Let me explain how we can verify the “Volatility Anomaly” I presented in my last blogpost.
In my view, the simplest way of testing this, is to rank stocks on volatility. Then make some portfolios based on the ranking and check the portfolio returns. It is something you could do in a spreadsheet. All you need is performance for a significant set of stocks over some period.
Here's an example:
A test of our strategy on the US equity market
Let’s do this test on the biggest equity market, US equities. The test is simple; Take the largest 3,000 companies in the US. Every month, we rank them on last two year volatility, and create 10 portfolios. Portfolio 1 holds the 300 lowest risk stocks, and portfolio 10 holds the 300 highest risk stocks.
Then we calculate returns for these 10 portfolios, and iterate this process over a significant period of time. Calculating annual returns for the period January 2000 – November 2019 shows these results:
Remember that these portfolio do not have any constrains on turnover. There are no trading costs or management fees. But really, these differences are rather large. The source of this analysis is our “Systematic Active Equity” web analysis. We do such analysis for more than 50 company fundamentals/characteristics, and the low volatility anomaly remains one of the most effective simple ways of ranking stocks. We do this for about 40 different markets around the world. The above result is not very surprising.
A crowded space, it is too late now?
Critics say that “the world is new”, this anomaly has been priced out by investors a long time ago. Well, it is true that professionals have known this for some time. But what if we do the same analysis as above since January 2014?
The low volatility anomaly still has some juice left. Let me remind you that this is in the longest running bull market of all times. –A period with extremely low risk in equity markets.
Creating a minimum volatility strategy
As mentioned in my earlier blog post, it takes more than ranking on volatility to set up and manage minimum volatility portfolios. Most managers would find that there is a need for turnover control, constraints to ensure portfolios have broad exposure to countries, sectors and industry groups. Total company exposure also needs constraints, and you would need a risk model to calculate robust measures of volatility and co-variance between difference companies.
The DNB Systematic Active Equity team now has 25 years of experience running such models. The minimum volatility strategy we have launched has been tested since year 2000. The risk reduction compared to the benchmark, MISC World, is approximately 25 %! The realized return of the portfolio is higher than the benchmark. Of course, this makes risk adjusted returns very attractive.
The risk reduction in our portfolio is approximately 25 %
The average turnover of this strategy during this period is round 70 % per annum. This means we are normally trading between 5 and 10 % of the portfolio in the scheduled monthly rebalances. The portfolio normally holds between 150 and 250 companies. All holdings are benchmark constituencies. They are the most liquid equities you can find. It is a strategy that is straightforward to trade, and has enormous capacity.
What are the implications of a low risk-strategy?
The average turnover of this strategy during this period is round 70 % per annum. This means we are normally trading between 5 and 10 % of the portfolio in the scheduled monthly overbalances. The portfolio normally holds between 150 and 250 companies. All holdings are benchmark constituencies. They are the most liquid equities you can find. It is a strategy that is straightforward to trade, and has enormous capacity.
There is little room for emotions, irrational (human) behaviour, price bubbles and agency problems. It is highly probable that broad benchmarks would be an efficient investment if we were all rational. However I have yet to observe any market where humans behave in a very rational manner. It would be nothing short of spectacular if the equity market was crowded with rational behaviour.
Neither do these empirical studies support rational behaviour. Let’s take a look at what is going on in the empirical results. Ours included.
The graphics on the left summarize what we should observe if the strong assumptions of modern finance were satisfied. The minimum volatility portfolio would still exist. It would provide lower risk, but at lower returns.
The graph to the right shows what we observe in markets. We observe this in all major markets in our backtests. We observe it on index level (MSCI World vs MSCI World Minimum Volatility), and a quick google search on “minimum volatility portfolios” shows that we are not the only ones tracking this.
The academic assumption of rational behaviour has been criticized since it was launched. The assumption is hard to prove wrong in sound statistical analysis, but investors of the world are free to take a look at the numbers, and figure out what they think.
Have a look!
Maybe your strategic equity weight can be revised if you can take equity exposure with much lower risk?
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