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The anatomy of an ML-powered stock picking engine

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

#21

Post by adamsmith143 »

muggermuch wrote: post #7
igorkraw wrote: post #4

Nice writeup, thank you for sharing so openly! The three things I always want to know from stock picking ML people: 1. Did you put your own money in it ? 2. How'd it go? 3. How well does your engine do vs a fixed stock allocation based on trend-statistics computed on the whole time window (i.e., compared to a fixed optimal portfolio computed with mean/std values you don't have access to, but which isn't allowed to ch…

Thank you for appreciating the article; I tried to disclose all that I could! 1. Yes, I did put my own money in it (low 6 figures). 2. It went as described in the article - for the capital I allocated to Didact, I beat the market (SPY) by ~20% since inception. 3. If I understand your question correctly, this would be the equivalent of the payoff on an optimal lookback option ( https://en.wikipedia.org/wiki/Lookback_o…

>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.

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

#22

Post by [deleted] »

adamsmith143 wrote: post #21
muggermuch wrote: post #7

Earlier quoted context omitted.

Thank you for appreciating the article; I tried to disclose all that I could! 1. Yes, I did put my own money in it (low 6 figures). 2. It went as described in the article - for the capital I allocated to Didact, I beat the market (SPY) by ~20% since inception. 3. If I understand your question correctly, this would be the equivalent of the payoff on an optimal lookback option ( https://en.wikipedia.org/wiki/Lookback_o…

>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.

[deleted]

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

#24

Post by muggermuch »

adamsmith143 wrote: post #21
muggermuch wrote: post #7

Earlier quoted context omitted.

Thank you for appreciating the article; I tried to disclose all that I could! 1. Yes, I did put my own money in it (low 6 figures). 2. It went as described in the article - for the capital I allocated to Didact, I beat the market (SPY) by ~20% since inception. 3. If I understand your question correctly, this would be the equivalent of the payoff on an optimal lookback option ( https://en.wikipedia.org/wiki/Lookback_o…

>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.

>You should be running a multi-billion $ Quant fund if this is the case.

You seem to underestimate the level of effort and rigor required to achieve this level of capital allocation. In contrast, beating the market by 20% is table stakes. Folks in the industry do it all the time; the difference here simply is that I built an ML-powered engine to do it systematically.

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

#25

Post by shadycuz »

muggermuch wrote: post #20
xapata wrote: post #15

Earlier quoted context omitted.

If you're sitting on a gold mine, you can wait 5 years. This does not make sense.

Indeed. I haven't shut down development, just shut down the newsletter. I'm continuing to work on it.

I'm a self proclaimed world class DevOps engineer. Can I help contribute in order to get access to the model?

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

#26

Post by muggermuch »

shadycuz wrote: post #25
muggermuch wrote: post #20

Earlier quoted context omitted.

Indeed. I haven't shut down development, just shut down the newsletter. I'm continuing to work on it.

I'm a self proclaimed world class DevOps engineer. Can I help contribute in order to get access to the model?

:) hmu on LinkedIn!

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

#27

Post by colinmhayes »

adamsmith143 wrote: post #21
muggermuch wrote: post #7

Earlier quoted context omitted.

Thank you for appreciating the article; I tried to disclose all that I could! 1. Yes, I did put my own money in it (low 6 figures). 2. It went as described in the article - for the capital I allocated to Didact, I beat the market (SPY) by ~20% since inception. 3. If I understand your question correctly, this would be the equivalent of the payoff on an optimal lookback option ( https://en.wikipedia.org/wiki/Lookback_o…

>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.

Starting a hedge fund is a lot harder than beating the market by 20%.

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

#28

Post by dennisy »

muggermuch wrote: post #2

Hi, 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 crypto?

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

#29

Post by [deleted] »

xapata wrote: post #15
muggermuch wrote: post #8

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.

[deleted]

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

#30

Post by muggermuch »

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 monthly running costs for data are ~$1.2k.

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