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QCU Weather Based Rebalancing

We took NYC temperature weather data imported from an external source and used it as a weighting factor for how much stock we should own. Data is stored on dropbox.

The theory was people are like bears: we hibernate during winter and when its sunny we're optimistic and go longer.

Example of using external data source, which creates custom strongly typed objects for use in your algorithm.
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I think the strategy also goes short for a few weeks during the peak of winter - anything below -5C would be short. Perhaps hypothesis could be updated that below a certain temperature it doesn't matter how cold it is? So it would eliminate the short days.
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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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