with Alexander Dickerson and Yoshio Nozawa, 2024, working paper.
[Paper] We introduce a novel framework for computing the transaction costs of trading strategies in
the infrequently traded corporate bond market. Infrequency leads to delays and missed trading
opportunities, which reduce the performance of the strategies. To quantify the cost of
delays, we consider counterfactuals by replacing inactive investors in the data with active investors
and estimate how frequently the securities would have been traded. The counterfactuals
are constructed by modeling the liquidity supply function of dealers and the liquidity
demand functions of customers and by shifting the demand curve. This framework allows us
to estimate the delay and bid-ask spreads for active factor investors trying to trade bonds immediately.
Applying this method to a comprehensive library of 341 corporate bond factors in
openbondassetpricing.com, we demonstrate that momentum-like strategies underperform due
to high turnover rates. Notably, even advanced machine learning-based trading strategies that
optimally combine the 341 factors yield zero or negative bond CAPM alphas after accounting for
transaction costs. Our findings underscore the critical impact of delay costs in illiquid securities
and provide valuable insights for factor investing in corporate bond markets.