Transcription
These free principles from Jim Simons will allow you to avoid costly mistakes and build better strategies right after watching this video. This man over here turned Renaissance Technologies into the most successful hedge fund in history, doing 66% annual returns before fees and after hedge fund fees was around 33% uh annual returns for 30 years.
While most of his edge remains a secret, he's openly shared principles that work for retail systematic traders just as well as they worked for his billion dollar fund. The reason why I know these work? While these are the exact rules I employ in my own algorithmic trading that led me to do 18% last month. While these are nothing compared to obviously Jim Simon's performance, this has completely transformed me from an unprofitable trader to one that now can do 18% in a month.
If you're wondering what is Jim Simon's overall performance over that time, here's a nice little table from 1998 to 2018. And you can kind of see the returns by each year and the size of the fund as well in millions. Ultimately, he capped the fund at 10 billion because it wasn't able to handle any more capital than that. But being able to handle 10 billion and doing these sort of returns on average is still impeccable.
Now, the first rule you need to know is that past performance is the best predictor of success. Most traders completely ignore this. They trade based on gut feelings, recent price action, and what worked last week. But Jim Simons did the opposite. Renaissance test tested everything against decades of historical data and was one of the first funds to actually use data in this capacity. and he even sent some of his employees to go down to the New York Stock Exchange and collect some of this data by hand before there was like you know APIs and everything like this for data.
Now how do you actually apply this? Well before deploying any strategy you want to back test it over at least 5 years of data or as many samples as possible really. Ideally this will include multiple market cycles. So bull markets, bare markets, sideways chop, etc. If your strategy only has 18 trades over two years, that's not really enough data. You need to keep testing or move on. The reason for this is because the law of large numbers. The more samples you get, the closer you get to the actual expected mean or the expected value of that particular strategy you're trying to test. Simply put, more historical samples equals more confidence your edge is real and not just luck over, you know, 18 trades. Stop trading based on your last 10 trades and start trusting tens or years of data with your actual execution.
One common question I get about this, it's sort of like a practical question is what happens if you don't actually have that much data for a particular market. uh for example, this is one of the core problems really in trading. There's a lot of way more complicated ways of trying to like simulate data. So create fake data that has the characteristics of real price data, but that can be quite difficult to do. Apart from that, at least in my opinion, I just try and focus on strategies that I can prove over a large enough sample size do seem to hold some sort of edge. So if a strategy, for example, only has 18 trades, I'm most likely going to move on unless there's some other way I can get some data.
Now, rule number two is we don't override the models. This is the hardest rule to follow. When your strategy hits a draw down, when you're down 15% and every losing trade feels personal, it can be really easy to override your strategy. But Jim Simons had one strict rule and it's never override the models based on emotion or really in general.
Now, why does this matter? Well, every strategy will have losing streaks. If you back test properly, you know this ahead of time. A key thing I like to say around back testing is it teaches you about the behavior of the strategy. A lot of people come into back testing purely for optimization. So trying to like get the highest returns possible which is a somewhat flawed way of thinking about it. And then two obviously testing if the strategy works which is completely sensible but another key thing it tells you is what is its risk profile like how long is the average draw down? What is the max draw down that it's historically had? What is your anticipated sort of equity curve going to look like? Is it going to be a lot of small losses and then big jumps on you know one 10our winner etc.
And the reason why this is also important is the traders who make money stick to the systems during draw downs. The amount of traders I've spoken to where they have quite a solid, simple, nice strategy, but it doesn't meet their, you know, dream outcome of that it's going to never have a draw down. It's going to, you know, be winning every single week. It's going to be doing 100% every year is an insane amount. I think a lot of trading because of whatever like I think what everyone kind of gets into trading for, right, is like making as much money as possible. Everyone has very high expectations for what they think their performance is going to be able to be. But most likely you're going to be running something that's sort of a risk premium or trend following model or a mean reversion model. It it can still perform quite well, but you're going to have periods where maybe a month, maybe even two months, you're not going to make any money. And that can be very difficult to like mentally handle. And often the ones that do blow up are the ones that turn off strategies at the worst pos possible time or the ones that just completely pivot, you know, from strategy to strategy trying to find that kind of holy grail strategy that they think is going to be the one that actually makes them fully profitable.
