91–100 of 179 posts
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The problem is that the majority of people are bad, so trusting the majority is a bad idea.
Bad in what sense? Surely that's not correct otherwise I imagine society would be significantly worse than it is today.
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> The idea was supposedly that everyones ideas were valid and hierarchy didn't matter and that everyone should challenge anything no matter who they were in the organisation. On the engineering side, ideally this is how things are done anyway. I've never had a problem digging into the ideas presented by engineers more senior than me, and I've always encouraged junior engineers to question any ideas I present. Everyon…
It's hard to get right, and merely having a culture of openness is not sufficient - it is easy to abuse - intentionally or otherwise. A common theme I see is "X criticizes/scrutinizes Y more often than he does Z because of some bias X has against Y" (could be an implicit bias). Most teams I've been in are incapable of handling such behavior (i.e. recognizing that X is the problem and not Y).
This is true. On the best team I was ever on, the team leader was respected by everyone and he also mediated conflicts. At the same time, he was incredibly open to new ideas and points of view, and would gladly spent days thinking about what people said to him before coming to a conclusion.
On multiple occasions I made proposals that were in direct conflict with what he had proposed, and he took the time to think my ideas over and give thoughtful feedback, and also on many occasions we came to either compromise, or he changed his mind based on the technical evidence presented.
I guess what I'm saying is, if you have someone in the team that everyone looks up to, and who everyone respects both technically and personally, then that one single person can define the culture for the team.
Very funny. If it's true that all the talk of computers and statistical modelling at Bridgewater is bullshit, and it's just a vanilla hedge fund, then it reminds me of the story from The Man Who Solved the Market that Renaissance was founded as a quant fund but none of the algorithms actually worked, so Simons just traded on hunches until D.E Shaw started competing with them years later.
It's really more of a continuum.
Or you could broadly tranche into 4 categories - 1) pure hunches, 2) pure quant ML stuff (I don't know what this signal even means, but computer say number go up), 3) hunches that you validate with data (kind of like the scientific process), and 4) the reverse - quant ML/data that you validate with logic/hunches (computer says number go up, but why would this pattern exist, who is on other side of this, what are the tail risks, etc).
It's interesting. I have seen rating systems work – in the military. They're harsh to some, but in some situations, you have to filter out B and C players to keep the A players alive. I do think transparent systems w/360º peer reviews are better than many others. I wonder what else is out there that might work.
Prediction markets : Have a system where people can make predictions in semi serious fashion in any field, record them with reasoning and probability numbers and match them later on. Atleast this will prove how deeply they know about a field they are interested in. Tagline: Prediction is Intelligence
If you predict that it will rain on Friday, and I predict an alien invasion before Christmas, and both actually happen… Does that mean I was smarter because my event was vastly more unlikely? How would you score these two successful predictions and what possible value could those scores have? Where was intelligence applied here?
A long time ago I was friends with a facilities person at Apple. She told of a peculiar case where she was called in to take care of a problem in one of the conference rooms. Apparently someone had not thought a meeting had gone well. That evening they had returned to the conference room and taken a dump on the table. Message received.
Maybe someone was trying to send a Ray a message with a puddle of pee:)
I worked with Ferrucci in BW. The internals of the employee rating system that preceded him were hilarious. In short: Everyone is encouraged to rate anyone else in a variety of categories, as often as possible. Every rating is public. You know who is rating you, and how they did it. Those ratings are put together to get a score in every category, and can be seen by anyone. It's your Baseball Card. The problem is that…
Tangential to your point but this is actually a solved problem and you only have to run once. You might even recognize the solution [1] [2].
[1]: https://en.wikipedia.org/wiki/PageRank [2]: https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors
Very funny. If it's true that all the talk of computers and statistical modelling at Bridgewater is bullshit, and it's just a vanilla hedge fund, then it reminds me of the story from The Man Who Solved the Market that Renaissance was founded as a quant fund but none of the algorithms actually worked, so Simons just traded on hunches until D.E Shaw started competing with them years later.
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I've seen multiple. The one I like is 'pinks and blues' where you're given two of each - a pink and a blue - and you write out why you think two dudes should get a blue (good) and a bad (pink). If you start accruing a bunch of pinks, there's a problem. It's very simple and probably wouldn't pass muster with an HR department, but it was effective at getting rid of turds.
Can you split the votes as you want among the candidates or does each have to get at least one review? How often do you rate? Do you only rate peers, or new hires? What about superiors? I could not find any reference to this system. As a person below said it recalls https://en.wikipedia.org/wiki/Limited_voting
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Same deal with Bill Gross (“the bond king”). Macro tailwind, a few good compounding successes, and riding that draft for the remainder. They don’t retire, they just graduate to “thought leaders” because what else are you going to do with that much free time and ego. The money no longer matters, all that is left is to chase status. https://www.google.com/search?q=bill+gross+lucky https://www.cnbc.com/video/2013/04/03/…
Yeah that's the thing with investing. Markets change, trades get crowded, data/tech gets commoditized, and strategies stop working. If you do not have a process and evolve, you are roadkill. So some guys who are early, big and right can attract a halo that long outlives its reality. To build some piece of tech you need to have some sort of process, and it is probably replicable to building another piece of tech. It i…
There was a NYT article about Bridgewater and Dalio last week: https://www.nytimes.com/2023/11/01/business/how-does-the-wor... If these articles are right, the picture I'm coming away with is that Dalio had some good strategies that gave him an edge decades ago but now his competitors have caught up and pulled ahead. Apparently Bridgewater no longer has any quantitative edge and it's really just Dalio and a few close…
Dalio is a perfect example of just how much finance has evolved over the last 30-40 years. Risk parity today is a turbo vanilla strategy that every systematic shop can offer and that a master student in fin. eng. can probably build, and yet in like 1990 this was the forefront of systematic investing and got you paid. Bridgewater today is still riding on the fact that they "invented" risk parity.
There are a lot of oft recommended books whenever the topic comes up, but they always border on too theoretical or outright "pop."
I would imagine simply looking at a syllabus from something like Baruch and going through the recommended readings would be a starting point.