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Jane Street Market Prediction ($100k Kaggle competition)

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Re: Jane Street Market Prediction ($100k Kaggle competition)

#191

Post by blovescoffee »

eru wrote: post #169
blovescoffee wrote: post #70

Earlier quoted context omitted.

I've wanted to start learning about this for a while but I'm really not sure where to start. I have a degree in CS and Math so I'm not a total layman wrt the maths. Do you have any suggestions?

I have a book called Empirical Asset Pricing by Wayne Ferson. Seems like as good a place to start as any. If you want something online, check out https://www.quantopian.com/

It looks like I'm a bit too novice for Empirical Asset Pricing. I'll check out the website though, thanks.

Re: Jane Street Market Prediction ($100k Kaggle competition)

#192

Post by blovescoffee »

secondcoming wrote: post #138
blovescoffee wrote: post #70

Earlier quoted context omitted.

I've wanted to start learning about this for a while but I'm really not sure where to start. I have a degree in CS and Math so I'm not a total layman wrt the maths. Do you have any suggestions?

This might be a good starting point. https://www.wiley.com/en-us/Paul+Wilmott+Introduces+Quantita...

Thanks, I'll give it a shot

Re: Jane Street Market Prediction ($100k Kaggle competition)

#193

Post by nojito »

reese_john wrote: post #106
fractionalhare wrote: post #58

Earlier quoted context omitted.

I can see why someone would characterize RenTech that way but it's not really fair to do so. There is a lot of mythos about how Simons hired computer scientists, mathematicians, signal processing and NLP experts, etc. When Mercer came over from IBM, he definitely contributed a significant amount of analytical expertise that was probably nonexistent in financial trading at the time (with the possible exception of the…

How much do you think does their advantage stems from having high quality proprietary/alternative datasets?

Not much if at all.

However, RenTech probably has the cleanest data warehouse of any firm. It was revealed that they have PHDs who do nothing but sort data into databases.

Re: Jane Street Market Prediction ($100k Kaggle competition)

#194

Post by b20000 »

quantumofalpha wrote: post #133
b20000 wrote: post #128

Earlier quoted context omitted.

who cares if they use ocaml or punch cards? i give zero shits about their tech. i care about getting paid properly, having my own office to work quietly and have work/life balance, and generally having no daily drama.

Their pay is top tier, $300-400k+ for new grads.

the question is, what the executives get paid, and what the traders get paid, in comparison to what the engineers get paid, and then also in what conditions you need to work as an engineer.

Re: Jane Street Market Prediction ($100k Kaggle competition)

#195

Post by filoleg »

jpetso wrote: post #152
kgwgk wrote: post #66

Earlier quoted context omitted.

Disclaimer: I have no first hand info. According to https://news.efinancialcareers.com/ch-en/307393/jane-street-... "Last year, Jane Street's graduate hires straight from college were said to be paid a $200k annual base salary, plus a $100k sign-on bonus, plus a $100k-$150k guaranteed performance bonus." According to random people in reddit https://www.reddit.com/r/cscareerquestions/comments/69k0ap/d... "somebody sai…

Am I the only one who thinks "$100k-$150k guaranteed performance bonus" is a weird concept? I get how maybe "bonus" can count as "not salary" by being paid as lump sum. But "guaranteed" and "performance" going together? What's the deal here, even?!

>But "guaranteed" and "performance" going together? What's the deal here, even?!

After interviewing with a bunch of similar finance shops over the past year, I think whoever reported that info omitted one important thing: the "guaranteed" part of "guaranteed performance bonus" applies to the first year of employment only (and it isn't a secret, every single recruiter and hiring manager made that very explicit and clear).

With this context in mind, it makes perfect sense, because you don't know how things work at the new company, you will have lots of learning to do, you are not sure of how performance bonus is structured or what goes into it, you don't know the details of how to affect it in your favor, etc. With that in mind, it makes sense for those companies to reassure candidates that you have a nice headstart by guaranteeing your performance bonus for the first year, to allow you to focus on learning all of the things relevant to your position without having to stress much about the performance bonus.

Re: Jane Street Market Prediction ($100k Kaggle competition)

#196

Post by filoleg »

agravier wrote: post #160
whymauri wrote: post #132

Earlier quoted context omitted.

Jane Street's interview was one of the funnest I've ever done. I failed but the questions were great!

What was so fun about it?

Not the parent comment you are replying to, and I cannot speak for full-time, but when I interviewed for an internship position with JS about 5-6 years ago, the questions were indeed fun.

