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Using credit information for Quant Equity

Using credit information for Quant Equity

02-08-2017 | Research
  • Bart van der Grient
    Bart
    van der Grient
    Reseacher
  • Wilma de Groot, PhD
    Wilma
    de Groot, PhD
    Lead Portfolio Manager and Head of the Quant Equity Portfolio Management team
  • Joris Blonk
    Joris
    Blonk
    Researcher

Speed read

  • New addition to Momentum factor
  • Research builds on a long history of equities and credits research
  • Added value on top of equity Momentum

Since the start of our multi-factor stock selection models in the early nineties, the equity price momentum factor has been very important. All our quantitatively managed equity strategies include momentum as one of the factors. We have now found that credit momentum offers added value on top of the information already provided by equity momentum. We therefore add Credit momentum to the Momentum factor in our stock selection models.

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Research: credit Momentum has predictive power for equities

Recent research shows that not only equity momentum but also credit momentum has predictive power for equity returns. Companies with high medium-term bond returns tend to have higher stock returns in the subsequent month.

Bittlingmayer and Moser (2014) show that within a sample of high yield bonds, abnormal price declines of bonds are likely to be followed by abnormal price declines in the corresponding stocks in the subsequent month. And one year later, Ben Dor and Xu (2015) create equity portfolios based on bond momentum looking back up to twelve months and show positive and significant returns, with lower drawdowns than traditional equity momentum.

We have recently researched the spillover of credit momentum into equity markets ourselves. Because of our long history in credit research, we can make use of a rich global database containing detailed information on bonds in either Bloomberg Barclays U.S. or Euro Corporate Investment Grade or High Yield indices, going back to the early nineties. The fact that bond data with such breadth and depth is much more difficult to obtain than equity data could be a reason why credit markets are relatively under-researched in the academic literature, making this research distinctive.

We started our analyses by considering the stand-alone performance of a credit momentum spillover signal. For each month in the period from January 1994 to December 2016, we ranked all stocks in our universe (MSCI constituents and liquid off-benchmark names) for which we have both stock and bond return data available over the past 12 months (resulting in approximately 800 ranked companies on average).

The results confirm the notion that information from credit markets also matters for future stock returns: stocks from companies with a high credit momentum, as defined by 12-minus-1 month excess return, outperform low credit momentum stocks in the subsequent month.

Most equity momentum strategies do not include the most recent month to avoid the short-term reversal effect. Interestingly, our research shows that including the most recent month of credit returns leads to a stronger spillover signal. Inclusion of the most recent month of credit returns therefore improves the spillover effect.

To the best of our knowledge, the academic evidence for the credit momentum spillover effect is limited to the United States. Our proprietary global credit database allows us to study the effect of credit momentum in European markets, as we have sufficient coverage in euro denominated bonds dating back to 2002. Our results, which can therefore also be seen as an out-of-sample test of existing academic work, show that the credit momentum effect is also present in Europe.

Two types of information

Even though equity and credit momentum factors are positively correlated, both signals provide unique information. We have performed a Fama-MacBeth (1973) regression analysis, regressing the individual one-month ahead stock returns on the past credit momentum values of a company and other characteristics, among which past equity momentum.

The results of our regressions show that 12-month credit momentum has informational content above that contained in traditional equity momentum and that this added value comes from both the most recent month and the spillover signal over the rest of the past year.

Intuitively, it makes sense that equity and credit momentum give different information, as investors in both markets focus on different aspects of a company. The equity value of a company can theoretically increase without bounds, whereas the value of a corporate bond’s future cash flows will be limited. As a result, equity investors typically focus more on the upside potential of a company, while credit investors focus more on the downside, avoiding default risk.

Implementation in the models

Based on all research findings, we add credit momentum spillover to the momentum factor of all our quantitative stock selection models of the Core Quant, Conservative Equities and Factor Investing strategies as of the second quarter of this year. By combining price information from stock markets as well as credit markets, we move towards a ‘company momentum’ signal.

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