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The Automatic Dividend Growth Investor

The origins of Ostirion are in fundamental trading. Our past (and modest) successes came in the form of exhaustive fundamental analysis, one of our main inspiration was the dividend growth investor blog. For several years we manually tried to emulate the process of selecting fundamentally "right" stocks, with success, yes, but feeling that a dynamic piece was missing, some agile risk control was missing, some automated evaluation that could prevent our basic emotions from interfering was missing. Our present form is completely quantitative, and in this form this fundamental approach is also valid, and its efficacy is augmented.


Quantconnect´s backtesting and live trading tools allow for the use of fundamental data, and using this data we are going to try to emulate the screening process described in this blog post. We are making some changes, basically we will:


  1. Find the Dividend Champions according to the resources available in this dividend investing page: The Dividend Investing Resources. This list was created originally by David Fish, who passed away in 2018. Lean engine and data available in Quantconnect allows us to calculate our own list of "Dividend Champions", limited to 1998 and forward. We could determine the list algorithmically, in this case, for the sake of simplicity and comparison we will use these predefined Dividend Champions/Contenders lists.

  2. We will screen the companies for PER, forward dividend and payout ratio, discarding PER below 5 and above 20, dividend payment above 2.5% and below 10% and dividend payout ratios above 60% and below 10%.

  3. The surviving companies will be ranked by their z-score in those screening parameters.

  4. We will rebalance every week, maintaining positions in the top 12 companies in our list. 12 is randomly selected (for historical reasons).

Running the backtest from June 1st 2015 for five years yields the following results:


It yields a compounding annual return of 10% with a sharpe ratio during this period of 0.52. Surprisingly, this model is highly uncorrelated to the SPY, with a beta of -0.16. The COVID19 crisis hits very hard this strategy, it has not recovered from this event as it did from the 2016, 2018 and 2019 corrections. The positions that the model enters are well known companies for dividend investors:


CTBI, ORI (with a somewhat unstable web page), ADM, TGT, WEYS, EV and WMT generate a large proportion of the buy signals, indicating that these companies stay in the portfolio for long periods of time. This is a curious group, large supermarket chains, medium financial and insurance, small shoe company. In general the mean portfolio stays diversified across industries, leaning toward a concentration in financials.


When compared to the SPY index: the returns for this period were 97% with a sharpe ratio of 0.8, 14.7% annual returns. These are June 2015 to August 2020 values. For this period the dividend champion strategy has underperformed the index.


This last year the behaviour is this so far into 2020:

SPY has produced 8.72% returns year to date, dividend champions are underperforming also this year. We will not venture any hypothesis as to why at this point. These are the Dividend Champions for the 2020 portfolio that underperforms, where there could be too many financial institutions:


Chasing the screened Dividend Champions is, as we implemented the strategy, underperforming when compared to just holding the SPY index fund. It is nonetheless a strategy that makes sense, these dividend paying companies are the "true" companies in the strict stock-dividend sense and we may be living in a highly speculative decade. Other factors may apply, tax considerations for example, that may make this strategy appealing.


This are the backtest and the algorithm for the model in this post:



Remember that publications from Ostirion.net are not financial advice. Ostirion.net does not hold any positions on any of the mentioned instruments at the time of publication. If you need further information, asset management support, automated trading strategy development or tactical strategy deployment you can contact us here.

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