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The Lazy-Ass Strategy, inspired by Christopher Klein

The following algorithm is based on the German Faulbär-Strategie introduced by Christopher Klein, which I roughly translated as "Lazy-Ass-Strategy".  The one rule is ridiculously simple:

Once a year, invest 100% in the ETF with the worst anualized return from a list of country-index ETFs.

The reasons why this strategy might work, are open for discussion. One reason could be some kind of a mean-reversion rule, another one could be administrative interventions such as quantitative easing. 

The one parameter for the simplest version of this strategy is the static universe, which should obviously only contain ETFs of relatively stable countries. Other parameters such as trend filters may be added, to reduce the maximum drawdown. 

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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.


What a fun algorithm! Nice work! I didn't know there were that many country-ETFs! The ETF basket/universe might make a simple universe selection model which we can open source since it is rare to add a new county it has a limited look-ahead bias. 

self.SetUniverseSelection( GlobalETFUniverseSelectionModel() )

 

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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.


I agree, this kind of built-in universe could come in handy in all kinds of algorithms that not only focus on the US market.  

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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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