To date, the majority of corporate bond benchmarks use a market capitalization weighting approach to determine the size of the constituent holdings. This methodology has been borrowed from the equity space where it has been the norm for decades. Market capitalization may make complete sense in equities, where it is a reasonable proxy for overall market wealth. However, in the case of bonds, capitalization is not a measure of wealth. In fact, it could be quite the opposite – the more a company borrows, the more indebted it becomes and thus the worse its income position could become. Higher corporate leverage generally induces higher volatility in returns. From a credit index perspective, a market capitalization weighted index would, by construction, overweight highly indebted issuers. This has the unintended consequence of greatly exacerbating index return drawdowns during a credit crisis. Given these inherent flaws, is a market capitalization weighting scheme necessarily the best metric for benchmarking the performance of active corporate credit mandates? Some of our longer term institutional clients have asked us whether there are alternative weighting schemes that one could explore, and if so, what their benchmark performance characteristics would look like? This blog addresses some of these questions.
Starting with the US dollar denominated constituents of the ICE BofAML Global Corporate Index (G0BC), we explore applying two alternative risk-based weighting methodologies: (i) a bond equal-weighted scheme and (ii) different risk parity weighting schemes, in which the weights are related to the volatility of the underlying bonds. Whilst the former scheme is self-explanatory, the volatility dependent methodologies perhaps require some further clarification.
Defining a coherent measure of volatility for bonds is not straightforward, as bond risk is derived via a number of distinct risk factors. Normally, one would need to use a factor risk modelling framework to remove the systematic sources of volatility and thereby isolate the excess return volatility. In practical terms, Duration Times Spread (DTS) is often used as a proxy measure of bond volatility, as it has been shown to be a good estimator of corporate bond excess return volatility in academic research. We calculate DTS by multiplying a bond’s credit spread by its spread duration. For the risk parity weighted index, we calculate the weight of each bond as an inverse proportion of the DTS (i.e. 1/DTS) and then re-weight to make sure the portfolio sums to 1 for each month. This is a purely theoretical index as in practice there could be a situation where a bond has a very low DTS and very low debt issuance, in which case it would be very difficult to purchase the required amount. We then take our risk parity weighted index a step further, by combining the approach with market capitalization. This is done quite simply by reweighting the original risk parity weights to give the same risk contributions as the market capitalization index across multiple dimensions, or risk cubes, such as sector and issuer.
Below, we present our back test results for the following four weighting schemes:
The key performance characteristics which would be of interest to investors are: returns, volatility, drawdown risk and turnover. In Figure 1 and Table 1, we show the performance of these various indices from January 2000 to May 2018. The risk parity weighted index has the best risk-adjusted returns and the lowest maximum drawdown. When we neutralize this index, we still maintain better risk-adjusted returns and maximum drawdown characteristics than the market capitalization and equal weighted indices. Both risk parity indices have over double the annualized turnover of the market capitalization index. Interestingly, the equal weighted construction also displays better performance characteristics than the market capitalization approach, with only a very slight increase in turnover from 60% to 65%.
We also investigated the impact of transaction costs on our results. Applying our proprietary historical transaction cost model gave us broadly similar conclusions to those presented here. Finally, we performed a return correlation analysis of these custom credit indices versus the S&P 500 equity index. The last line in Table 1 shows that the correlation pertaining to the risk parity index is by far the lowest of the four – in other words, this particular construction generally provides the greatest degree of portfolio diversification in a multi-asset setting.
An important consideration for indices is liquidity. Whilst larger market capitalization bonds are generally more liquid, we investigated whether larger risk parity weights had any particular liquidity bias. Interestingly, our analysis of forward traded volumes in different risk parity quintiles found no bias either way – i.e. the top risk parity weight quintile had the same forward traded volume in March 2018 as the average of all the other risk parity weight quintiles.
