Market prediction with anonymized feature set, sounds like Numerai: https://numer.ai/
Jane Street Market Prediction ($100k Kaggle competition)
61–70 of 217 posts
Re: Jane Street Market Prediction ($100k Kaggle competition)
#62Any model superior to what Jane Street is running is worth vastly more than the prizes they’re offering. If you prove such a model out, get licensed (SEC, FINRA) and start soliciting to manage assets. Disclaimer: Not investment advice. Not a lawyer, not your fiduciary.
You are ignoring execution, infrastructure and real-market conditions. The model is just one part of the game.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#63As a frequent Kaggler (perhaps too frequent... it's a bit addicting, in a way I'm sure others on HN will understand), I was fairly intrigued to see this one pop up in the competition list a few days ago. Finance shops have tried their hand at Kaggle before, but I think they've normally been out of their domain. e.g. Two Sigma recently did a reinforcement learning game competition. I'd caution the HN crowd not to expe…
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…
This!
>> The problem with predicting absolute levels, is that there is a game theoretic aspect which undermines any mathematical trading strategy as soon as it is public.
I took finance in Business school, coming from doing a lot of statistical analysis in a research lab. I hated my finance professors and there pseudo science. Pricing formulas work great until they don't. The problem is when they don't, they really don't, in a catastrophic way. Read "When Genius Failed." Real traders know this. But some economists and finance professors act like these mathematical models are describing a predictable physical phenomena.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#64Earlier quoted context omitted.
"have no domain expertise in the underlying data. This kind of approach to finance has historically performed poorly" I recently read 'The man who solved the market', about Jim Simons and Renaissance Capital. The way the book tells it, looking for patterns without seeking domain expertise (e.g. ignoring fundamental valuation of equities) is exactly what Renaissance did, and it worked out very well.
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…
Yup.
https://www.rentec.com/Careers.action?computerProgrammer=tru...
They look for programmers with knowledge of Tax and Risk Management.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#65Sine this is a competition, does someone mind explaining the reason for people to publicly post notebooks in the "Notebooks" section? Seems counter-intuitive to provide competitors with free information, unless you are trying to throw them off.
Posting notebooks can get you upvotes, which contribute towards becoming a Kaggle (Grand)Master. It is also a good way to "win" some attention and goodwill, without spending months trying to actually win the competition itself. Publishing Notebooks also helps you improve your coding/presentation skills, for a popular notebook needs to be useful for a wide audience (or fairly competitive).
The best techniques, certainly coming from teams, are hardly ever published as Notebooks. But yes, many winning teams will eventually incorporate some of the information in the Notebooks, if only to hedge against the others doing the same.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#66Earlier quoted context omitted.
I think you are significantly underestimating the cost per hour of jane street employees
I have first party information, two years out of date. Do you have contradictory first party information? Yes/no will be sufficient for me to adjust my priors and I will be grateful.
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 said they got an offer from JS for $150k + $50k/yr "performance"-based bonus"
Both may be true.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#67Earlier 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…
This! >> The problem with predicting absolute levels, is that there is a game theoretic aspect which undermines any mathematical trading strategy as soon as it is public. I took finance in Business school, coming from doing a lot of statistical analysis in a research lab. I hated my finance professors and there pseudo science. Pricing formulas work great until they don't. The problem is when they don't, they really d…
To add to this, unless your model is situated, and can purturb the market, it has no way of knowing what happens when you flex your muscle. I have a friend who did algorithmic trading professionally for a few years, and he said it was amazing to watch the data. Said he could see other bots come along and poke him, trying to look for weaknesses in his algorithm to exploit. I would expect a purely formulaic trader to underperform other traders who can take advantage of others. It’s no different than how you have to win a rhoshambo turnament.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#68Earlier quoted context omitted.
I have first party information, two years out of date. Do you have contradictory first party information? Yes/no will be sufficient for me to adjust my priors and I will be grateful.
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…
Thank you.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#69Isn't it pretty well known in the finance world that using stale public information to predict the market is a fool's errand? Unless you have some kind of specialized non-public data (e.g satellite images of number of cars parked outside parking malls, number of cargo ships moving in and out), trying to predict the market with historical data does worse than "Just give me some monkeys, darts and a dart board".
Using purely historical price data it is harrowingly difficult. There are 130 anonymized features, so that's unlikely to be only price data. It could include information on the order book, correlated assets, fundamentals, vectorized/embedded text, etc.
Besides, I bet you can train monkeys to do (slightly) better than blindfolded random throwing. Even with public data (replace satellite images with Youtube mentions, or number of links moving into a company website) it is very possible to do better than average guessing on quite a lot of assets (especially smaller and newer markets).
Most hedge funds, even with specialized expensive non-public data, are not magical unicorns. Their quants really may just run a gradient boosting machine and leave it at that. Some hedge funds even prefer linear methods, because this lowers risk through lower variance. Such models can be beaten by experienced Kagglers for sure. For one, I did.
Re: Jane Street Market Prediction ($100k Kaggle competition)
#70As a frequent Kaggler (perhaps too frequent... it's a bit addicting, in a way I'm sure others on HN will understand), I was fairly intrigued to see this one pop up in the competition list a few days ago. Finance shops have tried their hand at Kaggle before, but I think they've normally been out of their domain. e.g. Two Sigma recently did a reinforcement learning game competition. I'd caution the HN crowd not to expe…
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?