Dividend Portfolio

Hello,

Yes, you are correct. The FineFundamental data structure is where you can find fundamental data, including dividend information. You can access this data in your algorithm using the Fundamentals property of the Equity objects in your universe. For example:

fundamentals = self.Securities[symbol].Fundamentals

(Source: QuantConnect Documentation)

Regarding the inconsistency in the twelve-month value, it's important to note that these values represent the dividend per share over different periods of time. The twelve-month value is not necessarily the sum of the three, six, and nine-month values. It represents the dividend per share over the past twelve months. The discrepancy could be due to changes in the company's dividend policy, special dividends, or other factors.

As for calculating the historical annual % dividend yield, you would typically divide the annual dividend payment by the stock's price. However, the extracts provided do not contain specific information on how to calculate this in QuantConnect. You might need to use the GetFundamental method to retrieve historical fundamental data and calculate the yield manually. Here's an example of how to use the GetFundamental method:

history = qb.GetFundamental(symbol, "ValuationRatios.PERatio", datetime(2021, 1, 1), datetime(2021, 7, 1))

(Source: QuantConnect Documentation)

Please note that this example retrieves the P/E ratio, not the dividend yield. You would need to replace "ValuationRatios.PERatio" with the appropriate field name for the dividend yield.

I hope this helps! Let me know if you have any other questions.

Hi Mia,

Wow, that's what I call a fast answer, and a good one two. 
I have just a tiny little question left. Can I use the GetFundamental function also in back-testing? What I see in your answer and in the documentation it is used in QuantBooks.

Thanks,
       Markus

Hello,

Unfortunately, the GetFundamental function is currently only available in the Research Environment, not in the backtesting environment. This is mentioned in the QuantConnect Documentation.

However, in the backtesting environment, you can use the FineFundamental objects to access fundamental data. This data is available in the Coarse and Fine selection functions of your algorithm. Here's an example of how to use these functions:

self.AddUniverse(self.SelectCoarse, self.SelectFine)

(Source: QuantConnect Documentation)

For historical fundamental data, one workaround mentioned in a QuantConnect Forum discussion is to use a rolling window to save the fundamental values.

I hope this helps! Let me know if you have any other questions.