Quantitative Investment Strategy Insights

Investment Approaches in Quant Equity and Quant Fixed Income

Key takeaways

  • Much of quantitative investing is focused on equity investing, yet fixed income quantitative investing is mounting
  • Implementation alpha—requires subject matter expertise in research, portfolio management and trading
  • Risk return profiles differ—structural differences exist between equity and fixed income strategies
  • Macro and idiosyncratic risks—knowing your dominant risk

In a recent Market Insights Podcast, Denise Chisholm, director of quantitative market strategy in the Quantitative Research and Investments (QRI) division and Karishma Kaul, head of systematic fixed income strategies discuss how although a lot of focus about quant surrounds equity quant investing, it is also increasingly important and exciting in the fixed income space.

Differences in Quant Equity and Quant Fixed Income

Looking at the ecosystem of investing, a great majority of the quantitative driven analysis literature and investing has traditionally been focused on equity as opposed to fixed income. Equity and fixed income quant capabilities continue to evolve. There are three key factors that are important to keep in mind as we look at the differences between the two. Understanding the key differences as to research methods, model management, and testing is a component in robust portfolio optimization.

Implementation Alpha

As we move away from equities and into OTC (over-the-counter) fixed income assets, liquidity reduces, transaction costs increase, and the correlation between a quant model and an actual portfolio drops, putting implementation into focus. The key challenges when developing fixed income quant strategies are creating realistic models and implementing them efficiently. Accurately determining the right asset price and associated transaction costs of implementing a strategy and obtaining them in the market is crucial. This is what is called implementation alpha.

On the equity side, investors often struggle with alpha decay and the edge usually comes from the next not-priced-in alpha idea. When we compare that to the fixed income space, standard vehicles to get exposure to even simple factors like quality, momentum, and so forth in a cheap and transparent way do not exist. While there can be agreement on factor definitions themselves, actual construction and efficient implementation require subject market expertise in research, portfolio management, and trading. Hence implementation alpha becomes a key component of systematic fixed income strategies.

The good news is that fixed income quantitative investing is an uncrowded space. Fixed income remains dominated by large buy and hold players, such as insurance and pension clients, with constraints that may not always be economically driven. This can lead to structural inefficiencies that can produce opportunities for alpha to be harvested systematically.

Risk-Return Profile

A second important difference between fixed income and equity quantitative investing is the risk-return profile. With equities, valuations for the most part have a symmetric upside and downside. Fixed income, owing to its higher cash flow certainty, has an asymmetric profile where the upside is relatively limited and downside valuation can go to zero. This implies standard factors or approaches that might work in equities won't always work in fixed income. However, that is also an opportunity for exploring innovative techniques to build systematic strategies while accounting for the constraints within the asset class.

Macro versus Idiosyncratic Risk

Finally, in equities, it is relatively easy to neutralize for macro risk factors and isolate idiosyncratic risk as the dominant risk. Idiosyncratic risk is simply the risk of price change caused by the unique circumstances of a specific asset. As a result, an equity investor is able to take pure security selection bets relatively easily. Alternatively, in fixed income, total risk is generally dominated by macro risk and neutralizing for macro risk factors requires sophisticated risk models. Hence, a focus on risk models, transaction costs, and implementations drive a big part of a successful quant fixed income strategy.


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