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I was wondering if anyone knew the reasoning behind the $1000/month price tag for live data, as it is quite out of reach for the majority of humans. I find it funny that it is FREE to use for backtesting historical data on QuantConnect and Quantopian, so researchers everywhere can find the Alpha but not act on it. Its quite an annoying pricing model, but can we ever expect to see a more reasonable cost for using this data to live trade? I don't need minute data, just EOD data, and I can't see why scraping alone is justification for such a steep price.
Alexandre Catarino
Hi John Hawkins
The reasoning behind that price tag is the value of the information. If the data has predictive power that will result in big third-party profits, it's fair to say that the price tag is reasonable. I think you can compare, for instance, that price tag against those of Alpha Streams.
Please note that PsychSignal sets the price, not QuantConnect.
On the other hand, their backtest data is free since we cannot make money from backtesting and it is PsychSignal's way to advertise their product.
It's free to create a live Alpha Stream with it too.
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Spacetime
AlMoJo ,
Also, if you would like to explore more CBOE data sets, then you can use the Nasdaq Data Link provided below.
Correction in my last post: meant to say CBOE and not Quandl (Quandl was acquired by Nasdaq)
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Spacetime
AlMoJo , Just posting our QC CBOE Datasets link below for your reference if you need it.
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Vladimir
Spacetime,
There are only 6 trades for SHV in your version of the code.
Can you try changing in the code the VIX and VXV data retrieval in a way like in the attached sample.
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Spacetime
Hi Vladimir,
Hmm… not entirely sure why there were only 6 trades executed.
The above backtest which I have attached was taking a “bit” to complete for me and I was engaged with other work, so I ran the above model (shaerd by pangyuteng) with a start date of self.SetStartDate(2020, 11, 1) just to speed up things.
Hmm… I have extended the date range to start from self.SetStartDate(2019, 1, 1) and it does not have too many trades either. (backtest attached)
If you have noticed from the above example shared by pangyuteng , then it does not trade that often either. [ self.SetStartDate(2019, 1, 1) ]
But, the fixes which I have shared above does work as the error which was being received by AlMoJo is no longer occurring.
Hmm… maybe someone else might have a better idea on this, but I will try to look into this further. Hmm… maybe the LSTM configuration needs to be looked into or the volatility data resolution and other resolutions needs to be changed to minute time slice if possible.
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Vladimir
Spacetime,
I backtested cloned pangyuteng algorithm with only changes in my_custom_data
url_vix = "http://cache.quantconnect.com/alternative/cboe/vix.csv"
url_vxv = "http://cache.quantconnect.com/alternative/cboe/vix3m.csv"
It generated 13 SPY-SHY trades and metrics as your last one, but the performance is not comparable to pangyuteng's results.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Spacetime
Vladimir,
Hmm… If you want to compare it with pangyuteng's results, then you have to provide an end date of self.SetEndDate(2020, 1, 1) because pangyuteng's model ends around that time. Please note, pangyuteng's post is time stamped somewhere in December 2019.
Try to run it with end date parameter and check to see if performance is comparable.
I have attached a backtest run starting from self.SetStartDate(2019, 1, 1) and ending at self.SetEndDate(2020, 1, 1) and it only traded once.
Hmm…
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Vladimir
Spacetime,
I definitely like the metrics from your last backtest, but my attempts to reproduce them for some reason were unsuccessful.
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
AlMoJo
Hello everybody,
Pangyuteng this is an amazing result. Jack Simonson I also think technical indicators would help a lot.
I tested Pangyuteng version on the 2022 crash and it is not so good at dodging it. I taught maybe going hourly timeframe instead of daily could help even if I know that trading more frequently is not really good.
Anyone has an idea on how to change the timeframe? I tried to pass all the .Daily to .Hourly but obviously it wasn't that simple.
Kind Regards
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Varad Kabade
Hi AlMoJo,
To change the timeframe of the entire algorithm we recommend adding the following to the Initialize method:
Note that the algorithm uses higher frequency bars to create lower-frequency bars. Therefore to use indicators or consolidators at the hourly resolution we need to have the universe at the minute, seconds, or hourly resolution.
Best,
Varad Kabade
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Will Berger INVESTOR
Hey Guys and Sherry,
Thanks for this incredible thread. So many interesting ideas!
Will
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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