You can see that Value, which searches the market for companies that are underpriced relative to fundamentals—in other words, identifying “cheap” stocks trading at bargain prices—tends to outperform in both up and down markets, but does substantially better when stocks are struggling. In part, that’s because the companies identified by our value signals are those that already trade at very attractive valuations and experience less of a decline when markets are receding. We also note that stressful periods in the market tend to produce opportunities when solid companies see unreasonably pessimistic reactions in their share price.
Quality is another factor that produces most of its outperformance in down markets. That’s because quality stocks are those with strong underlying fundamentals, irrespective of price: companies with efficient operations, good managers, high-integrity accounting¬ and low risk of financial distress, amongst other things. We’re explicitly picking out the companies that should fare best in markets characterised by investor anxiety. Our high-quality selections are those we deem likely to hold up best when economic and financial stress is at its peak.
A foundation of our approach is diversification. That entails, for example, holding a broad enough portfolio of stocks to avoid taking too much risk in individual names, regions or industries. We also think about diversifying across sources of information that we use in our trading models. Along those lines, while Value and Quality perform better in declining markets, our Growth and Sentiment signals tend to do better when stocks are rallying—which is exactly why the overall performance we saw before shows such balance.
Our model identifies “good growth” stocks that have demonstrated strong recent expansion—not just in share price, but also in underlying fundamentals. This allows our portfolio to participate in periods when investors are optimistic and forward-looking, rewarding companies with strong growth, even if they aren’t particularly cheap. Sentiment-based signals likewise seek to ride recent winners that have underreacted to good fundamental news due to investors’ slow reaction to information in the marketplace. Not surprisingly, since both categories depend on positive reactions (e.g., to growth and good news), they tend to perform better in up markets than in down markets. Indeed, both signals modestly underperform when the market is declining—a testament to the benefits of pairing these signals with countercyclical factors like Value and Quality.
We’ve just seen that the R-Score model underlying Henderson Rowe’s direct stock investments produces fairly balanced outperformance in historical simulations through different economic environments, outperforming in both up and down markets. Looking more closely at the individual factors driving our strategy, we saw that the model includes both defensive trading signals that spring into action when fear dominates, and pro-cyclical factors that exploit investor greed when optimism reigns. We believe systematic models built around investor behaviour are one of the most effective ways of not only preserving wealth during periods when psychology rather than fundamentals is driving markets, but also positioning clients to benefit when the pendulum swings back.
Phil Wool, Ph.D.
Head of Investment Solutions
Rayliant Global Advisors