I had a good idea. It was going to make my company millions of dollars per year. It was different, but certainly doable.
“How much do you think it will bring in?” our finance executive asked me.
“If we just focus on emerging markets, I think it could be up to $10 million next year.”
“Not interested.”
His reply was flat and caught me off-guard.
“It’s $10 million!” I insisted.
For him, it just wasn’t worth it. A million here and there made no difference to him or (more importantly) his boss; it’s a rounding error on the balance sheet. Such is the life at a multi-billion dollar firm.
I share this because it highlights one of the critical differences between large institutions and retail players: scale.
When people say retail can’t compete with the funds like Citadel, Renaissance Technologies, DE Shaw, and others — they’re right. You don’t try to play that game.
Instead you “go where they ain’t” and focus on making money in places that they aren’t interested in playing.
Where are those places?
Opportunities Scale with Account Size
As the anecdote above highlighted — you can go to find markets that can’t scale to meet the needs of a larger fund. A retail trader may be thrilled if he can make a few thousand dollars or tens of thousands on some of their trades — for some people that’s anywhere from a nice bonus to paying the bills for a year. A wall street behemoth looks at that as the tab for lunch.
Think of it another way. My wife and I travel a lot and she always has friends in various countries who want us to bring something to them that they can’t buy in their home country. They’re often willing to pay a 50% markup for these items. Does this mean we ought to drop everything and get into an import/export business because we’re sitting on a 50% profit margin? No! This doesn’t scale. It’s nice for some one-off exchanges, but we’re talking about paying for lunch here.
You may be able to make a 50% return, but if that tops out on a few hundred dollars of profit, then it’s not worth the time and effort. For the big boys, they look at those small opportunities and scoff; not enough liquidity and not enough scale. That’s where the disciplined small investor can thrive.
Longer Term for Less Competition
Prioritizing this month’s or this quarter’s earnings has long been an issue in capital markets. Fund managers are eager to keep clients happy so their AUM doesn’t take a hit, but they’re pressured to release monthly earnings statements which show growth, or they risk losing clients (and their hefty fees).
We can see this in the data as the average holding period for a stock has continued to fall over the years.
This short-term, chase-what’s-hot-now-approach is part of human nature, so good luck trying to make money in the same realm that everyone else is working in.
You can go against the flow, zig when everyone else zags, by trading more slowly and longer term. Taking long term approaches can help you avoid playing in an overcrowded market, because you’re the only investor you need to answer to. If you can develop a plan and stick to it, then ride it without apology.
How You Can Use Algos to Reduce Your Emotions
Sticking to a plan is where the rub lies. We are emotional creatures, particularly when it comes to money.
Too many live and die with every up and down day in the market, changing their “strategy” accordingly.
So how do we deal with ourselves — our biggest enemy in investing?
My answer has long been algorithmic trading.
We can program a cold, emotionless computer trade for us. We just need to develop some rules, hand them over and let the machine run.
This raises the question, how do we find good rules?
There are a few ways to go about that, but it always boils down to doing your own research.
This should be obvious to some extent. If you want to come up with a good strategy, you’re going to need to research it to make sure it works. Get the data, try the rules and see if your stats check out. If not (and most don’t work well) then you tweak it or come up with a new idea and try it again.
Can you take a shortcut? Like reading a book that promises to make you a stock market millionaire?
That’s all great! But you better go test it before you start trading it. See if the claims you read actually match up with reality. There’s no shortage of authors who will print a beautiful equity curve that marches up and to the right. It gets eyeballs and sells books. But is it real or just an illusion?
So you’re back at spending time to get data, code a strategy, debug it, and see if it works (and have fun if you’re going to do this right without coding!).
And you repeat that cycle every time you want to test something new. We haven’t even gotten to deploying it so you can make money either.
It doesn’t have to be that way. At Raposa, we’re building a no-code algorithmic trading platform. We want you to be able to design and test a strategy in just a few clicks with high-quality data, and get results fast so you spend less time working through the tedious minutiae of debugging your code and can find trading strategies that fit you.
Get the tools to play where the big boys ain’t and join our waitlist here.