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Show HN: Quantblocks - Backtest your trading strategies

quantblocks.com

11–20 of 87 posts

Re: Show HN: Quantblocks - Backtest your trading strategies

#11
post #8

A cautionary note on backtesting (ie, assessing how trading strategies would have performed over a historical period in time). If an a posteriori probability distribution is a good fit for historical events, it doesn't mean in any way it is going to fit future data points. It may or may not. Hence, use backtesting with care while trading.

Absolutely true, backtesting is not a guarantee of anything. That being said, I can't remember who said that "No model is perfect but some models are useful."

Re: Show HN: Quantblocks - Backtest your trading strategies

#12
post #6

Earlier quoted context omitted.

Why did you choose that over something like Yahoo! Finance or Google?

yeah that caught us out - we found that even though the data is freely available from those sources, you're not allowed to include that data in a commercial app :-(

Oh really? That's interesting - does that apply even if it's not distributed with the commercial app? I'm sure I've used trading platforms before which use Yahoo...

Re: Show HN: Quantblocks - Backtest your trading strategies

#14
post #13

Earlier quoted context omitted.

We're using Xignite's API right now. It's super-simple to integrate with.

How far back does it go?

Xignite allows us to show the full historical data of an instrument, but because we're taking a lean approach at testing how people use it, we're limiting them to a few years.

Re: Show HN: Quantblocks - Backtest your trading strategies

#15
This is fantastic. Love the clean, straightforward interface. However I have a feeling that anyone knowledgeable enough to profit from this is probably already heavily invested in another system for doing these calculations and/or feel the rules system isn't flexible enough. One thing you could do is to implement sharing. ie, have a list of "top performing strategies measured from date of creation". Then let users subscribe to other users' "proven" strategies for a fee - you take half and the author takes half - this could be an alternative way to monetize the site as well attract the kind of people who make a living doing this - ie the kind of people you want talking about your product.

Re: Show HN: Quantblocks - Backtest your trading strategies

#16
post #15

This is fantastic. Love the clean, straightforward interface. However I have a feeling that anyone knowledgeable enough to profit from this is probably already heavily invested in another system for doing these calculations and/or feel the rules system isn't flexible enough. One thing you could do is to implement sharing. ie, have a list of "top performing strategies measured from date of creation". Then let users su…

Thanks for the great feedback. Do you think people would be too protective of their strategies to participate though?

Re: Show HN: Quantblocks - Backtest your trading strategies

#17
post #8

A cautionary note on backtesting (ie, assessing how trading strategies would have performed over a historical period in time). If an a posteriori probability distribution is a good fit for historical events, it doesn't mean in any way it is going to fit future data points. It may or may not. Hence, use backtesting with care while trading.

this is great. love the design, and I can totally see a broker acquiring this so their clients will make more trades on their backtested-to-be-profitable strategies!

Re: Show HN: Quantblocks - Backtest your trading strategies

#18
post #12

Earlier quoted context omitted.

yeah that caught us out - we found that even though the data is freely available from those sources, you're not allowed to include that data in a commercial app :-(

Oh really? That's interesting - does that apply even if it's not distributed with the commercial app? I'm sure I've used trading platforms before which use Yahoo...

Our understanding of the Yahoo/google T&Cs was that we couldn't aim to profit from their data (http://finance.yahoo.com/badges/tos). We may be being overcautious but we didn't want to risk getting into trouble ;-)

Re: Show HN: Quantblocks - Backtest your trading strategies

#19
post #15

This is fantastic. Love the clean, straightforward interface. However I have a feeling that anyone knowledgeable enough to profit from this is probably already heavily invested in another system for doing these calculations and/or feel the rules system isn't flexible enough. One thing you could do is to implement sharing. ie, have a list of "top performing strategies measured from date of creation". Then let users su…

Thanks for the great feedback. Do you think people would be too protective of their strategies to participate though?

You could keep the strategy hidden but allow users to follow the output signals. There are some sites which already do this or similar for both fundamental and technical strategies. Motley Fool comes to mind: http://caps.fool.com/

Re: Show HN: Quantblocks - Backtest your trading strategies

#20
post #15

This is fantastic. Love the clean, straightforward interface. However I have a feeling that anyone knowledgeable enough to profit from this is probably already heavily invested in another system for doing these calculations and/or feel the rules system isn't flexible enough. One thing you could do is to implement sharing. ie, have a list of "top performing strategies measured from date of creation". Then let users su…

Thanks for the great feedback. Do you think people would be too protective of their strategies to participate though?

Possibly. If you integrate with a trading platform you could always let other users subscribe to a strategy without knowing what the strategy is (eg they only know it's gained X% vs the S&P 500 in the last few months, the author's profile and that 5000 other users have 5MM invested in this strategy). However I have a feeling that a) the money from commissions and b) the feeling of being at the top of a list will compel a lot of people to share their strategies - people blog about their stock picks constantly. Also I'd love to see some left-field data about these companies eg: Google search volume, Wikipedia edits/day, mentions on Twitter, press releases, sentiment analysis of news articles etc...
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