Executing on a Quantitative Strategy

Hi all,
I'm a new investor who has recently read "DIY Financial Investor" and "Quantitative Value" by Dr. Wesley Gray. I've been really interested in the contents and investing in a quantitative manner, to eliminate human biases.

In now trying to implement them, I am having problems in terms of big data. I live in Canada and would be thus investing in the TSX and am wondering if anybody knows how I could import the excel data for all companies on the market? These strategies require financials like EBIT, market cap, etc. for each stock, and then to sort by percentiles, and am unsure where I could get this data from.

Any help would be appreciated!
Thanks

Comments

  • Hi ngagliano, the CEO of Stockopedia is working in including canadian stocks but he doesn't say when it will be done.
    Stockopedia is great because It allows you to use the strategies of What works on wall street in US and Europe stocks, which are otherwise difficult to implement. I assume that the strategies in Quantitative Value are similar.
    I know It's not a big help but I don't know any other platform to do this.
    Pablo
  • I'll try and offer my 0.02 on the subject from the point of view of american stocks.

    First I'll say that the logistics involved with implementing quantitative value is challenging. You will need 8 years worth of data where currently most data sources offer only 4. You can pay for 10 years worth of data using a service like Morningstar, or Fred. The next step would be collecting the getting the data which involves either (1) using an API, or scraping the web. Both require practical knowledge of a scripting language such as python. An API will have rate limits per month, and web scraping is obviously less reliable.

    Once you have all the data you need in a database ( you'll need a relational database such as mysql), you'll need to figure out how to reliably calculate EBIT, mkt cap and the rest of those. You'll need to filter or index as needed, than sort them as described in the book. Once this is all done you can again use python or whatever database scripts to export as csv or an excel formal file to get what you want.

    I wrote this because I have done part of this implementation and can speak to it being non trivial , but doable. Moreover, I wanted to make sure you understood that neatly formatted historical data in the form you want will not be lying around because I would have found it and already made my models :)

    If you are interested in implementing something like this and have questions, feel free to shoot me a message.

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