

This went on for about 9 months, constantly changing up what I was doing until I landed on a slow and steady way to trade ES/MES that I felt comfortable with. I also discovered algorithmic trading.

Damn, I thought. That sounds like the sweet spot. You mean I can use my wasting developer skills to research strategies and then program them to trade automatically for me? Yes, please.

So, while I traded slowly, manually, I started researching this algorithmic trading thing. I launched this Substack to document it along the way. My manual trading did okay, not bad enough to quit, not good enough to own a G-wagon. I dove in head first.

The first strategy that had great backtest results and drawdowns I could handle (I thought) went live about a week before a planned trip to Disney World with the family. That first week, it went great. It had an automatic stop at $2500, which backtests showed it rarely ever hit, typically only losing a few hundred dollars with bad trades. It took profits pretty fast, and would trade several times a day when criteria was met.

So, I felt comfortable setting it up to run while out at the parks, enjoying the theme parks.

The one thing the backtest never showed was that if the market gets volatile enough (not enough testing data), and criteria is still technically being met, there is nothing saying that it couldn’t take max losses multiple times a day. Like the rookie I was, I didn’t program in a hard stop. Of course, I came back into the room to find that it had failed twice (that’s 5k for those who can’t math) and was currently in a third losing trade.

Fuck me.

I pulled the plug on the trade, taking my licks, and shut down the strategy.

Back to the drawing board… back to manual trading for a while.

I think this was when I actually found the entrance to the rabbit hole. I started looking for anything and everything that was going to help me avoid that mistake again. I wanted a better trading platform, I wanted better testing techniques, I wanted in depth risk analysis with more data, I wanted my fucking money back!

I eventually dug myself out of that drawdown, but it was slow, and I was scared to take risks again. I even quit trading for a while, telling myself that I needed to know more, to learn more, so that I wouldn’t have any more black swan events like that one. Knowing what I know now, it is unfair to call it a black swan event. It was very possible for me to have known about that risk. I was just naive.

Anyway, I kept trading manually and I kept studying. HGT (that’s this Substack, keep up) started changing. I started focusing on mathematical concepts, and researching how to more accurately test strategies and research ideas. I looked into people like Jim Simons and picked up some obscure books, like those written by Timothy Masters.

There was no "aha!” moment. No mentor came to my rescue. There were times when I was in contact with other traders, but I eventually fell away from them all as I started learning more. I felt like I didn’t want any other influence while I was searching. It all felt hollow, like everyone had their own ideas and was confident they were correct. I wasn’t convinced.

During this time, I came to a conclusion: all day trading is gambling. Some people do it by feel; The cowboys, the discretionary traders hyped up on cocaine caffeine, staring at charts all day long, year after year, fingers on the pulse (in the form of ticker tape, or the new age equivalent). Others study the data, monitor the news, and trade in a way that resembles valuation estimations, buying when an asset is undervalued, selling when it returns to value or holding it until it makes them millionaires (like anyone who bought Apple in the 90s).

People make a living gambling, right? The same principles apply: you need a system, you need to know the odds, you need to be able to read the room, and you need to know when to exit, before that big fucker in a suit who started moving closer to your table gets within reaching distance.

I asked myself, what is it that the pros are doing? What are the firms and people with too much money doing? Turns out, they are doing math. Lots of it. Hard math too. The kind that makes men weep, preferring instead to enter the breach once more, anything to avoid having to learn about something that can’t be fixed with a hammer or a bullet, let alone figure out what an epsilon means, or those tiny little numbers and letters below that weird fucking ‘E’.

After being displeased with every platform I was using, I decided to build something on my own. Enter quantKit. My way to give back to the community (assuming it is worth a damn).

But, there is a catch. It’s a pretty big undertaking, especially for someone who is self-taught. I didn’t go to school for this, I have never had a mentor (unless you count The Primeagen on YouTube), and I don’t have any idea if what I am doing is going to be any better than what others before me have done. I can guarantee this though: it will be free, it will be well documented, and it will be better than something proprietary, which requires you to conform to their way of thinking.

This undertaking has actually required me to stop trading actively, or day trading rather. It requires my full attention, which, as always, means that I ignore it until I feel overwhelming pressure and disappointment before binge studying/coding until my brain is leaking out of my ears and I am tired before noon every day.

That is the path though. This shit isn’t a flat stroll through the woods. It’s fucking treacherous. I don’t have any idea if there is anything at the end of this path or not, but I am sure as shit going to find out.

Because here's what keeps me up at night: maybe this is a game that can't be won. Maybe those retail traders making a living are just riding good luck until it runs out. Maybe when I see quant firms starting Substacks, dispensing wisdom like digital prophets, they're just the house telling the marks how to play better — keep losing, but with more style.

Am I building another tool to help people lose money more elegantly? At least it'll be free (as in speech). Maybe that's something. Maybe it's not.

The path to quant trading might not have a destination. But I'm walking it anyway.

Happy hunting everyone! Until the next one.

This post 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.

In case you were wondering where my usual AI art at the beginning of my articles went, after trying to defend the use of AI generated art on a Note thread, I convinced myself that I was indeed a piece of shit for using it. In place of it, you just get this explanation of why it isn’t there.