Problems required knowledge of basic stats, general problem solving, critical thinking/reasoning, and all of it was wrapped in a nice package. Mind you, when I say "general problem solving", I don't mean brain teasers like "how many piano tuners there are in Manhattan" (I don't like that kind of problems at all).

I don't remember the details, but one problem was about estimating the most optimal move in a poker game given a specific situation at the table. The rules were explained in a very relevant and simple way to those not familiar with poker, which I wasn't at the time, and I didn't find that my lack of poker knowledge affected my ability to solve that problem at all (which is already an impressive feat, major credit to those who wrote that specific problem that way).

Zero memory of the rest of the problems, but most of them were relying on just basic stats and reasoning skills/critical thinking, no bs, and they were written/designed in such a way that it was interesting. The kind of a problem you would randomly see online in the middle of some discussion and won't be able to resist the temptation to stay glued to your computer screen until you solve it.

Re: Jane Street Market Prediction ($100k Kaggle competition)

#197

Post by filoleg »

npmisdown wrote: post #79

I'm sorry, if you could build a model to predict markets, why will you post in to Kaggle to get $40k in prize instead of applying this model to your own broker account?

>if you could build a model to predict markets, why will you post in to Kaggle to get $40k in prize instead of applying this model to your own broker account?

Because things aren't that simple. I find this argument very similar to that of devs who complain "I wrote this piece of code that made my company $3mil in revenue over the past year, but I only got paid a fraction of that, i am getting ripped off, oh woe poor me". If you could do that, you would have made it on your own and made that much money already.

Turns out, other people at the company are actually doing tons of work to make it possible to make that much revenue off your code. Same applies here. It isn't just as simple as having one good model at a single point in time to be able to make tons of money off it, there are a lot of other people doing their own work at those finance shops that make it possible for those models to bring in tons of money.

Re: Jane Street Market Prediction ($100k Kaggle competition)

#198

Post by quantumofalpha »

b20000 wrote: post #194
quantumofalpha wrote: post #133

Earlier quoted context omitted.

Their pay is top tier, $300-400k+ for new grads.

the question is, what the executives get paid, and what the traders get paid, in comparison to what the engineers get paid, and then also in what conditions you need to work as an engineer.

It's privately owned - the firm trades the executives' (partners) capital. Wlb depends on the role. As a quant you won't have a life in any firm, as an SWE I heard it's decent for the pay.

Re: Jane Street Market Prediction ($100k Kaggle competition)

#199

Post by quantumofalpha »

blovescoffee wrote: post #70
riazrizvi wrote: post #51

Earlier quoted context omitted.

Mathematical analysis of financial markets is more celebrated when applied to relative valuation of different assets, rather than prediction of the market. Black-scholes, for example, applied calculus with an underlying no-arbitrage assumption to create a thriving market in option pricing, by giving traders a mechanism to reduce risk and thereby reduce bid offer spreads. Same in fixed income, mortgage, and credit mar…

I've wanted to start learning about this for a while but I'm really not sure where to start. I have a degree in CS and Math so I'm not a total layman wrt the maths. Do you have any suggestions?

Eh, don't bother reading any financial literature that other commentators suggest you for this competition. With anonymized input data and even the nature of the problem (is it even short or long term prediction? the two are very different beasts), you're not going to use any financial domain knowledge here. Besides, the good stuff is rarely if ever openly published. Just keep in mind two useful unchanging truths about finance here: it's time series data and with very low signal-to-noise ratio, so overfitting is a major concern.

Start by reading/running notebooks ("kernels") and winners solutions from this and previous competitions with tabular/time series data, building models and then grid searching, stacking, bagging, boosting 'em up. Here's a bit aged but still useful guide how pros do it: https://mlwave.com/kaggle-ensembling-guide/

Re: Jane Street Market Prediction ($100k Kaggle competition)

#200

Post by eru »

blovescoffee wrote: post #191
eru wrote: post #169

Earlier quoted context omitted.

I have a book called Empirical Asset Pricing by Wayne Ferson. Seems like as good a place to start as any. If you want something online, check out https://www.quantopian.com/

It looks like I'm a bit too novice for Empirical Asset Pricing. I'll check out the website though, thanks.

Yeah, I haven't read that book myself yet. Borrowed it from work. But it seems like the Real Deal. So you could just use it as a stepping stone, and just see what basic material the author recommends to work through beforehand. You can usually find these recommendations in the preface or similar.
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