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Making Use of Historical Fundamental Data
Neore Qunzb
posted

I was really excited to see that Quantopian now provides access to fundamental data and I would like to start making use of this data as soon as I can - I feel that the opportunities here are endless ...

With that said, I have been trying to figure out if this data can be used to develop market, sector, and industry wide statistics. For example, because of the recent energy slump, stock prices of most companies associated with oil and gas production, exploration, and refinery have dropped significantly. As an investor, I would like to have a tool to measure the impact of the slump on both prices and fundamentals:

  • Can Quantopian be used to measure the impact on stock prices of an even such as the recent oil crisis? In other words, can we develop statistics, such as average price impact, standard deviation, etc. for an entire industry for a given time period?

  • Similarly, can Quantopian be used to develop current and historical fundamental data statistics by industry, sector, etc? In other words, can we develop the average, standard deviation, etc. of such fundamental measures as P/E, Sales Growth, EBTDA etc. for the energy sector and for industries within this sector such as E&P, Refinery etc. both historically and as of most recently?

I should mention that I have yet to code an algorithm within Quantopian but I am a seasoned Python developer (whatever that means) with many years of experience in programming and financial analyis.

1 response
Josh Payne

Neore, so glad you have found Quantopian and are exploring the product.

In short, you can do many of the things you outline today with Quantopian. Within the context of the backtester and IDE, you can use methods like record() and history(). They'll let you record and track calculations you generate within your algorithm. schedule_function() is another useful method to ramp up on, as it will help you make the calculations at the right point in time within a backtest.

Now the backtester is optimized for the purpose of testing out your algorithm without look-ahead bias to emulate trading. We are also working on a more flexible research environment (it is currently in a closed alpha) where we will make it easier to explore your ideas much as you outline above.

In the short term, check out the sample fundamental algo in our documentation: https://www.quantopian.com/help#sample-fundamentals

Thanks,
Josh

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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.