4 ms·

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

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?

homie 6y ago
Mostly because it’s impossible to accurately predict the market - and this is just a competition to see who can build the best model.
- thegjp210 6y ago
  HFT firms aren't trying to predict "the market" as a whole - just small eddies of it. A typical example of this is arbing names at the bottom of index fund rebalances. Speed is important mostly to make sure someone else doesn't hit the arb first.
tikhonj 6y ago
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 involved executing there alongside other trading venues. The payoff for getting these operational details right or wrong is massively asymmetrical. If you get everything right, you'll only do as well as your model lets you. But if you get anything wrong, you run a real chance of losing far more money than you could have hoped to make! Even just validating your strategy on historical data (ie back-testing) is harder than it sounds. If you make a mistake that leaks information to the code you're testing, you can end up with a much rosier return and risk profile than you really have. Another way to lose money when you go put your model into action. If you get over these challenges and run your strategy successfully for a while, other market participants are going to start adjusting against it and you have to adjust in turn. You can't just "set and forget". I should note that I am far from an expert on any of this, though! I just know enough to not trade with serious money—my real savings are all in index funds I don't touch, thank you very much :).
- hogFeast 6y ago
  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 knew this was going on for decades before the SEC starting fining people) that someone who managed money was making this error. You are 100% correct about all the other stuff. Lots of issues with "production"...that is why financial firms employ traders/risk people/etc. Most people who trade themselves tend to go for lower-frequency strategies that they can implement personally. I actually don't think there are huge barriers, smaller investors have a huge advantage (when you trade at scale, the market moves against you) but you have to work with what you have and realise that you will get crushed if you try to replicate what someone with more money is doing. Also, data. Data is expensive, and a huge fixed cost.
  - nstj 6y ago
    A “foreign exchange” not “foreign exchange market”
    - hogFeast 6y ago
      Ah, same principle. I have heard of many similar stories.
  - tikhonj 6y ago
    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.
- ben_w 6y ago
madrafi 6y ago
well because quant trading isn't about import xgboost, you need a sustainable infra to handle api failovers, bad data... not even going to mention risk management which is 50% of what quant trading is about. the data provided is anonymized but would probably be a mix of laggard measurements (moving averages, rsi...) and maybe some flow data... quant trading isn't really about finding "secret stuff" most profitable strats you can deploy can be based on stat-arb, basis trading or even just delta-neutral funding farming and such
mbesto 6y ago
It's a good question. The basic answer is not everyone has capital and risk, but they may have the time and intellect.
kolbe 6y ago
This competition doesn’t predict markets. It’s a manufactured game to resemble things JS does. And even if it were an accurate representation, the competition is run on 128 unknown features that you would have to discover for yourself. And trust me, >90% of the work is identifying the features.
logicchains 6y ago
I'd be surprised if the data Jane Street provides isn't some form of high-frequency tick data. It's relatively easy to make accurate short-term predictions with such data, the challenge is being fast enough that behemoths like Jump and Citadel don't get all the good trades before you, leaving you with just the bad predictions. This requires a huge investment in infrastructure and connectivity, beyond the reach of individuals who aren't already quite wealthy.
filoleg 6y ago
>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.

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?

homie 6y ago

Mostly because it’s impossible to accurately predict the market - and this is just a competition to see who can build the best model.

thegjp210 6y ago
HFT firms aren't trying to predict "the market" as a whole - just small eddies of it. A typical example of this is arbing names at the bottom of index fund rebalances. Speed is important mostly to make sure someone else doesn't hit the arb first.

tikhonj 6y ago

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 involved executing there alongside other trading venues. The payoff for getting these operational details right or wrong is massively asymmetrical. If you get everything right, you'll only do as well as your model lets you. But if you get anything wrong, you run a real chance of losing far more money than you could have hoped to make! Even just validating your strategy on historical data (ie back-testing) is harder than it sounds. If you make a mistake that leaks information to the code you're testing, you can end up with a much rosier return and risk profile than you really have. Another way to lose money when you go put your model into action. If you get over these challenges and run your strategy successfully for a while, other market participants are going to start adjusting against it and you have to adjust in turn. You can't just "set and forget". I should note that I am far from an expert on any of this, though! I just know enough to not trade with serious money—my real savings are all in index funds I don't touch, thank you very much :).

hogFeast 6y ago
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 knew this was going on for decades before the SEC starting fining people) that someone who managed money was making this error. You are 100% correct about all the other stuff. Lots of issues with "production"...that is why financial firms employ traders/risk people/etc. Most people who trade themselves tend to go for lower-frequency strategies that they can implement personally. I actually don't think there are huge barriers, smaller investors have a huge advantage (when you trade at scale, the market moves against you) but you have to work with what you have and realise that you will get crushed if you try to replicate what someone with more money is doing. Also, data. Data is expensive, and a huge fixed cost.
- nstj 6y ago
  A “foreign exchange” not “foreign exchange market”
  - hogFeast 6y ago
    Ah, same principle. I have heard of many similar stories.
- tikhonj 6y ago
  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.
ben_w 6y ago

madrafi 6y ago

well because quant trading isn't about import xgboost, you need a sustainable infra to handle api failovers, bad data... not even going to mention risk management which is 50% of what quant trading is about. the data provided is anonymized but would probably be a mix of laggard measurements (moving averages, rsi...) and maybe some flow data... quant trading isn't really about finding "secret stuff" most profitable strats you can deploy can be based on stat-arb, basis trading or even just delta-neutral funding farming and such

mbesto 6y ago

It's a good question. The basic answer is not everyone has capital and risk, but they may have the time and intellect.

kolbe 6y ago

This competition doesn’t predict markets. It’s a manufactured game to resemble things JS does. And even if it were an accurate representation, the competition is run on 128 unknown features that you would have to discover for yourself. And trust me, >90% of the work is identifying the features.

logicchains 6y ago

I'd be surprised if the data Jane Street provides isn't some form of high-frequency tick data. It's relatively easy to make accurate short-term predictions with such data, the challenge is being fast enough that behemoths like Jump and Citadel don't get all the good trades before you, leaving you with just the bad predictions. This requires a huge investment in infrastructure and connectivity, beyond the reach of individuals who aren't already quite wealthy.

filoleg 6y ago

>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.