Quant Concepts: Do You Need the Risk?

By leveraging earnings and momentum data, Emily Halverson-Duncan finds outperformance while keeping volatility under control  

Emily Halverson-Duncan 17 July, 2020 | 7:36AM
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Emily Halverson-Duncan: Welcome to Quant Concepts' virtual office edition. Following the momentum style of investing has always been attractive to investors, especially given the high returns that are typically associated with it. It may, however, be avoided or limited and used due to the higher volatility that's usually present. But is that excess volatility a necessity?

Today, I'm showcasing a strategy that looks for Canadian momentum stocks within the CPMS Canadian universe without taking on excessive risk. So, let's take a look at how to build that.

First off, as always, we're going to go through and rank our universe of stocks. As mentioned, we are doing this in the CPMS Canadian universe which today houses 699 names. For our ranking step, we are going to look at three different factors. The first one is quarterly earnings surprise which looks at what a company is expected to report on earnings and whether or not they beat or miss that number. Obviously, you'd like them to beat it. So, higher values are best. We're looking at quarterly earnings momentum which is looking at a company's quarter-over-quarter growth in earnings and again, we want higher values. And then, lastly, we're looking at a company's stock price and the change from that to its highest price over the last 12 months. And again, you want that to be as close as possible to the 12-month high. So, a higher value is preferred.

Once we've organized our universe, we're going to go ahead and apply our screens. So, some of the screens we're applying here – both that quarterly earnings surprise and quarterly earnings momentum, we want that to be positive, so greater than or equal to 0.01, just to make sure again they are on the higher end or avoiding any big negative numbers or surprises in terms of earnings. Price relative to the 200-day moving average – this is a technical indicator. So, what we are looking at is a stock's price compared to its 200-day moving average of price. We want that difference to be greater than or equal to 3% indicating that a company is trending upward. Five-year beta, we want that to be less than or equal to 1. This is one that we explore a lot on these videos, and this looks at a stock's price sensitivity compared to the benchmark, which in this case is the S&P/TSX. This is what's really going to help us reduce that risk that is typically associated with momentum models. And then, lastly, on the market cap side, we're just going to screen out the bottom-third smallest stocks in the universe just to make sure that we're not getting into any ultra-small caps.

On the sell side, we're going to sell stocks very simply if that price relative to 200-day moving average drops below negative 15% and that's really it on the sell side.

So, from here, we obviously want to see how this model did in our back test. So, let's take a look here. Our back test today consists of 20 stocks and the benchmark we're comparing to is the S&P/TSX Composite. So, looking here, we can see that from the back test period, which is February 1999 to June 2020, the model returned 22% annualized, which is a very hefty number, and that's an outperformance of 15% over the benchmark across that timeframe. Turnover is a little on the higher side compared to what we usually look at, at about 82%. So, again, turnover is looking at how often you are trading from the model on average in a given year. So, at 82% you are probably doing about 15, 16 trades in a year on average. Some years will be higher, some years will be lower. But some of the metrics we want to look at – we can see that the performance is quite strong, but again, we are trying not to take on too much risk, so really want to focus on those risk metrics to see if we are able to achieve that.

So, of course, downside deviation, which is looking at the volatility of negative returns, for the strategy, it has a value of 8.3% and the benchmark has a value of 10%. So, that smaller value there is an indication that we were able to better manage risk with respect to the volatility of negative returns. And then, otherwise, always like to look at my favourite green and blue chart here and this tells you how the model did in both up and down markets. So, in up markets where we would expect it to well, the model outperformed 68% of the time, so definitely good in comparison to the benchmark. But in down markets, it actually outperformed 83% of the time. So, despite the fact that it has such a high return, which can be very much associated with the momentum model, it still manages to perform well on the downside and still to protect your assets in volatile markets. So, if you are wary about momentum, it might be worthwhile still giving it another consideration and just coupling in some risk metrics to help make sure you are not taking on too much volatility.

For Morningstar, I'm Emily Halverson-Duncan.

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Emily Halverson-Duncan  Emily is Director, CPMS Sales at Morningstar

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