Live data from Hacker News

Jane Street Market Prediction ($100k Kaggle competition)

kaggle.com

141–150 of 217 posts

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

#141
post #88

Earlier quoted context omitted.

Pump in 2020, dump in 2021.

It always makes me laugh when I see people calling a rebound from a crash a “pump”. I usually hear it from people who were too scared to get in low or are short. Be careful of what you allow your cognitive biases to convince you of. It’s the fastest way to lose money.

We are in "greed" territory.

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

#142
post #115

Earlier quoted context omitted.

Maybe or maybe not. You may need to build up your trading infrastructure first, which entails among other things low-latency connectivity to different venues, negotiate good deals with brokers to get low trading fees etc. If it were that simple, all the quants would be working for themselves. Trading is not just about having good prediction. Also if you publish/share your algorithm, people will copy it and it will lo…

"Also if you publish/share your algorithm, people will copy it and it will lose its edge." That's why I list patenting it after getting rich. The quants don't work for themselves because they're number crunchers and need the financial knowledge that the trading/portfolio managers have. Either way, the main reasons they don't work for themselves is risk and access to capital.

IDK who will still buy a patent for the trading algorithm knowing that it's publicly available and probably not so competitive anymore.

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

#143
Late to the game.

https://numer.ai is an entire hedge fund built around an anonymous ML prediction tournament. They solicit predictions, trade them, and reward the best performing ones. IIRC They’ve paid millions in prizes over the last few years.

They also recently introduced Numerai Signals, where they pay for the performance of actual training data. So you can make money providing datasets that perform well.

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

#144

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…

Also, prices aren't stationary. For an equity security, you are predicting the price for a company that is compounding capital over time. You can predict the price for the company at one point, the relative valuation for the company (for example, against peer group) may not change in one year but that company is investing their capital at X% so you get price growth. The reason why relative valuation models are more e…

> Also, prices aren't stationary

I'm not sure about the rest of your comment, but this is mathematically the correct reason why we don't predict absolute price levels.

And the reason why this is mathematically the correct reason is because for a non-stationary process, when you predict into the future, the variance tends to infinity which means taking expectation on any statistical model is useless since the variance is ridiculously wide

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

#145
post #88

Earlier quoted context omitted.

Pump in 2020, dump in 2021.

It always makes me laugh when I see people calling a rebound from a crash a “pump”. I usually hear it from people who were too scared to get in low or are short. Be careful of what you allow your cognitive biases to convince you of. It’s the fastest way to lose money.

Tesla has a P/E ratio of 1100

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

#146
post #86

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?

It is much harder to turn a model into a profitable trading strategy than people realize. Apart from transaction costs, risk management and market impact there are also a lot of small operational details which can make or break your execution. One example I vaguely recall was that the details of how a specific foreign exchange conducted its closing auction could make a substantial difference to a strategy that involv…

Data quality is another real-world problem. There can be typos, deliberate biases, omissions that need to be guesstimated, sudden structural changes (e.g. a stock split event or a change in reporting cycles) etc.

There's also heterogeneous data sources to aggregate and consolidate, each with their own way of measuring things. e.g. You can see how different states and countries are tracking Covid related stats, they all have their own metrics and interpretations. Some even change the way they report overnight. Companies will similarly report their data in different ways.

Data cleansing is its own science and art for this reason, quite separately from developing any algos on it. It's a practical problem that's easy to overlook when you're just looking at ML transformations from input to output data sets.

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

#147
post #101

Earlier quoted context omitted.

Theres actually still money to be made in small scale strategies. Sophisticated funds are running billions. They cant focus on strategies that only work for 100-500k. This is where big returns can be made. Even warren buffet will say, if he was only managing 1 million, he would get 100% a year returns.

That doesn't make sense unless there are very few viable small scale strategies, at which point they'd probably be difficult to identify. Your assertion might have been true before computers were able to help someone manage many strategies simultaneously.

No it makes a ton of sense. 100k is too small to have a researcher focus on full time. His compensation is probably 500k or more. Then add in fees, infra, cost of regulations, etc and small time strategies arent developed. Making money in the market is completely overrated from a difficulty perspective, the hard part is managing billions.

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

#148
post #142

Earlier quoted context omitted.

"Also if you publish/share your algorithm, people will copy it and it will lose its edge." That's why I list patenting it after getting rich. The quants don't work for themselves because they're number crunchers and need the financial knowledge that the trading/portfolio managers have. Either way, the main reasons they don't work for themselves is risk and access to capital.

IDK who will still buy a patent for the trading algorithm knowing that it's publicly available and probably not so competitive anymore.

Example: See USAA licensing Vanguard tax savings technique

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

#149
post #86

Earlier quoted context omitted.

It is much harder to turn a model into a profitable trading strategy than people realize. Apart from transaction costs, risk management and market impact there are also a lot of small operational details which can make or break your execution. One example I vaguely recall was that the details of how a specific foreign exchange conducted its closing auction could make a substantial difference to a strategy that involv…

I believe what you are referring to is the fix. Foreign exchange markets, that I am aware of, do not have closing auctions. I have heard of some quants trading foreign exchange markets, agreeing to trade at the fix with their counter-party, and not realising that traders often manipulate the fix resulting in the quant's strategy appearing not to work. It is almost comical (I worked in finance but not in FX, everyone…

I was half-remembering some story I heard a while ago about the work needed to arbitrage between some US ETF and some securities on a Brazilian exchange, or something to that effect. I don't remember the details, and I'm not even sure that specific example was real, but it stuck out as a great illustration of the complexities involved in executing a strategy vs just coming up with a model.

Nothing foreign-exchange-specific there although, now that you mention it, dealing with different currencies is another problem you can run into with strategies.

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

#150
post #88

Earlier quoted context omitted.

Pump in 2020, dump in 2021.

It always makes me laugh when I see people calling a rebound from a crash a “pump”. I usually hear it from people who were too scared to get in low or are short. Be careful of what you allow your cognitive biases to convince you of. It’s the fastest way to lose money.

RemindMe! 12 months

Buying overpriced loss making investments is the fastest way to lose cash.

Post reply on HN