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Sentiment and style Rotation strategy Help

Hello,

I tried cloning the Sentiment and style Rotation strategy, it gave quite decent results up until Jan 2018 where there is a huge drop in equity. Could anyone please help me to figure out the cause?

Thanks!

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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.


Hey Prashant,

The massive drop in equity is caused by a buggy trade which occurred on 01-03-2018.

Time: 2018-01-03 00:00:00, Ticker: DISCB, OrderType: Buy Market On Open, FillPrice: $199,999.95 USD, Quantity: 45, Status: Filled

This order for the ticker DISCB fills for 45 shares at $199,999 dollars per share. However, the price of DISCB at that time is $26.20 per share. This causes a massive drop in the value of your portfolio, putting your account into a margin call. We are investigating this issue; for now you can work around this error by reducing the size of your universe. Instead of selecting all equities with fundamental data, you can select the top 1000 most liquid ones.  You can use Universe.Unchanged to signal to your algorithm that no changes need to made to the universe.

def CoarseSelectionFunction(self, coarse):
if self.month_start:
# drop stocks which have no fundamental data or have low price
fundamentals = [x for x in coarse if (x.HasFundamentalData)]
sorted_fundamentals = sorted(fundamentals, key=lambda k: k.DollarVolume, reverse=True)
self.filtered_coarse = [x.Symbol for x in sorted_fundamentals][:1000]
return self.filtered_coarse
else:
return Universe.Unchanged

Best
Rahul

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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.


Update Backtest





0

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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