Factor investing & smart beta: Advances in factor-based fixed income indices
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Global fixed income investors have benefited from a long bull market that began in the early 1990s. During that time broad market value-weighted benchmark indices that guided most investment policy portfolios enjoyed remarkable returns.
While these indices remain at the centre of asset allocation policy portfolios, some investors have been seeking new alternatives as this phase of the interest rate cycle seems to be drawing to an end. Recent research has led to a few different methods of constructing alternative-weighted indices.
The search for income
In the post-financial crisis period of depressed yields many investors have been seeking additional income. The global family of Bloomberg Barclays Enhanced Yield Bond indices focuses on dynamically managing interest rates and credit risk factor exposures to enhance the yield relative of a benchmark index.
Risk factors are useful for understanding portfolio exposures, but one cannot invest directly in factors. Investors need to determine which securities to over- or underweight to alter their portfolios’ factor exposures. Rather than re-weighting individual bonds, we group bonds into ‘buckets’ based on their primary risk characteristics – asset class, maturity and credit quality – and then vary the weights of the buckets relative to the benchmark. The bonds within each bucket remain market value-weighted. Launched in July 2018, the Euro Aggregate Enhanced Yield index (the index), for example, re-weights sub-components of the Euro Aggregate Bond index (the benchmark) such that yield is maximised while primary risk characteristics are preserved.
The buckets are chosen to allow for meaningful yield and risk factor differentials while ensuring size and liquidity for trading. Up- or downsizing the weights of buckets, instead of individual bonds, could have two additional benefits. Forecasted risk is more reliable and turnover and index replication is easier to manage.
Since the relative attractiveness of interest rates and credit risk varies over time, the buckets are re-weighted monthly to maximise yield while controlling tracking error volatility to the benchmark. In back-tested performance from November 2002 to August 2018, the index achieved a higher yield (0.57% on average) and higher total return (4.73% annualised) than the benchmark (4.26%) with commensurately higher risk (4.11% versus 3.33% annualised volatility respectively). This index would underperform the benchmark in sub-periods of rising interest rates or widening credit spreads. However, it offers investors a means to vary exposures to duration and spread in a systematic and controlled manner to capture yield in the most risk-efficient manner.
Risk parity in fixed income
Traditional ‘beta’ fixed income indices embed several distinct systematic risk factors, such as interest rates, credit and prepayment risk. These factors have associated risk premia and passive long-term investors aim to harvest all three via investments in these indices.
Over the past three decades, the risk-adjusted returns that are attributable to interest rates risk exposure in these indices were much higher than those from credit- or mortgage-spread risk exposures. This served passive benchmark investors very well since these benchmarks are dominated by exposure to interest rates risk. However, past performance is not necessarily indicative of future returns. Thus, absent strong views on factors’ future performance, establishing better risk diversification across risk premia factors is a sensible allocation strategy. The Bloomberg Barclays US Fixed Income Balanced Risk (FIBR) index seeks to balance interest rates and spread risk exposures. It also aims to benefit from the addition of the low volatility and high yield factors.
The FIBR index assigns equal excess return volatility-weights to buckets comprised of investment grade and high yield corporate bonds and agency mortgage backed securities. It then estimates the overall exposure of interest rates and spread risk in the portfolio and adjusts the former to equal the latter. Rebalanced monthly, and launched in February 2015, this alternative to a benchmark such as the US Universal Bond index (US Universal) is designed to offer balanced interest rates and spread risk using a systematic, rules-based approach.
While FIBR had lower total returns over a back-test from January 1992–August 2018 (5.28% annualised versus 5.66% for the US Universal), balancing interest rates and spread risk exposures in FIBR led to better risk diversification and lower realised volatility (2.57% annualised volatility versus 3.49%). Furthermore, FIBR outperformed during periods of rising interest rates (17bps/month total return versus 3bps/month). Over the entire back-tested period, FIBR had a higher Sharpe ratio than the US Universal (0.92 versus 0.78).
While deviating significantly from market value-weights may not be possible for all investors, certain investors may find balanced-risk indices appealing. It would be of interest to investors seeking to tactically reduce interest rates exposure as well as to investors who believe that in the long run indices with balanced exposures to multiple risk premia will deliver better risk-adjusted returns than indices with concentrated interest rates risk exposures.
Corporate bond factors
While our approach to credit style investing is guided by common equity styles, we make necessary adjustments to account for important differences between the two markets, particularly with regards to portfolio implementation and the liquidity constraints of corporate bonds. Our results provide strong evidence that alternative risk premia (value, low risk, momentum and size) factor-tilted portfolios have higher risk-adjusted returns than market value-weighted benchmarks do. These strategies, when implemented effectively, could deliver significant excess returns which are robust to transaction costs and specific portfolio construction settings over the past two decades.
The value factor assumes the fair value of a bond’s spread can be deduced from its peer group – defined as the set of bonds with similar duration, industry, rating, subordination type and country of issuance. Low risk bonds have historically generated higher risk-adjusted returns than high-risk bonds. We define the low risk factor as a combination of a bond’s systematic and idiosyncratic excess return volatilities. Momentum is predicated on empirical evidence of past winners continuing to outperform past losers. The size factor exploits the outperformance of small companies. While we recognise that size captures an illiquidity effect, we argue that the premium it offers holds even after accounting for the higher transactions costs that these bonds incur.
Our analysis and results are conducted and presented on excess returns over duration-matched Treasuries. This removes the interest rates premium and isolates the returns due to credit risk. The historical excess return Sharpe ratios for value (0.70), low risk (0.65), momentum (0.53) and size (0.43) were higher than the European Investment Grade benchmark index’s (0.24) over the past 16 years. After conservatively accounting for transaction costs, all the factors’ Sharpe ratios, with the exception of momentum, remain higher than that of the benchmark index.
Zarvan Khambatta, CFA, CAIA, is responsible for systematic strategies, and Amine El Khanjar for portfolio modelling at Bloomberg