Peloton’s Journey

Since our founding, Peloton has been a research-oriented investment manager. For most of that time, our research has been fundamental in nature: investing in great companies whose stocks trade below our estimate of their long-term value. Fundamental investing will always be a core principle for us.

Several years ago, we began to investigate quantitative strategies. In contrast to fundamental research, quantitative investing focuses on identifying securities of companies which display positive quantitative characteristics. Over time, we’ve developed our own quantitative research into strategies which we now use in our private fund and our Core Growth portfolios. The type of quantitative investing we do is known as factor-based investing. We thought it might be helpful to describe factor-based investing and offer some important lessons learned.

What is Factor-based Investing?

Factor-based investing seeks to identify attractively priced securities, relative to standardized fundamental criteria, or factors. In this way, factor-based methods blend the purely quantitative research with qualitative or fundamental research. An easy example is buying low P/E stocks. Companies with earnings are valuable (the fundamental piece), but only if you don’t over-pay for them (quantitative).  In addition to ratios, factor-based approaches also use rates of change and correlation between variables.

Why Some Factor-based Methods Work Well

While a sound fundamental assessment of a company incorporates quantitative aspects, the ultimate investment decision relies on a reasoned argument. Human reason is powerful, but also subject to biases which work against us at times. Factor-based investing can work well because it places limits on human reason. The role of reason is to construct the correct – the highest value-adding – factors and the trading parameters surrounding them. Reason then steps back and trusts the mechanism it built. In short, factor-based approaches limit our capacity to make mistakes when our biases try to intervene.

Successful Factor-based Investing Principles

On our journey to our factor-based investment strategies, we adopted a few principles, which we want to share with you.

  1. Recognize that data-mining is always a risk. Data-mining occurs when, looking at historical return patterns, you notice trends which yield high returns. Unfortunately, those trends turn out to be mirages. Be sure your factors are real, not ephemeral. 
  2. Have a behavioral basis for every factor strategy. Unless you’re the company’s founder, every security you’ve ever owned was bought from someone else. Market participants are constantly buying and selling – and both sides can’t be right. Be certain that you understand why a given factor works; be able to point to why your counterparties are wrong.
  3. Choose an investment opportunity set with attractive return potential. If your objective is capital appreciation, apply your factor method to security types consistent with your goal. Switching from stocks to a money market fund may have worked for you in the past, but your timing may have just been lucky. Money market funds are good for safety, not growth.
  4. Once you’ve followed the three principles above, trust your strategy. The point of factor-based investing is to guard against your worst instincts. Don’t ruin your strategy by selling when relative performance is poor in the short run. In our research, the best individual factors outperform in only 50-60% of years. But their probability of outperforming rises parabolically over 3, 5, and 10 year periods.
Conclusion

Factor-based investment methods are complementary to fundamental investing – it’s not an either/or in our view. Factors are useful because they protect investors – even professional investors – from emotional decision-making. If factor-based investing is appealing, make sure you protect yourself with sound principles before you begin.