6 ms·

This is full of gems ; and a great compendium I wish I had 10 years ago. However, honest advise: if you actually really want to trade in this way, start with a

This is full of gems ; and a great compendium I wish I had 10 years ago. However, honest advise: if you actually really want to trade in this way, start with a solid course in mathematical finance. It’ll teach you how to model the space, think about arbitrage, portfolios, risk, factors and the sheer important of theory and hypothesis in real strategy. Building a backtester is exceptionally hard to do if you include scenario analysis, slippage, event risk, lag, multi hypothesis testing, data snooping, etc. Testing is a huge source of competitive advantage. In summary, if you’re starting out, go learn the basics like the back of your hand, and he basics are mathematical finance.

logicchains 8y ago
I work in HFT, and I'll be contrary and suggest that if you want the most value from your time, focus on learning as much maths and probability as possible. Once you have a strong maths background, learning most financial maths is relatively easy. Any of the financial models you find in textbooks are probably useless because if they work, everybody else who's read the textbook has also used them so there's unlikely to be any edge left, hence it's the ideas underneath them that matter, and understanding and extending these is much easier with a strong maths background. The key skill is developing and assessing new models, and the better one's maths, the easier this is (imagine if a market behaved like a complex aerodynamic system; only somebody with enough mathematical background to model a complex aerodynamic system would be able to create a very accurate model of that market). One of the most successful hedge funds, Renaissance Technologies, also takes this approach. Regarding its employees: "a third have PhDs, not in finance, but in fields like physics, mathematics and statistics. Renaissance has been called “the best physics and mathematics department in the world” and, according to Weatherall, “avoids hiring anyone with even the slightest whiff of Wall Street bona fides." (https://en.wikipedia.org/wiki/Renaissance_Technologies https://en.wikipedia.org/wiki/Renaissance_Technologies). Similarly some of the best HFT hires I've been have been people with a maths or science background. A quote sourced to Renaissance Technologies from https://www.quora.com/What-is-the-secret-behind-Renaissance-Technologies-Can-mathematics-really-be-used-to-bring-high-returns-to-investors/answer/Vladimir-Novakovski https://www.quora.com/What-is-the-secret-behind-Renaissance-...: "We have some Tier One mathematicians and a lot of Tier Two mathematicians. Other quants funds have mostly Tier Three mathematicians, and worse, they don’t even know that these tiers exist! Someone has to create the correlations in the markets." Aim to be one of those Tier one mathematicians!
- tudelo 8y ago
  How would you even become a 'Tier One' mathematician? What does that entail?
  - logicchains 8y ago
    I suppose work hard on learning, deeply understanding and practicing as much math as possible, and trying to make novel discoveries / models. I'm certainly not a Tier One mathematician, so I'm probably not the best person to ask. Maybe it requires people to be born with some innate ability, although I'd certainly like to hope it doesn't. Regardless of whether it's actually achievable or not, however, it's definitely a worthy goal to strive towards if you want to be a good quant/trader (and a very intellectually stimulating one). A nice post on the topic by someone who most certainly is a Tier One mathematician: https://terrytao.wordpress.com/career-advice/does-one-have-to-be-a-genius-to-do-maths/ https://terrytao.wordpress.com/career-advice/does-one-have-t....
    - usgroup 8y ago
      Remember reading an article by an ex rentech guy who says that linear regression is about as complex as the modelling gets; that the edge is not in making things hard.
      - XnoiVeX 8y ago
        Deep neural nets approximate polynomial regression. That's probably the limit now.
        darksaints 8y ago
        The finance industry loves deep neural networks because it provides them a way to extract money from all of the naive tech engineers who took a deep learning class on Coursera and thought they could apply neural networks to trading. The general consensus is that deep learning for general trading purposes is complete bullshit because it unavoidably overfits. There are some quality uses for NN, but price or volatility prediction is not one of them.
kunjank 8y ago
Do you have recommendations on good Mathematical Finance books? I have a background on maths and engineering. Thank you.
- usgroup 8y ago
  As a textbook, I suggest Investment Science by Leunberger. It's concise and has great coverage, and you can just keep referencing it over time. As an initial focus, I suggest understanding discrete time models well. If you've got some LA and calculus then I'd suggest just hoping into Introduction to Mathematical Finance by Pliska. It's concise, zero filler, but really clear.
orojackson 8y ago
Or a more tongue-in-cheek answer: if you're starting out, just pour money into ITOT, SCHB, or VTI and call it a day =P In all seriousness, though, it's crazy that we're at a point where these hyperactive algorithms can perform price discovery fairly decently.

