The UK Payout Strategy

We show off a lucrative investment strategy focusing on UK dividend-generating stocks

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Written by Liam Flavelle on 9 May 2018

  • I've been researching into UK dividend-paying strategies and found one that shows promise.
  • My strategy invests in quality companies with strong payout ratios and low levels of debt.
  • The Piotroski F Score once again adds a little magic to improve the mix.

Since 2008 interest rates around the world have been languishing at their lowest levels since the 1930's. The Bank of England and other central banks have effectively forced income-seeking investors to take on more and more risk in their search for yield, the result being an inflation in the values of dividend-paying stocks.

So is there a way of playing this momentum in income stocks? I have been researching a lot of UK-based trading strategies recently, and have found and one that shows some promise.

The Results

UK Dividends

As always with my research you can click on any of the images to take you to the trading strategy where you can see more return, risk and backtest data together more information on how the strategy has been bolted together.

You can see in the chart above that since 2010 my strategy would have returned 24% a year, with a maximum drawdown of 20%. In fact, the strategy experienced its maximum drawdown twice during this period - during the Greek / Euro crisis in 2011 and immediately after the Brexit vote. The rest of the time the strategy would have been a very calm vehicle to invest money into.

This calmness is amply demonstrated by the high Sharpe and Sortino ratios of 1.5 and 2.3 respectively. These ratios show us how risky our returns were when compared with investing in a risk-free security (in this case US 3 month treasury bonds). The FTSE 100 over the same period achieved ratios of 0.8 and 1.1, making my strategy a safer place to invest over the last 8 years.

UK Dividends

This lack of volatility would have resulted in annual gains in 7 of the last 8 years, with 2018 shaping up well in spite of the markets pausing for breath since January.

How the strategy works

To achieve these results I used three traditional pillars of dividend investing - Yield, Payout Ratio and Debt.

To start, the strategy creates a universe of stocks by selecting all UK Shares and Depository Receipts with a Yield between 0 and 15%, an improving Payout Ratio and finally a Piotroski F Score of 8 or greater (the Piotroski score is a scoring system from 0 to 9 that seeks to identify quality companies).

This leads to a fairly small universe of stocks that the strategy can select from - running the screener today results in just 42 stocks meeting my requirements. This is mainly down to the Piotroski stipulation - scores of 8 or higher select only the highest quality companies into the mix.

Once the strategy has identified the available stocks it sorts them based on 4 factors:

  • Payout Ratio
  • Yield
  • Debt to Equity Ratio
  • Price to Sales Ratio

The InvestorsEdge ranking system sorts the universe of stocks and gives each one a rank score based on the strength of each factor when compared to each other. In this case, companies with high yields and low payout ratios, debt to equity levels and price to sales score and rank the highest in our list.

Each quarter the strategy simply opens positions in the top 10 stocks from the rankings, closing any current positions that don't appear in the list. Trading costs of £5 per transaction are included in all results.

My Research

I used the platform to conduct create, refine and test my strategy - clicking on this link takes you to the best version that I found. You can click on the History action to see the 42 iterations I went through to refine my model, which can be broken down into six steps:

Step one in my thought process was to identify the sweet spot for yields in the UK, so the first four versions of the strategy all focused on identifying the key yield level that worked best over the period. Ironically, identifying a maximum threshold for this factor became unnecessary as I incorporated other price and debt factors into the mix, but came to the conclusion that stocks with a maximum yield of 7.5% produced the best returns.

Step two incorporated a company's payout ratio into the mix and identified that it was a more important factor than yield in predicting short-term returns.

Step three looked to see if a company's history of increased dividend payments to shareholders can improve things. The simple answer is they don't, so this factor was removed from the strategy.

Step four incorporated the Piotroski F Score into the strategy. This score of 0-9 looks simple but, when you look under the hood is a complex beast that rates a company based on improving income, cash flows, assets, debt and gross margin. On its own, it is a weak indicator of future value but when added to an existing mix of factors tends to successfully filter out the higher-quality companies over the rest. A score of 8 or more was determined to produce the best returns over the last 8 years.

Step five saw me researching how selecting companies with lower debt levels improved backtested returns - once again I determined that adding this to the ranking order of stocks was better than selecting a specific value that a company had to beat to join the universe.

Lastly, in step six I introduced a timing element in adding a price ratio to the list of factors the strategy examined. Out of all the price ratios available, the Price To Sales factor worked best historically when applied with a small weighting to the ranking order of the strategy's universe.

The Risks

A key risk that I always examine with mechanical investing strategies is that the data phenomenon that I am exploiting will simply stop working. To combat this, I look to see if a strategy intuitively makes sense - my model invests in companies that pay increasingly safer dividends to its investors, that have low debt levels and are cheap when comparing their price to their sales.

Entering positions in stocks can be easy, but getting out again can be considerably more costly in a downturn. This strategy predominantly invests in companies valued between £200m and £7.5bn, so liquidity risks do exist if disaster strikes. Risk is a very personal thing, but I personally am willing to accept a higher level of risk by trading in smaller companies based on the enhanced returns they are capable of delivering.

The macroeconomic climate can have an impact on any strategy and this one is not immune to them. The key external force affecting this strategy is interest rates and their upward trajectory which has led to high yield stocks being punished this year. Our strategy has demonstrated a good degree of resilience over this period with positive YTD returns and gains in three out of four months.

Data anomalies are also a potential risk. Sometimes we data mine and exploit an anomaly that doesn’t repeat itself. We tend to look at the fact the strategy makes sense and has fewer working parts to see if this is the case and we test in different time frames to identify data mining. If we are happy that the strategy is robust we will then run it using a theoretical pot of money to see if it performs in line with the backtests.


The last eight years have been a great time to be invested in dividend-yielding stocks, and this strategy seems historically able to harness this momentum and generate significant returns from it.

With the Federal Reserve and Bank Of England beginning the process of normalising interest rates, the investing landscape will change once again. I believe that this process will take a significant number of years before rates are anything close to their pre-2007 levels, and that the pressures to reach for yield will still exist in the short to medium term.

I will be tracking this strategy from here on in and reporting my findings as to how it works when investing real money - feel free to sign up to receive updates on how I get on.


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