Earlier quoted context omitted.
Great question. If I beat the market by 20% (say SPY generated 0% for the year, very optimistic at this point), and I have allocated $100k to this, I make $20k before taxes. That's less than minimum wage. Meanwhile, allocators expect a track record of at least 3-5 years. Ideally, if I have an asset, I'd like to extract as much revenue as I can. Hope this makes sense.
If you're sitting on a gold mine, you can wait 5 years. This does not make sense.
The anatomy of an ML-powered stock picking engine
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Re: The anatomy of an ML-powered stock picking engine
#32Earlier quoted context omitted.
Great question. If I beat the market by 20% (say SPY generated 0% for the year, very optimistic at this point), and I have allocated $100k to this, I make $20k before taxes. That's less than minimum wage. Meanwhile, allocators expect a track record of at least 3-5 years. Ideally, if I have an asset, I'd like to extract as much revenue as I can. Hope this makes sense.
How difficult is it to get investors when you can show your model beats the market consistently? Of course, they have to check your not trading a strategy with extreme tail risk, but here it sounds like that's not the case?
Re: The anatomy of an ML-powered stock picking engine
#33Earlier quoted context omitted.
Great question. If I beat the market by 20% (say SPY generated 0% for the year, very optimistic at this point), and I have allocated $100k to this, I make $20k before taxes. That's less than minimum wage. Meanwhile, allocators expect a track record of at least 3-5 years. Ideally, if I have an asset, I'd like to extract as much revenue as I can. Hope this makes sense.
If you're sitting on a gold mine, you can wait 5 years. This does not make sense.
Re: The anatomy of an ML-powered stock picking engine
#34Hi, fellow HN'ers! Author here, please let me know if you have any questions or thoughts!
This is great! Thanks for writing this! I have wanted to do something like this for a while, purely for learning. The thing which puts me off is that there is a huge amount of knowledge needed in understanding the features vs the ML. Could you recommend a base system / reference one could use to get started which explains or bakes in some of the feature / signals engineering work? Also would this approach work with c…
Some of it works on crypto. TBH I've stayed away from the asset class, but only because I find it difficult to build mental models and think about features (in my mind, it's a mix of commodity factors and currency factors, but I'd have to test it out).
I seem to remember coming across papers that have tested momentum factors at larger time-frames (e.g. weeklies).
> Could you recommend a base system / reference one could use to get started which explains or bakes in some of the feature / signals engineering work?
The references I put in at the end of the post will really help with this! I might actually write out a separate blog post about starting out in this space from an ML perspective. Thanks for the idea!
Re: The anatomy of an ML-powered stock picking engine
#35It's usually very difficult and it takes a lot of money to run a proper fund.
Let's say you raise $50M. You can maybe charge 1 and 20,meaning you get 1% of assets each year for running the fund and 20% of profits.
1% of $50M( and keep in mind this is a large raise for someone without a track record on the sell side or inside another fund) give you $500,000 a year to pay:
- salaries( lets say you pay yourself $100,000 all in plus the same for a single analyst
- a Bloomberg terminal $30,000 including data feeds
- market data feeds you need $25,000/year for basic market data and fundamental data that you are allowed to warehouse(you can't store data you get from the Bloomberg terminal).
- rent $50,000/year for office space
- outside lawyer fees and outside accounting fees $100,000/year
- similar fees for someone to run your back office, roughly $100,000/year.
And on the other side of expenses you have the money making side of things. Which as the OP pointed isn't great. If you return 10% on the 50M you get to keep 20% of that so a 10% return gives $5M in profits and you keep $1M.
That allows you to bonus out yourself and analysts on good years. If you lose money one year then you get no bonus and have to bonus out the employees out of the retained earnings you kept from previous bonuses.
it usually gets worse as most funds have what's called a high water mark. This means you don't collect the performance fee until your fund gets back to the high water mark. So if you are down 10% one year you need to make that back before you start to make any performance fee, which is why most funds shut down if they go down more than 20%.
As to raising money.....Anyone can show a model that makes money. that doesn't mean its easy to create a model, its just that there are alot of people capable of building such a model.
Its the risk management that people with money are really looking for and sadly that's just really hard to show out of a model as part of the risk management is things like positions sizing and showing your model doesn't pile into one asset class or trade correlated products.
it bodes well for the OP that they talk about market regimes as, IMHO, this is one of the biggest risk management tools that aspiring traders ignore.
And this risk management is why people ask for a track record of more than a year.
Re: The anatomy of an ML-powered stock picking engine
#36If you have a tool that can generate great returns, then why fall back to a newsletter?
Great question. If I beat the market by 20% (say SPY generated 0% for the year, very optimistic at this point), and I have allocated $100k to this, I make $20k before taxes. That's less than minimum wage. Meanwhile, allocators expect a track record of at least 3-5 years. Ideally, if I have an asset, I'd like to extract as much revenue as I can. Hope this makes sense.
Re: The anatomy of an ML-powered stock picking engine
#37Re: The anatomy of an ML-powered stock picking engine
#38Someone asked about how difficult it is to get outside investment.... It's usually very difficult and it takes a lot of money to run a proper fund. Let's say you raise $50M. You can maybe charge 1 and 20,meaning you get 1% of assets each year for running the fund and 20% of profits. 1% of $50M( and keep in mind this is a large raise for someone without a track record on the sell side or inside another fund) give you…
I have often found myself struggling to explain the difference between building a strategy or trading system (which reduces to a technical/intellectual challenge) and running a hedge fund (essentially running a complex information-driven business).
Your cost breakdown really puts matters into perspective.
> it bodes well for the OP that they talk about market regimes
I concur. Market regimes (modeling, detecting, reasoning about them) are too delicious of an intellectual puzzle to resist.