My best tip I can give for this rule is try and automate as much as possible. I'm I automate pretty much all my strategies and that has helped me a ton because I can step back from the stress of you know watching a P&L on the day trying to execute a trade every single day all those sort of things and I can more look at it it as a large lens view where I can see the portfolio of strategies and just how they perform on month quarter to quarter etc.
Now, rule number three is the system is always leaking and we have to keep adding water. Even Renaissance, they've had an army of PhDs. They had some of the smartest people. They had massive computing power. They all know their edges decay. Markets evolve, strategy stop working, competition adapts. The key thing he always emphasized was you have to keep on researching. And this is kind of across the board with a lot of funds. Like Ken Griffin said, trading is the way to monetize your research. And this is quite similar in this sense where you have to keep on researching.
The mistake most traders make is they maybe find one profitable strategy and they stop researching altogether. They think that's their one strategy now that's going to make them profitable forever and they're just going to keep on, you know, trading that particular one. Whether it be 1 month later, 6 months later, 2 years later, etc. That edge does normally fade at some point and you're going to be starting again from scratch.
So, how do you apply this? Well, I would dedicate at least 25% of your current time to testing new strategies. Now, obviously, this can be a bit difficult if you aren't automated. So maybe that would be a bit less time, but for me, most of my day nowadays is testing new strategies, looking at new ideas and just trying to get uh some inspiration for what I think could add to my portfolio. Another key one is testing new markets. Uh adding crypto, adding Poly Market, for example. Poly Market has a lot of small inefficiencies you can kind of exploit right now. Now, they are quite a liquid, meaning you can't push a ton of capital for it. But if you're starting with a small account, there's definitely things you can find on Poly Market, for example. I'd also say testing new markets is perfect when you have maybe a bit of automation or if your strategies are quite simple for you to execute such as swing strategies, right, that don't take too much time to execute because adding new markets adds more diversification. It can normally add more uh total returns or risk adjusted returns as well. And you can also explore like new time frames. So daily, weekly, uh lower like 4 hour, 1 hour, etc.
You can read new papers and books. I will say a lot of people think academic papers are like you know they're going to detail out a whole strategy and it's going to work and you just simply click play and you you know you execute that strategy and it works. Most of the time academic papers are somewhat forward in some essence but that doesn't mean you can't get value from it. And I do see this a lot in the whole trading community is that if something doesn't easily lead to you getting more returns most people sort of just disregard it right they think well academic papers are normally for they don't really always work. if there's normally something they haven't mentioned or maybe an assumption they've made wrong, but they don't take it for all the value it can provide with new ideas, new approaches that you can test and build on from there. Same thing with books. A lot of books I recommend, uh, people that do, you know, go on to be really successful from them normally take the parts they like from the book and then build that into a really good strategy or take the lessons they've learned from that book. A lot of people that find those books not useful is they kind of go into the book expecting it to give you a strategy and you're just going to execute that strategy and now you're, you know, a millionaire in the next month.
Lastly, uh probably the most important as well is adapting ideas from other successful traders. Try and keep a pulse on what other traders are doing well at this current time and see what they are sort of trading or what they sort of uh hint at trading. For example, there's been a lot of people on Twitter showing very good P&Ls around poly market and that's cuz you know poly market at the moment is a newer market. Prediction markets are overall newer and they're becoming a bit more liquid which means you can do more strategies here and there.
Ultimately, all of this is for that the strategies you develop during the good times save you during the bad times. Both in draw down sense as that you get a bit better riskadjusted returns because you're running more strategies in a portfolio, but also in the sense that if a strategy stops working, your trading career isn't like completely halted. You know, you can still have other strategies you can run.
Now, as a TLDDR, Jim Simon's principles aren't complex, but they are a bit hard to follow. You want to trust historical data over gut feelings. You want to back test everything religiously. You never want to override your models, especially once you've, you know, built them and they they look sound. You want to stick to the system during your draw downs. And lastly, constantly research new strategy ideas. Edges decay, so always be building and researching new things. Also, it keeps you on your toes and normally makes you a better trader overall because you can learn a lot from other traders. And then lastly, if you want to learn how to back test and build robust strategies, check out the first link in the description.