Back in March of this year I posted about a low volatility quant strategy that I added to the QuantPulse subscription. In that post I mentioned a strategy that combines the low volatility, value, and momentum factors to increase performance and still keep drawdowns in check. The strategy is called the Conservative Formula and you can read a great summary post on the strategy here from the Alpha Architect team. And here is a link to the source paper. This is the strategy I will implementing and discussing in this post.
The Conservative strategy first sorts stocks into a low vol group and a high vol group based on 3 year volatility. The the stocks in the low vol group are then ranked by a combination of value and momentum. It uses Net payout yield as the value metric and 12 month price momentum as its momentum measure. It then picks the top 100 stocks and equal weights them. In addition, the strategy limits the stock universe to large cap stocks, actually the largest 1000 stocks in each of the regions tested. Portfolios are re-balanced quarterly. The results are quite good over a long period of time particularly on a risk-adjusted basis as shown in the table below.
And the results are good across regions. The chart below plots returns vs volatility for the conservative portfolio and a portfolio with the exact opposite characteristics.
Now for my implementation I did things slightly different. Since I’m constructing much smaller portfolios, 10 and 25 stock versions for individual investors, I used a larger stock universe, the OSAM market leaders universe that I usually use for very large and liquid stocks. For the volatility sort I used 2 year volatility due to limitations in the software I use, Portfolio123. For momentum I used the same 12 month price performance and I also use net payout yield (aka Shareholder Yield). Finally, like I usually do in all my quant strategies, to reduce the risk from stock market crashes I used my SPY-UI risk reduction indicator. Re-balance period is 4 weeks and I constructed two portfolios, top 10 stocks and top 25 stocks equally weighted. Results are posted in the table below. I compared performance to the SPY and to the US Minimum Volatility ETF.
Returns, risk, and risk-adjusted returns are quite good for the strategy. You get a low-volatility like portfolio juiced up by factor returns from value and momentum. Seems like a good trade-off between low vol and returns. In fact, in terms of risk-adjusted performance, as measured by Sharpe ratio, this strategy would be at the top of the strategies in my QuantPulse strategy universe. The QuantPulse low vol strategy, the Consumer Staples Value strategy, and the Utilities Value strategy are not far behind. In the table below I show the top 10 QuantPulse Strategies ranked by sharpe with the Conservative Formula Strategy added.
We should take these performance numbers with some skepticism since low vol has been one of the most dominant factors in recent years, and value has seen a large period of underperformance. Nonetheless, as results over the longer term show combining low vol, value, and momentum in a simple approach like this is pretty powerful.
Note: the conservative formula strategies will be added to the QuantPulse subscription by the end of this month for the new year.
3 Comments
Sitiben · December 8, 2019 at 8:04 am
Great post and impressive results.
Is there a way you could also:
– share the turnover of the various strategies. It helps in making tax aware decisions
– also add the performance of USMV and SPY with the UI-Comp approach? It helps evaluate the benefit of UI-Comp vs the strategies.
Thank you Paul
Doug Landry · December 17, 2019 at 4:22 am
Is this strategy similar to what Pim Van Vleit published in his 2017 book, “High Returns from Low Risk”?
paul.novell@gmail.com · December 17, 2019 at 7:45 am
Don’t know what’s in the book, but he is the lead author of the paper I link to in the post.
Paul
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