Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

School for quants - Inside UCL's Financial Computing Centre

ft.com

Post reply on HN
Print view View original

11–20 of 31 posts

Re: School for quants - Inside UCL's Financial Computing Centre

#11

Post by mdda »

disgruntledphd2 wrote: post #5

The main idea when you become a quant is that a computer is less prone to pitfalls than a human. Computers and humans are prone to different pitfalls. Humans have far too many biases to count - see for example, the works of Kahneman and Tversky and most of social psychology. Computers, on the other hand come with a whole host of different problems (perhaps because they're made by humans). The essential advantage a hu…

One of the things about financial markets is that large numbers of people are attempting to spot patterns, and eek out a profit from the patterns repeating. People are very good at this - which means that, over time, the number of profitable patterns reduces. Thus, to human eyes, market behaviour becomes noise : just like zip compression reduces a bytestream to being essentially white noise by taking out repetitive sequences.

Computers are just the next step, crunching out the patterns until they are unexploitable (below the threshold of trading costs).

The end result is that markets are a random walk - unless you are at the bleeding edge with faster machines, better latency, lower transaction costs, etc.

Of course, an alternative to this is to do true bottom-up analysis, or invest in illiquid companies (like VCs do).

Re: School for quants - Inside UCL's Financial Computing Centre

#12

Post by comm_it »

elchief wrote: post #10

that's cool and all, but it seems like a waste of talent to learn all that stuff to shuffle money around and occasionally destroy the world economy. it's interesting that it's 80 percent men. it's obviously going to be very lucrative.

In what way is it a waste of talent?

Additionally, how are they occasionally destroying the world's economy?

Re: School for quants - Inside UCL's Financial Computing Centre

#13

Post by marchdown »

mdda wrote: post #11
disgruntledphd2 wrote: post #5

The main idea when you become a quant is that a computer is less prone to pitfalls than a human. Computers and humans are prone to different pitfalls. Humans have far too many biases to count - see for example, the works of Kahneman and Tversky and most of social psychology. Computers, on the other hand come with a whole host of different problems (perhaps because they're made by humans). The essential advantage a hu…

One of the things about financial markets is that large numbers of people are attempting to spot patterns, and eek out a profit from the patterns repeating. People are very good at this - which means that, over time, the number of profitable patterns reduces. Thus, to human eyes, market behaviour becomes noise : just like zip compression reduces a bytestream to being essentially white noise by taking out repetitive s…

This is a strong point, and the one rarely acknowledged at that. Many people stop at pointing out that efficient markets cannot be gamed, and almost all exploitable inefficiencies have been ironed out already. In correctly observing that most investment activities are fueled by greed and human biases, they incorrectly extend this to trading illiquid goods, which still have a lot of low-hanging fruit to pick.

Re: School for quants - Inside UCL's Financial Computing Centre

#15

Post by tikhonj »

chrisaycock wrote: post #6
dustineichler wrote: post #2

I sometimes think HN is trolling me. I just had this conversation about Quants, finance etc. Is there anything like this in NY? I'd go.

You're looking for quant schools in New York? There are tons of those. The most common degree is the Master of Financial Engineering or equivalent. QuantNet maintains a list of the top programs in the US: https://www.quantnet.com/mfe-programs-rankings/ But you should think very carefully about whether starting a new degree like this is worth it. Firstly, you'll notice that the tuition for all of these programs is ver…

While the tuition is very high, a compromise is that the programs are surprisingly short. I know that at Berkeley--which has a fairly good MFE program, I think--the entire program only lasts one year. I think other programs are similar. This might make it more attractive than a cheaper but longer degree for some people.

Re: School for quants - Inside UCL's Financial Computing Centre

#17

Post by radikalus »

comm_it wrote: post #16
hendrix wrote: post #7

I was thinking mining online data to gauge the feeling of the market awhile ago, looks like someone is actually doing it.

Check out http://bullbear.ca/ - it was posted here before and is quite interesting. (I'm not involved with it)

This looks pretty excellent. (Based on my playing with it for 30 seconds)

I'm constantly underwhelmed by Bloomberg and would love to see more players in news aggregation/analysis space in finance.

Re: School for quants - Inside UCL's Financial Computing Centre

#18

Post by radikalus »

mdda wrote: post #11
disgruntledphd2 wrote: post #5

The main idea when you become a quant is that a computer is less prone to pitfalls than a human. Computers and humans are prone to different pitfalls. Humans have far too many biases to count - see for example, the works of Kahneman and Tversky and most of social psychology. Computers, on the other hand come with a whole host of different problems (perhaps because they're made by humans). The essential advantage a hu…

One of the things about financial markets is that large numbers of people are attempting to spot patterns, and eek out a profit from the patterns repeating. People are very good at this - which means that, over time, the number of profitable patterns reduces. Thus, to human eyes, market behaviour becomes noise : just like zip compression reduces a bytestream to being essentially white noise by taking out repetitive s…

One counterpoint is that at the bleeding edge of low-latency, pattern analysis and sig-int become once again extremely meaningful.

Can you execute your strategy faster than your opponents if you go to a slightly more aggressive (less arbitrage-y) signal?

Should you? (Why bother if you're faster?)

For what situations is it worth "thinking longer"? Some straight arbs require speed beyond what you can do if you want to use your HOT "smart" model.

If you work outwards from the fastest "stupidest" trades, there's a vast array of strategies/opportunities that intersect ML/AI, hardware design, network optimization, and so forth -- I do agree that if you're looking at bad, inaccurately sampled tick data, the opportunities aren't really there anymore. (Because there's increasingly more players correcting relative value mispricings)

Re: School for quants - Inside UCL's Financial Computing Centre

#19

Post by comm_it »

radikalus wrote: post #17
comm_it wrote: post #16

Earlier quoted context omitted.

Check out http://bullbear.ca/ - it was posted here before and is quite interesting. (I'm not involved with it)

This looks pretty excellent. (Based on my playing with it for 30 seconds) I'm constantly underwhelmed by Bloomberg and would love to see more players in news aggregation/analysis space in finance.

Yeah it's pretty impressive parsing of natural language to form financial opinions.

The Bloomberg website or Bloomberg terminal? There's a big difference between the sorts of things you can do with those two, but the website leaves a lot to be desired! Google's finance pages are fairly good at aggregation.

Re: School for quants - Inside UCL's Financial Computing Centre

#20

Post by SkyMarshal »

disgruntledphd2 wrote: post #5

The main idea when you become a quant is that a computer is less prone to pitfalls than a human. Computers and humans are prone to different pitfalls. Humans have far too many biases to count - see for example, the works of Kahneman and Tversky and most of social psychology. Computers, on the other hand come with a whole host of different problems (perhaps because they're made by humans). The essential advantage a hu…

> The essential advantage a human has is the eye, which is extremely well adapted to picking out patterns.

I'm not sure that's an advantage. The human eye is so good at discerning patterns that it sees them even where they do not exist. Witness: technical analysis, Eliot Wave Theory, etc.

Quants use math to provide a more rigorous framework for eliminating hocus pocus like that, though they have been known to make less than rigorous assumptions from time to time (good ones like Paul Wilmott have been particularly prescient in calling out that tendancy).

> Nonetheless, i agree with the thesis that this kind of analysis will invade the rest of the social sciences. In fact, that's one of the reasons I learned to program.

Agreed. There's still anachronistic cruft that needs to be exorcised from the field, for example the notion of 'utility' that economists use to evaluate the psychology of decision making (good discussion about that on HN recently, forgot where). CS + X, for (almost) all X, is where the world is heading.

Post reply on HN