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Hi All,
I'm currently using option chain provider to add specific contract into the universe. However, I don't know how to fetch the Greeks using this method, there seems to be no documentation on that. Does anyone have any idea?
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Hi,
I have written an example that can be used as a starting point.
The basic components are:
- Define a security initializer to set and warm up the underlying volatility model or set the option model
- Call OptionChainProvider.GetOptionContractList and filter down the list in OnSecuritiesChanged. I created a separate method, CoarseContractSelection, because one may want to use it multiple times if the underlying prices move “too much”.
- Check out that the Delta is not zero in OnData. It might be zero for some contracts by definition, since Delta measures how much an option's price can be expected to move for every $1 change in the price of the underlying security or index.
Best regards,
Alex
P.S.: I am using a universe of top 3 dollar volume, and the filter/selector gets about 50 contracts, so the algorithm is running about 150 securities, thus it's not fast.
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Cole S
Hi There,
You need to set the Price Model and also warm up the algorithm long enough for the Greeks to get calclulated. Here's a thread that discusses:
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Urnotdhc
Hi,
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.
Urnotdhc
Hi Alex,
Thank you for the sample, this is really helpful.
Best,
Urnotdhc
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.
Shile Wen
Hi .ekz.,
Users interested in metrics not supported by web QC can save the portfolio values and do custom calculations in OnEndOfAlgorithm and print the results or retrieve the results of the algorithm as shown in this post.
I've shown how to the former method in the attached backtest.
Best,
Shile Wen
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.
Jake Sehnert
Is the PSR calculated using CSCV?
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.
Abhijeet Mulye
Longer duration backtests have higher PSRs. Is there a standardized time period for making sure an alpha has >= 80% PSR before submitting?
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.
Derek Melchin
Hi Jake,
No cross validation is used in the calculation. The formula is available in the notebook at the top of this thread. Implemented in Python, it is:
def get_psr(self, benchmark = 0): skew = sps.skew(self.returns) kurtosis = sps.kurtosis(self.returns) n = len(self.returns) estimate_std = np.sqrt( (1 - (skew*self.sharpe_ratio) + ((kurtosis-1)/4)*self.sharpe_ratio) / (n - 1) ) return round(sps.norm.cdf((self.sharpe_ratio - benchmark)/estimate_std),3)Best,
Derek Melchin
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.
Derek Melchin
Hi Abhijeet,
When submitting an alpha for Alpha Streams, the strategy must be backtest over the most recent 5 years. Refer to our documentation here.
Best,
Derek Melchin
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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