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In the past, we presented the QCU Weather Based Rebalancing algorithm as an example of using an external data source. That algorithm tested the theory of weather impact on market sentiment.
What about the impact of weather on agricultural contracts?
We adapted the QCU algorithm, using Corn CFD, instead of SPY and went short when the weather is hotter.
It would be interesting to run a backtest using the weather conditions from the regions where corn is cultivated.
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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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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We did a review on the algorithm posted earlier.
In this new version, the algorithm access weather data directly from Weather Underground. With self-updating data, we can now use this algorithm in live trading. Also, we make it possible to select the weather station location:
// KNYC is NYC Central Park. Find other locations at
// https://www.wunderground.com/history/
AddData<Weather>("KNYC", Resolution.Daily);With this flexibility, traders can easily defined what weather stations give better trading signals.
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Pretty intresting concept! Trading based on the weather.. but if you think about it.. its very logical :D Nice man!
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Hi guys!
Algorithm looks interesting! However, im trying to run it but no trades are being triggered. Any ideas?
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Unfortunately Weather Underground changed its API and we cannot fetch the data as CVS anymore.
We will need to see whether is possible to extract the data from the html code we are getting to create the non-null instance of the custom data.
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Hi Alexandre, thanks for the quick response. Maybe there is an alternative api out there like Weather Underground.
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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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