Hi there,
Is there somewhere to find out how all of the statistics are calculated? For example, I would like to know if the beta calculated is a percentage or is the real figure. So if the beta reads 25, does that mean the beta is 25 or 0.25?
Is there somewhere that I can find out how all of the results are calculated?
Thanks for any help.
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Hi Alex,
The beta is calculated here:
I'm not sure exactly what you mean by your question. If the beta is 0.25, it means your strategy experienced only 25% of the volatility of the benchmark over that period.
Hi Douglas,
I am confused because I am getting a Beta of approximately 20, this doesn't seem realistic to me. Maybe I am wrong
I initially though that the beta of 20 implied 20%. Would this be correct?
The benchmark its comparing to is a straight line of constant return.
SetBenchmark("SPY") will give you the beta with S&P500.
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.
Hi, Jared Broad
How would I implement this? Is it in initialise? self.SetBenchmark("SPY"), I am still getting the same beta value with or without the benchmark on the results panel.
Hi Alex.
The value of the regression coefficient, Beta, is dependent upon time-period and data resolution and of course, the selection of benchmark asset. A short time-period combined with high-resolution data, such as tick resolution, can produce an extreme beta value.
Try increasing the backtest period, using daily data resolution, to get a 'realistic' value for Beta. For example, in the attached backtest, the Beta coefficient is 1.161, between QQQ and SPY.
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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