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Factor investing in corporate credit

Caio Natividade

There are two main investment philosophies out there: discretionary and systematic. While still a minority, systematic investing has grown increasingly popular over the years and it is the focus of our team’s research.

Systematic investors search for persistent drivers of financial market returns. Persistent drivers of short, medium and long-term returns. We call these drivers factors, and try to find as many as we can in order to build a portfolio that is well diversified. Think of a factor as a version of a “robot investor”.

Factor investing is based on the premise that investors earn a premium in compensation for exposure to the risk that the factor brings. For instance, an investor exposed to market beta - in other words, to market risk - should earn a premium in compensation for it. This describes the Capital Asset Pricing Model, the first ever factor model.

However, in the 1990s two economist from the University of Chicago, Eugene Fama and Kenneth French, popularized the implementation of two new factors in equity markets: size and value. A new dimension in investing science was born with it.

The Fama-French premise is simple and intuitive. The investor can potentially be not only rewarded by exposure to market risk or market portfolio, but also to the size and value portfolios. In the case of Value, for instance, the portfolio would be built by buying companies that look “cheap” according to the metric of cheapness – price-to-book – and sell those that look expensive according to the same metric.

Since their publication, a number of new factors have been discovered. For instance: momentum, quality and Low Beta.

Factor investing has also become popular in other asset classes, but interestingly it isn’t as much so in Credit markets.
Why has Credit fallen behind the rest?
Two simple reasons. The first one is that is notoriously difficult to study on a systematic basis. Corporate bonds are very diverse. They come with different seniorities, maturities, optionality and so on. At the same time, it is necessary to remove the rates component from the bond yields in order to isolate their credit element. The over-the-counter nature of this market also create challenges to gather data.

The second reason is how costly it is to trade credit instruments. In our study we make a comparison with the transaction costs of other asset classes. Trading corporate credit is orders of magnitude higher than the rest.
How is it possible then that you have developed a framework for factor investing in credit markets under such limitations?
The good news is that the appearance of a liquid CDS (Credit Default Swap) market in the early 2000s has paved the way for the factor investor to take a fresh look at the asset class.
Think about CDS as an insurance for credit risk, which premium is quoted and traded in the market. The instrument is a pure measure of credit risk. The higher the premium to be paid (or received if the investor is the seller) the riskier the credit issuer risk.

The advantage of the CDS markets, compared to the bond market is that it works with standardized contracts. The most liquid issuers have contract with similar specifications. Therefore, the diversity problem faced by corporate bonds is now eliminated.

Another advantage is the CDS markets allow the investor to go short the credit, which is akin to going short the issuer’s debt, without major issues. This makes factor investing a lot easier in the asset class, as the systematic investor typically seeks to build portfolios that have similar number of long and short positions.
So what are the drivers of credit markets?
With CDS instruments, we find that the best explainable driver of credit markets is an abstract factor that relates to economic growth and market sentiment. This is similar therefore to equity markets. But as factor investors we typically aim to capture drivers that are orthogonal to this, which can therefore diversify a long-only exposure.

And there are quite a few other, alternative drivers. For instance, the duration of the asset is a driver. Lower duration instruments tend to outperform higher duration instruments, after taking volatility into consideration. The beta that the asset has to the market is also an important driver. The CDS of lower beta companies outperforms the CDS of higher beta companies. Higher quality companies – those that are more likely to pay for their debt – outperform lower quality companies and, as is the case in equities, cheaper debt outperforms expensive debt after accounting for volatility differences. Finally, momentum is also a driver in that credit default swaps that have been rallying in the past are likely, in the future, to outperform those that have been weakening in the past.

As is the case with factor investing in any asset class, it is always important to understand what is behind a specific driver, why the phenomenon exists. We find that leverage constraints, peer benchmarking, hidden risks – such as jump to default and slow information diffusion are behind most of the return drivers, and are confident that these will likely persist over time.
How can we invest in them?
We introduce 6 strategies here, each associated with a specific driver – in other words, specific factor. They are: a low duration strategy, a quality strategy, a value strategy, a low beta strategy and 2 momentum strategies.

These strategies are separated according to type of market factor. 4 of them capture company-specific factors, and 2 capture so-called market factors; in other words, drivers that are not specific to a company but affect all credits at the same time.

Transaction costs are an issue in credit markets, even when using CDS contracts. Therefore the company-specific strategies had to be aggregated together so that all CDS positions were netted before we looked at transacting.

However, because we still face high transaction costs in the asset class, the single factor portfolio returns were not as attractive as we were expecting. In order to overcome this issue we firstly created portfolios containing a mix of the different factor strategies. Namely: Quality, Momentum, Value, Low Beta and Low Duration. Lastly, we developed a novel technique that dynamically controls the turnover and transaction costs of our strategies.

Introducing 2 applications: one for the absolute returns investor and one for the long-only investor. Both should be interested in the fact that our strategies are either negatively correlated, or uncorrelated to the credit market as a whole, and therefore can add value either on their own or in combination with other strategies.
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