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Basically, investors cover 3 aspects before buying a stock:
1. Assessment of return-to-equity, financial stability and management quality.
2. Assessment of market valuation and screening of historical values.
3. Assessment of future risks and price volatility.
The last aspect is the hardest to estimate and maybe for many investors the most critical one. Long-term investors rather prefer stability of returns and therefore build portfolios. But is the risk correctly accounted for?
Some investors have superior knowledge and insights of a company's internal affairs and others assume high risks for their speculation. With a clever strategy that better specifies the risks you can now simply follow the 'Best-in-Class' companies and as stock holder be part of their superior success.
When calculating Risk of individual stocks or portfolios the concept of "standard deviation" or "downside deviation" is commonly used. The formulas contain assumptions about the "real world" which are not always correct and in certain circumstances this can lead to sub-optimal decisions.
Sharpe ratio*: average return / standard deviation
Sortino ratio*: average return / downside deviation
Warren Machine Measure: average return / effective drawdown
* risk-free rate and target return are set to 0%
A higher ratio should indicate a better return-to-risk constellation, but this is not always true for Sharpe or Sortino, whereas the Warren Machine Measure ranks return-to-risk correctly.
Click the images* to enlarge
The reason for the better precision of the Warren Machine Measure is the fact that the chronological distribution of returns is taken into account and there is empirical evidence that volatility is more predictable than prices, i.e. risk is rather clustered in regimes of low or high volatility.*
A precise Risk concept like the Warren Machine Measure allows for an unambiguous ranking of stocks in terms of their Stability.
Due to a more precise measurement of Stability the transition to a more unstable state is much better predictable and this fact adds a new dimension to selection and timing of individual stocks.
An investment in high-stability stocks is not necessarily pursuing the best possible returns but rather reduces the downside volatility to a large extent. A Best-in-Class approach to select stocks creates superior portfolios, as demonstrated below for a universe of 500 US large cap stocks.
The track record below is calculated using adjusted closing prices, i.e. dividends are constantly re-invested. At the beginning of a month, the 10 stocks with average trading volumes of at least 100,000 and with the highest Warren Machine Measure (Best-in-Class) are selected for the portfolio. This portfolio is held for an entire month without any transactions. Transaction costs of 1% per trade are deducted.
To zoom in, drag a rectangle with the mouse pointer or click the 'Zoom' buttons or move the orange handles at the bottom.
Past Performance Is No Guarantee of Future Results
10 Top Stability Stocks
With a subscription
- you get a bigger universe of available stocks ranked by Stability (Best-in-Class)
- you receive information several days before they get published online
- you can filter by volume, sector, industry or country
- you become more independent of financial advisors
Above, you see the hypothetical result derived from 500 US stocks with at least 100,000 trading volume. It is a sample portfolio and by no means optimized. With very few transactions (on average 1.6 per month) major downturns can be mitigated to a large extent since
- the portfolio already consists of strong companies
- the portfolio switches automatically into the best surviving companies based on current market conditions
For independent support cross-check portfolio compositions with the great tool Portfolio Visualizer.
Best-in-Class portfolios can currently be provided for:
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