Systematic EM, Global Aggregate, and Unconstrained Bond Strategies Explained

Book: Systematic Fixed Income: An Investor’s Guide Author: Scott A. Richardson, Ph.D. ISBN: 9781119900139 Publisher: John Wiley & Sons, 2022

We covered systematic IG, HY, and credit long/short strategies in the previous post. Now Richardson takes us through the remaining categories: emerging markets, Global Aggregate, and Unconstrained Bond. Then he closes with a fascinating look at how different systematic and discretionary approaches actually are when you compare their holdings.

Systematic Emerging Market Bonds

The systematic EM hard currency bond portfolio focuses on sovereign and quasi-sovereign bonds, benchmarked to the JP Morgan Emerging Market Global Diversified Index. It engages in security selection across both country and maturity dimensions.

Target active risk is about 2%, which is actually lower than the typical discretionary EM bond manager (who tends to run around 3.5% tracking error with a Sharpe ratio of just 0.29).

The results are strong. The information ratio comes in at 1.02. At 200 basis points of active risk, that’s 204 basis points of alpha. The correlation with the credit premium is nearly zero (0.03), and the R-squared is just 0.12%.

Richardson also runs a more comprehensive regression controlling for the US term premium, emerging market debt premium, emerging corporate premium, and EM currency exposure. After all those controls, the information ratio is still 0.98. A systematic EM bond portfolio is delivering genuine alpha that’s not explained by any of the usual risk factor exposures.

Compare that to the 117 discretionary EM bond funds from Chapter 4. Those managers had a Sharpe ratio of 0.29 and average excess returns of about 1%. But much of that came from tilts toward riskier EM countries and loading up on credit beta. The systematic approach generates better risk-adjusted returns while keeping beta exposure in check.

Systematic Global Aggregate

Now we get to the broadest fixed income mandate. A Global Aggregate portfolio combines security selection across rate-sensitive assets (government bonds picked by country and maturity) and credit-sensitive assets (corporate bonds picked across and within issuers). It can also incorporate active currency views.

Target active risk is about 1.5%. The simple regression against the credit premium shows an information ratio of 0.91. At 150 basis points of active risk, that’s 137 basis points of alpha.

But Richardson goes deeper with a full regression controlling for the global term premium, credit premium, emerging market debt, EM currencies, and the volatility premium. After all those adjustments, the information ratio is 0.71 and the annualized alpha is 0.77%. The correlation with the credit premium is only 0.11.

That’s solid. Not as flashy as the long/short or EM numbers, but remember: this is a very broad, diversified mandate. Generating 71 basis points of IR in a Global Aggregate portfolio that’s genuinely uncorrelated with traditional premia is a meaningful result for asset owners.

Systematic Unconstrained Bonds

The unconstrained category is where things get spicy. This is a benchmark-agnostic strategy (benchmarked to cash) that can go anywhere in fixed income: government bonds, corporate bonds, EM debt, securitized products. It uses leverage, derivatives, and shorting. Target active risk is 4-5%.

The unconstrained portfolio has a bit more credit premium exposure than the other systematic portfolios. The R-squared against the credit premium is 6.58% (higher than the near-zero we saw elsewhere), and the slope coefficient is significant (t-stat of 4.20). That makes sense because the strategy deliberately captures some fixed income risk premia as part of its mandate.

But the alpha is substantial. The simple regression shows an information ratio of 1.41. At 500 basis points of active risk, that’s 705 basis points of alpha.

After the full regression controlling for global aggregate returns, inflation, credit premium, EM debt, EM currencies, and the volatility premium, the alpha drops to 3.99% annualized with an information ratio of 0.91. The risk premia capture is real but small compared to the overall return, and it doesn’t eat the alpha.

Compare that to the 103 discretionary Unconstrained Bond funds from Chapter 4. Those funds tended to use their unconstrained mandate as an excuse to load up on credit beta. The systematic approach keeps that tendency in check while still using the breadth for genuine security selection.

The Holdings Analysis: Proof They’re Actually Different

Richardson saves one of the most compelling pieces of evidence for the end. Palhares and Richardson (2020) looked at 154 HY mutual funds and compared their actual portfolio holdings to what a systematic approach would do.

They computed a “transfer coefficient” (TC) for each fund: how correlated are the fund’s active weights with the systematic signals (carry, defensive, momentum, and value)? If a fund is overweighting bonds that score well on these signals, the TC will be high.

The result? The average discretionary HY fund has a TC near zero. They’re not systematically targeting any of these well-documented return drivers. Their active bets look essentially random relative to the systematic signals.

The systematic fund, by contrast, sits far to the right of the distribution with a high TC. It’s deliberately and consistently targeting exposure to these investment themes.

This is powerful evidence that systematic and discretionary approaches are genuinely different. They’re not fishing in the same pond. A systematic fund adds real diversification to an asset owner’s lineup.

Richardson’s Career Advice

The chapter closes with some surprisingly personal career advice for aspiring systematic investors.

Failure is success. Most investment ideas won’t work out. That’s fine. The problem is when organizations set KPIs like “change the model by X percent this quarter.” That pressure is inconsistent with a careful, systematic process.

Watch out for hidden data mining. Keep track of your “graveyard” of failed ideas. If you try 100 things and focus only on the 3 that worked, you don’t actually have 3 good ideas. You have noise that looks like signal.

Culture matters. Systematic investing requires both deep asset class knowledge and strong data analytics skills. These rarely exist in the same person. Teams need to hire for both and manage the tension between specialists who each want decision-making authority.

Communication is key. Discretionary managers can tell a story about each position. Systematic managers have 500+ positions driven by abstract signals. Learning to explain that to asset owners, with deep attribution and transparency, is a real competitive advantage.

Be humble about market efficiency. Ask yourself: what’s your edge? Is it exploiting a risk premium, a behavioral error, or an institutional friction? If it’s the latter two, keep checking whether your edge is still there.

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