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The anatomy of an ML-powered stock picking engine

principiamundi.com

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Re: The anatomy of an ML-powered stock picking engine

#91

Post by asavinov »

> I have always kept in mind is that feature engineering is almost always the key difference between success and failure

I also developed an ML-powered service heavily relying on feature engineering

https://github.com/asavinov/intelligent-trading-bot Intelligent Trading Bot

Its difference from Didact is that this intelligent trading bot is focused on trade signal generation with higher frequency of evaluation. It is more suitable for cryptocurrencies but also works for traditional stocks with daily frequencies so it could be adapted for stock picking. What I find interesting in your work is the general design of such kind of ML systems relying on feature engineering.

Re: The anatomy of an ML-powered stock picking engine

#92

Post by drdrek »

If you have a guaranteed compounding money machine that out perform the market by 20% just let it run, sooner or later you will be able to buy out those who did not invest in you. If its just a useful recommendation engine than there are indeed a lot of questions relating to personal finance or investment strategies that have nothing to do with machine learning that needs to be addressed for PMF. You don't need better models you need to understand the needs of your customers.

Re: The anatomy of an ML-powered stock picking engine

#94

Post by thunky »

HFguy wrote: post #53
adamsmith143 wrote: post #21

Earlier quoted context omitted.

>2. It went as described in the article - for the capital I allocated to Didact, I beat the market (SPY) by ~20% since inception. This seems extremely hard to believe. You should be running a multi-billion $ Quant fund if this is the case. The idea that you would try to push this as a newsletter rather than just taking investor money and becoming a billionaire literally makes the story seem farcical.

It is very easy to believe. I could have flipped a coin, gone long or short at beginning of this year. I would have had a 50% chance of outperforming the market by 40% this year (given it is down roughly 20%).

Right. The difficult part is doing it consistently.

Re: The anatomy of an ML-powered stock picking engine

#95

Post by chollida1 »

HFguy wrote: post #50
chollida1 wrote: post #35

Someone 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…

This is actually way too optimistic. Your first 1-2 seed investors will: - Only pay 1 and 10 (1% fixed fee and 10% of PNL) - They will also get ownership of the actual fund management firm and will get that in the form of 20% of REVENUE (not equity, revenue, think about that) This is one reason new fund formation is way down. The economics are bad for years. Know a bunch of HF people that started vc-backed tech firms…

Ha, you need a better network:)

I don't know too many people who have started funds in the past 5 years, but of the 3 who did, none gave up any ownership in the management firm.

That's a suckers game and the only people who would need to give up any ownership are people who are very green:)

Re: The anatomy of an ML-powered stock picking engine

#96

Post by gbasin »

Straw wrote: post #82
gbasin wrote: post #37

If your predictions are good, I'd be happy to get you $100 million in assets to manage. It's very unlikely that your predictions are good...

I've been thinking about trying to build something from scratch with a similar spirit, but very different methods, but I also doubt that my predictions will be any good without far more time investment than I have available. As you say you have expertise in the area, any chance I could ask you for advice or how to decide if its worth trying?

Sure ping me on twitter

Re: The anatomy of an ML-powered stock picking engine

#97

Post by alpineidyll3 »

maCDzP wrote: post #88
alpineidyll3 wrote: post #55

My heart goes out to this author, but you can tell even by his first table that he doesn't quite understand the mathematics of financial markets, the purpose of a hedge fund, how they grow etc. 1) It's plain by quickly looking at the allocation of capital in investment firms, that AUM is not made by performance; it's marketing. At best people invest when they believe a person is connected to inside information. Sayin…

I found your comments about rediscovering Kelly et al interesting. Could you recommend some textbooks that describes what you are referring to? If there are good overviews of the subject?

If you can read and understand bergomi's book you basically understand financial math

Re: The anatomy of an ML-powered stock picking engine

#98

Post by collegeburner »

chollida1 wrote: post #95
HFguy wrote: post #50

Earlier quoted context omitted.

This is actually way too optimistic. Your first 1-2 seed investors will: - Only pay 1 and 10 (1% fixed fee and 10% of PNL) - They will also get ownership of the actual fund management firm and will get that in the form of 20% of REVENUE (not equity, revenue, think about that) This is one reason new fund formation is way down. The economics are bad for years. Know a bunch of HF people that started vc-backed tech firms…

Ha, you need a better network:) I don't know too many people who have started funds in the past 5 years, but of the 3 who did, none gave up any ownership in the management firm. That's a suckers game and the only people who would need to give up any ownership are people who are very green:)

facts, the people i know who started funds in the past few years gave no ownership. they alsp made the numbers work down starting at about $75mm iirc, tho it's a lot easier once past $500mm.

Re: The anatomy of an ML-powered stock picking engine

#99

Post by JSGdev »

muggermuch wrote: post #30
jesuslop wrote: post #23

Nice report. How did you did risk management? Have you been leveraged? Have you paid for data? Kudos for a view from the trenches.

Thank you! >How did you did risk management? I put in a basic position management layer (1% fixed stop). Also, the market regime module would modulate participation, i.e. in really risky environments it would dial down the number of stock picks. I can definitely do much more on this front, but I wanted to nail down the stock picking first! :) >Have you been leveraged? No leverage. >Have you paid for data? Yes, my mon…

what data sources did you use? im interested in working on something similar.

Re: The anatomy of an ML-powered stock picking engine

#100

Post by JSGdev »

darawk wrote: post #80
moeymo1 wrote: post #75

"steadily beating the S&P 500 for over a year on a weekly basis" Can be achieved by chance alone. If not chance, I can give you a strategy that would be highly likely to achieve such a result: it would take a lot of risk though! I love it when people post this stuff to HN. Naive people try it, loose a bundle to market makers, then go back to their day job.

> "steadily beating the S&P 500 for over a year on a weekly basis" If you're going to make a claim like that, you should actually follow up with the calculations. When you do that, you'll realize that the issue is quite a bit more complex than this shallow dismissal. He has very low correlation to the index, which means he's not just levering beta and getting lucky on a trending market. His standard deviation is smal…

usually the answer for a negative strategy is set aside a long period of data for backtesting, right?
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