Published

September 2022

Author

Tracking benchmarks has never been easy for fixed income managers. The size of the investable universe, structural complexity and lack of liquidity are just some of the challenges of fixed income benchmarking. Critically, the cost of tracking monthly index rebalances means portfolio managers are at a disadvantage even if they perfectly mimic the index. This is because fixed income indices have traditionally not incorporated the full extent of trading costs. Now, a new index methodology is addressing this hurdle - and ultimately, helping reduce tracking error.

For a passive portfolio manager, a key objective is to track their benchmark as closely as possible (minimize tracking error) which includes the monthly rebalance of index constituents. Generally, there are five catalysts for a bond’s weight to change when an index is rebalanced. These include newly issued bonds, ratings changes, corporate actions, the passage of time and changes in alternative data, including ESG data and scores.

To track an index, passive managers must buy and sell the rebalanced bonds each month. Most indices use bid side bond prices for calculating index values. Therefore, bonds with declining weights already include theoretical transaction costs, as their exiting portion leaves the index at the bid price, which is presumably where a portfolio manager would also exit their position.

When bonds increase their weight, indices typically incorporate transaction costs only for new issues. They do this by adding newly issued bonds at the offer price, giving a nod to the real-world transaction costs for a portfolio manager. However, these methodologies do not incorporate trading costs for bonds with increasing weights due to ratings changes, corporate actions, maturity bands or alternative data changes. Unfortunately, the portfolio manager will have to acquire this additional bond exposure on the offer side, while the index will add exposure at the bid side. In mathematical terms, this would be considered an unfair game - making it very difficult for passive managers to closely track an index with minimal cost.

ICE Data Indices recently enhanced its fixed income methodology to incorporate all the aforementioned transaction costs. In plain terms, this means that all increasing bond weights are added to the index on the offer side. Based on historical pro forma data, the significance of this change is ~5 bps of performance per year for the ICE BofA US Corporate Index and ~10 bps per year for ICE BofA US High Yield Index. Indices with lower liquidity profiles and/or higher turnover would see an even greater impact on performance.

ESG is a case in point. While ESG indices have grown in popularity, the impact to rebalancing due to changing ESG scores is less discussed. Given the opacity around ESG scores, these indices often have greater turnover relative to typical market cap weighted indices, which raises the cost of tracking an ESG benchmark. This means a fixed income index that attempts to replicate all the real-world costs of trading is a welcome addition to ESG bond indexing. Likewise, tracking custom weighted indices, even simple fixed-weight blends, can lead to higher turnover and consequently higher cost.

The reputation of a passive portfolio manager relies on their ability to closely track an index. Amid robust demand for passive strategies, incorporating transaction costs takes us one step closer to making bond indexing a fair game.