Concentration risk implications
Another key concern for indices is concentration risk. To measure concentration risk, we use the Herfindahl-Hirschman Index which is computed as the sum of squared weights per issuer. The lower the value the less concentrated the portfolio is. From Figure 2, we can see that the equal weighted index is the least concentrated portfolio through time. Additionally, the risk parity weighted index has been consistently less concentrated than the market capitalization index since 2007. Also note that the market capitalization index had the highest levels of concentration risk during the global financial crisis. Finally, as we would expect, the neutralized version of the risk parity weighted index has the same concentration risk through time as the market capitalization index.
Benchmarks are thought to be an efficient representation of “the market”. More importantly, the choice of benchmark by investors is representative of their investment style. Consequently, the benchmark tends to be the starting point for portfolio construction for active mandates. It is clear that not all investment styles seek to be fully consistent with market capitalization weighting – for example, there are longer term buy and maintain styles that actively seek to capture illiquidity premia, or even fundamental quality styles that weight issuers from a balance sheet perspective. We will explore some of these in future blogs. In this piece we have focused on risk-based styles, which are about mitigating volatility and limiting drawdowns during credit crises. It is worth noting that not every investor, when specifying an active mandate, wants to necessarily start with the universe of the most heavily indebted companies or sectors. Some of our longer term institutional clients have specifically wanted to discuss the merits of equal weighted and risk parity related performance benchmarks. The thoughts and empirical results presented in this blog are a starting point for such a discussion.
Following the Fed’s announcement, please see below for market views from the Global Fixed Income, Currency & Commodities Team (GFICC):
Consistent with our and the market’s expectations, the Federal Open Market Committee (FOMC) increased the Fed Funds rate range to 1.75%‐2.00%.
The June statement was moderately more hawkish than the market had anticipated. The Committee emphasized the solid growth and inflation backdrop. The Fed effectively dropped its forward rate guidance by removing language in the statement on the need for the Fed to keep the Fed Funds rate below longer-run levels for “some time”. The statement continues to emphasize the Committee’s symmetric inflation objective. The Fed statement did not reference the balance sheet but the process will continue in the background. In June, the maximum run-off per month will remain unchanged at $30bln ($18bln Treasury/$12bln MBS).
Due to a steady upward drift of the effective Federal Funds rate within the trading band, the Committee made a technical adjustment to ensure the actual rate continues to trade in the middle of the 1.75 – 2% band. They did this by raising the lower end of the band (the rate on the Fed’s overnight reverse repo facility) by 25bps while only raising the upper end of the band (the interest rate on excess reserves held at the Fed by 20bps). This technical shift will likely not occur again, at least in the near term, and does not reflect a change in the stance of monetary policy.
We can break the statement into three parts:
There were no dissenters.
Summary of Economic Projections
Investors had priced in nearly 100% probability of a rate hike at this meeting, so the SEPs and the “Dot Plot” took on greater importance. Within the projections, the growth forecasts were mostly unchanged at this meeting after being upgraded to incorporate fiscal stimulus in prior meetings. The inflation forecasts were also mostly unchanged, with the exception of an upgrade to headline PCE in 2018 due to higher energy. The median forecast of core PCE continues to show a small overshoot above the Fed’s target in 2019 & 2020. The unemployment rate estimates were cut in 2018, 2019 and 2020, but remained unchanged in the long-run. The median dots increased in 2018 to a total of 4 hikes, as one member of the Committee increased their expectations. The 2019 median increased in parallel to the 2018 dot reflecting an additional 3 rate hikes next year. The 2020 and Long-run dots were unchanged.
Chair’s Press Conference
Chairman Powell made several announcements during the press conference. He signaled that every FOMC meeting would be followed by a press conference starting in January 2019. He projected confidence in the growth outlook. He explained that some of the communication provided by the FOMC during the financial crisis and the early recovery was less necessary as policy had moved away from the zero lower bound and normalization has gotten well underway. The Chair downplayed concerns around the lack of wage pressure, suggesting that while surprising, it was not abnormal and also downplayed the risk that inflation would accelerate much higher from here. The Chair emphasized that the adjustment to IOER was a technical factor. Regarding the Dots, the Chair stressed that the rise in 2018 should not be viewed too far out of context and that the shifts in the median forecasts were relatively small.