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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.
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 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 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 0.5% per trade are deducted.
Risk Neglect in Equity Markets, Malcolm Baker, The Journal of Portfolio Management Spring 2016
The Misbehavior of Marketshttps://www.scientificamerican.com/article/multifractals-explain-wall-street/
There are two look-back periods: (1) the entire stock's history from beginning until today (x-axis: Long-term Stability).
(2) the period from the last low point until today which yields the highest Warren Machine Measure (y-axis: Medium-term Momentum).
About 7% of all stocks globally have a Medium-term Momentum > 100
About 3% of all stocks globally have a Long-term Stability > 100.
Berkshire Hathaway has a Medium-term Momentum of 379 and a Long-term Stability of 370.
Martin Rothe, CTA
I am an academic who fell in love with data. I learned programming software when the first desktop PCs appeared in the business world. Applying logic on raw and boring data turned out to be a fun and intriguing exercise. I have developed algorithmic trading tools and programs and built a hedge fund company around it. The financial success of objective decision making especially in times of stress and uncertainty in the financial markets directed my attention to the more all-encompassing hot topics of machine learning and AI. My aim is to provide intuitive and fact-oriented solutions for portfolio managers, investors and people who seek advice for self-directed wealth management.
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