Determining the fastest profitable timeframe for a low-frequency intraday algo for a retail trader?

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Determining the fastest profitable timeframe for a low-frequency intraday algo for a retail trader?

posted

I'm trying to come up with a general framework for this. The strategy enters actively meaning via market orders and pays the spread on each order.

Plus side - Average trade statistic of your algo
Minus side - transaction costs which include: bid/ask spread, commission, slippage
Overhead ratio = plus/minus

Then we need to aim for the fastest timeframe that produces a certain "comfortable" overhead ratio? What would be a good minimum ratio?

1 response

Anyone? :)

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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 Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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.