logicchains 8y ago

I work in HFT, and I'll be contrary and suggest that if you want the most value from your time, focus on learning as much maths and probability as possible. Once you have a strong maths background, learning most financial maths is relatively easy. Any of the financial models you find in textbooks are probably useless because if they work, everybody else who's read the textbook has also used them so there's unlikely to be any edge left, hence it's the ideas underneath them that matter, and understanding and extending these is much easier with a strong maths background. The key skill is developing and assessing new models, and the better one's maths, the easier this is (imagine if a market behaved like a complex aerodynamic system; only somebody with enough mathematical background to model a complex aerodynamic system would be able to create a very accurate model of that market). One of the most successful hedge funds, Renaissance Technologies, also takes this approach. Regarding its employees: "a third have PhDs, not in finance, but in fields like physics, mathematics and statistics. Renaissance has been called “the best physics and mathematics department in the world” and, according to Weatherall, “avoids hiring anyone with even the slightest whiff of Wall Street bona fides." (https://en.wikipedia.org/wiki/Renaissance_Technologies https://en.wikipedia.org/wiki/Renaissance_Technologies). Similarly some of the best HFT hires I've been have been people with a maths or science background. A quote sourced to Renaissance Technologies from https://www.quora.com/What-is-the-secret-behind-Renaissance-Technologies-Can-mathematics-really-be-used-to-bring-high-returns-to-investors/answer/Vladimir-Novakovski https://www.quora.com/What-is-the-secret-behind-Renaissance-...: "We have some Tier One mathematicians and a lot of Tier Two mathematicians. Other quants funds have mostly Tier Three mathematicians, and worse, they don’t even know that these tiers exist! Someone has to create the correlations in the markets." Aim to be one of those Tier one mathematicians!

tudelo 8y ago
How would you even become a 'Tier One' mathematician? What does that entail?
- logicchains 8y ago
  I suppose work hard on learning, deeply understanding and practicing as much math as possible, and trying to make novel discoveries / models. I'm certainly not a Tier One mathematician, so I'm probably not the best person to ask. Maybe it requires people to be born with some innate ability, although I'd certainly like to hope it doesn't. Regardless of whether it's actually achievable or not, however, it's definitely a worthy goal to strive towards if you want to be a good quant/trader (and a very intellectually stimulating one). A nice post on the topic by someone who most certainly is a Tier One mathematician: https://terrytao.wordpress.com/career-advice/does-one-have-to-be-a-genius-to-do-maths/ https://terrytao.wordpress.com/career-advice/does-one-have-t....
  - usgroup 8y ago
    Remember reading an article by an ex rentech guy who says that linear regression is about as complex as the modelling gets; that the edge is not in making things hard.
    - XnoiVeX 8y ago
      Deep neural nets approximate polynomial regression. That's probably the limit now.
      - darksaints 8y ago
        The finance industry loves deep neural networks because it provides them a way to extract money from all of the naive tech engineers who took a deep learning class on Coursera and thought they could apply neural networks to trading. The general consensus is that deep learning for general trading purposes is complete bullshit because it unavoidably overfits. There are some quality uses for NN, but price or volatility prediction is not one of them.

kunjank 8y ago

Do you have recommendations on good Mathematical Finance books? I have a background on maths and engineering. Thank you.

usgroup 8y ago
As a textbook, I suggest Investment Science by Leunberger. It's concise and has great coverage, and you can just keep referencing it over time. As an initial focus, I suggest understanding discrete time models well. If you've got some LA and calculus then I'd suggest just hoping into Introduction to Mathematical Finance by Pliska. It's concise, zero filler, but really clear.

orojackson 8y ago

Or a more tongue-in-cheek answer: if you're starting out, just pour money into ITOT, SCHB, or VTI and call it a day =P In all seriousness, though, it's crazy that we're at a point where these hyperactive algorithms can perform price discovery fairly decently.