Completely self-interest -- their work is slowly creeping up the curve to take the jobs of fundamental folks. Current 'quant' will likely never take over jobs of those investing beyond a 1yr< time horizon, that's more AGI-type stuff (which is a lot different and not around today) but eh, gives me something to hate on
Great man, but in all honesty the book was a massive disappointment. Tells you zero about how they made money or even what quant investing is half about. It's largely a superficial book on how he built the team.
I 100% see your point. It is largely a book about Jim Simons’ life, and as you mention, building the team. I think it showed that Simons’ strenght was having acess to the best people, and creating an environment where they could thrive. I read it when I only vaguely knew the concept of quantitative investing, so for me, it really sparked my initial interest in the field. I can see how it would be uninteresting for someone who knows the field well, and was expecting to learn something new.
Having said that, there are several great discussion on r/quant about the differences between RenTech and other «quant» firms. I’m sure this is not news to you given your position, but I’ll try to summarize for anyone interested.
Reoccuring theme is that RenTech is leagues ahead in terms of obtaining and cleaning data, which allows them to feed models data that might not have any intuitive link to whatever they are trying to predict. This also lines up with the guy (can’t remember his name) mentioned in the book — one of the first employees who became obsessed with gathering and cleaning data. More traditional quant firms will have “alt data”, but they always have a very intuitive link to a market/asset (cc data, weather data, satellite images, etc..), so the interpretation of the data is basically done by human reasoning. RenTech is more focused on giving models good data, without any filtering in terms of relevance, and then deploying any statistically significant strategy without trying to understand the inefficiencies.
(take all of this^ with a grain of salt, as I really don’t know shit)
The point of the book is that the secret sauce is the team he built and the culture he helped cultivate.. there aren't any top secret signals or fomulas in this industry it's all about doing the simple things really well. There was a podcast with one of the senior guys at RenTec and he was asked something along the lines of does anyone use any complex PhD level math or statistics and he responded that the main tool they use are simple linear regressions - one variable against another. The rigorous hiring process ensures that the researchers are using the simple tool extremely well, understand its limitations and don't make mistakes. You'd be surprised at how many masters and PhDs don't understand the basics...
Also very curious. Personally know of someone who went to RenTech and he was an NLP researcher. Not sure if he was using NLP for the markets when he actually got there though
They collect all data they can find, pretty much anything you can think of might be of some use
Mostly stat arb, so basically mean reversion. They make up about 1.4% of Nasdaq's daily trading volume according to a recent article, there were times they made up to 10% of daily trading volume
They buy options to hedge against a black swan event from banks so that they don't blow up
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RIP to the GOAT
damn, who could have predicted this (no pun intended). Huge inspiration towards quant finance
While I despise quants in general, this guy is the single greatest money manager in history given returns and duration of those returns
To those who MS this guy, who would you suggest is better?
Buffett is better on a MOIC basis, Simon is better on an IRR basis
Why do you despise quants?
Completely self-interest -- their work is slowly creeping up the curve to take the jobs of fundamental folks. Current 'quant' will likely never take over jobs of those investing beyond a 1yr< time horizon, that's more AGI-type stuff (which is a lot different and not around today) but eh, gives me something to hate on
Wow. RIP, the GOAT
RIP Jim
F
"I did a lot of math. I made a lot of money, and I gave almost all of it away. That's the story of my life."
RIP to the greatest to ever do it. Really recommend the book on him for anyone interested in his life and work.
Great man, but in all honesty the book was a massive disappointment. Tells you zero about how they made money or even what quant investing is half about. It's largely a superficial book on how he built the team.
I 100% see your point. It is largely a book about Jim Simons’ life, and as you mention, building the team. I think it showed that Simons’ strenght was having acess to the best people, and creating an environment where they could thrive. I read it when I only vaguely knew the concept of quantitative investing, so for me, it really sparked my initial interest in the field. I can see how it would be uninteresting for someone who knows the field well, and was expecting to learn something new.
Having said that, there are several great discussion on r/quant about the differences between RenTech and other «quant» firms. I’m sure this is not news to you given your position, but I’ll try to summarize for anyone interested.
Reoccuring theme is that RenTech is leagues ahead in terms of obtaining and cleaning data, which allows them to feed models data that might not have any intuitive link to whatever they are trying to predict. This also lines up with the guy (can’t remember his name) mentioned in the book — one of the first employees who became obsessed with gathering and cleaning data. More traditional quant firms will have “alt data”, but they always have a very intuitive link to a market/asset (cc data, weather data, satellite images, etc..), so the interpretation of the data is basically done by human reasoning. RenTech is more focused on giving models good data, without any filtering in terms of relevance, and then deploying any statistically significant strategy without trying to understand the inefficiencies.
(take all of this^ with a grain of salt, as I really don’t know shit)
The team building part was incredibly interesting imo. Who do you think builds the company? :-)
The point of the book is that the secret sauce is the team he built and the culture he helped cultivate.. there aren't any top secret signals or fomulas in this industry it's all about doing the simple things really well. There was a podcast with one of the senior guys at RenTec and he was asked something along the lines of does anyone use any complex PhD level math or statistics and he responded that the main tool they use are simple linear regressions - one variable against another. The rigorous hiring process ensures that the researchers are using the simple tool extremely well, understand its limitations and don't make mistakes. You'd be surprised at how many masters and PhDs don't understand the basics...
Anyone have an example type of inefficiency / alpha (in equities) they would exploit (even if it doesn’t work today), just curious of the types
Also very curious. Personally know of someone who went to RenTech and he was an NLP researcher. Not sure if he was using NLP for the markets when he actually got there though
They collect all data they can find, pretty much anything you can think of might be of some use
Mostly stat arb, so basically mean reversion. They make up about 1.4% of Nasdaq's daily trading volume according to a recent article, there were times they made up to 10% of daily trading volume
They buy options to hedge against a black swan event from banks so that they don't blow up
RIP to the genius that solved the market.
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Dolor saepe sit eos rerum. Hic officiis quo iusto saepe laudantium laboriosam accusamus. Eum numquam cum inventore officiis quia. Iusto omnis deserunt distinctio nam ex aut sunt repellat. Voluptatibus ut iste nostrum minima quaerat est.
Omnis est reprehenderit quisquam quo. Et earum qui voluptate magnam assumenda. Suscipit sit culpa est vel quae. Eos laudantium tenetur ratione. Hic quia labore ex ad dicta. Maiores magni sit autem nostrum minus totam placeat. Amet explicabo nihil vitae voluptate minima nam. Autem aut consequatur beatae fuga et est cupiditate.
Ex assumenda repellat molestiae quibusdam quia enim. Suscipit maiores tenetur delectus quo similique. Non aspernatur quia dolor vero. Quo magni laborum consequatur earum. Similique mollitia velit nihil.
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