Thursday, February 24

Moby Flagship Quant Dividend Fund


Today we’re introducing another quantitative-based portfolio – The High Dividend Aristocrat Strategy.

Similar to the strategy we released yesterday, this strategy also uses machine learning and algorithms to select the stocks within the portfolio. 

The goal of this strategy is to make a portfolio of 10 high dividend paying stocks with sustainable earnings and dividends.

The Dividend Aristocrat strategy combines the stable income of high dividend paying stocks with the limited downside risk associated with long-term earnings quality and attractive valuations.

There is a three-fold benefit to this strategy:

  1. The price return of the portfolio. This portfolio is designed to not only pay you but also increase in price.
  2. The dividend is all-but guaranteed. While nothing is 100% guaranteed, the companies here are virtually guaranteed to maintain or increase dividends based off their histories.
  3. The combination of stock price increases, dividends, and lower valuations creates a very solid and safe total return strategy. This limits our downside as we're buying most of these companies at lower valuations.

You can see the active portfolio below!



How This Portfolio Was Made:

  1. Start with the S&P 500 constituents. Then only analyze the companies with over $3B of market cap and $5M of average daily value traded over the last 3 months.
  2. Then filter out the companies who haven't increased or maintained dividends over the last 10 years.  Please note that this does exclude newer companies but we did include spin-off's and divestitures.
  3. Only add companies with high dividend quality and sustainability. What this means is that we used internal metrics to find companies that not only pay dividends but pay quality dividends. We don’t want to invest in companies that will not be able to sustain high and growing dividends.

Once we've narrowed down this short list we use over 20 more internal and proprietary indicators to signal which stocks should be included in the portfolio.

From there we then rank the stocks and create a Z score for each stock left that we could invest in.

We won't get into the weeds on what a Z score is but basically we're analyzing how a stock moves relative to the index. 

We can then judge how stable, volatile, etc. it is!

 

Returns & Features:

Expected returns:

  • Expected Dividend Yield: 4%
  • Expected Annual Return: 11%

 

Features of the strategy relative to a broad market strategy: 

  • Better performance in down months
  • Lower volatility of returns
  • Lower beta and higher sharpe ratio
  • Limited max drawdown

 

How It Works & What's A Quant Strategy:

While we do give you a lot of individual recommendations on stocks and cryptocurrencies that are primarily based on fundamental research, this strategy (and many strategies to come) are based on algorithms that we’ve built!

Don’t know what an algorithm is? In a nutshell, algorithms are a set of computer based rules built by engineers & computer scientists. In this instance, our in-house team analyzes large data sets and makes their investments (aka rules) based on a ton of technical indicators that are constantly changing.

So rather than the humans making the decisions, the computers are the ones doing it. This is a much newer investing style that the top hedge funds and banks in the world use everyday. This is one of the few ways that the best investors in the world consistently beat the market.

 

How To Use It:

Rather than just give you individual ideas in isolation, the way these strategies work is by recommending a basket of weighted stocks/cryptos that are meant to be used as a portfolio!

So in the example above, rather than just buy a stock blindly, our algorithms recommend how much of that stock to buy.

With market dynamics changing so often, these strategies are designed to update once a month (and we will notify you once they do).

Therefore, what we’re doing is picking a set amount of money and then allocating that money in percentages across the stocks the algorithm recommends.

So if we choose to invest $1,000 and the algorithm recommends 20% of Stock A, then we would put $200 in Stock A, and the same for Stock B and so on – until the entire 100% of our $1,000 is invested.