Kakushadze Model for Overnight Returns

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Kakushadze Model for Overnight Returns

posted Nov 20, 2016

Hello all,

I've been working on some of the ideas proposed by the following paper: https://arxiv.org/pdf/1410.5513.pdf.

Essentially, the author proposes four factors to predict overnight returns. However, a little research and a quick backtest (see attached notebook) seems to show that these factors seem to be generally unpredictive... Even worse, due to the fact that any overnight positions must be exited the next morning, there is an incredibly high turnover, and the transaction costs will swallow up any potential profitability.

I don't see any way to salvage this idea, but I'd be very grateful for any comments or suggestions on where I should go from here. Should this idea be abandoned? Or is this a feasible idea for an algorithm, and if so, how might the factors be improved, and how might the algorithm be implemented?

1 response

you could run it on the time period proposed in the paper. If you get similar results, then perhaps you have competition that has taken this opportunity. If you get different results, perhaps there is an important flaw in your implementation.

The most important issue is the first one you list in the notebook, factors are not predictive. To deal with this, perhaps you can use machine learning on these and other factors to determine relevant factors for the overnight scenario. I'm a 25 year professional data scientist that is trying to do this.

The less important issue is that transaction costs are significant. My ideas include:

perhaps you don't sell securities that are in the first quartile of the next day's overnight hold period, except that this would only be known at the end of the day, not the beginning
perhaps the transaction costs as a percentage of the purchase price could be included in the decision whether to buy
perhaps the sell period could be studied to find a better moment than the open

Please tell me if this is still an area of interest for you.

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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.