Incorporating pre-trade bond liquidity data into corporate bond management

The identification of liquidity is a key factor for successful corporate bond management. In this white paper, we show how the incorporation of pre-trade liquidity data into the portfolio construction process provides more precise estimates of tradability, tradable volumes, and transaction costs. It also increases relative portfolio performance.

Quoniam authors Dr Harald Henke, Max Geilen and Tobias Stein, CFA have analysed the value of liquidity information in the management of corporate bond portfolios and how pre-trade information can help obtain better liquidity, tradability, and transaction cost estimates.

Navigating liquidity in the corporate bond market is a challenge for credit managers. Contrary to the equity market, most trading in bonds does not take place on regulated exchanges but in over-the counter (OTC) markets, where buyers of a bond need to find a willing seller and no publicly available limit order book exists. Therefore, investors must identify the existing liquidity in corporate bonds and leapfrog other investors when trading on liquidity.

This study uses sell-side pre-trade information to analyse its effect on the construction process of corporate bond portfolios. In the first section of the paper, we cover liquidity in the corporate bond market in greater detail. Subsequently, we describe the pre-data we use and show their impact on identifying liquidity, tradability, transaction costs, and performance before concluding the paper.

“The inclusion of pre-trade data significantly decreases the share of bonds erroneously classified as untradable. Additionally, a factor portfolio constructed from an investable universe built on both pre- and post-trade data outperforms a portfolio containing only post-trade information.”

Dr Harald Henke,
Head of Fixed Income Strategy

Key ideas in the paper

  • This study analyses the incorporation of pre-trade data into the portfolio-management process for USD IG credit by determining which bonds are tradable, at which size, at which cost, and to which performance effect. For example, we use pre-trade bid and ask axes and incorporate these data into the liquidity determination process.
  • We find that pre-trade data significantly increases the part of the universe that is correctly classified as tradable, adds predictive power to the traded volume, and helps lower the estimation error for transaction costs.
  • A backtest with different liquid universes, including and excluding pre-trade data, to determine the liquid universe yields annual performance differences of up to eight basis points.
  • Information is the key to success, particularly in an opaque OTC market such as the corporate bond market. By incorporating pre-trade data into the investment process, value can be added to corporate bond portfolios. Because systematic strategies profit the most from liquid trading, properly addressing the challenges of identifying liquidity is a decisive feature of quantitative factor strategies.

Read the full Quoniam – White Paper:

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