Assessing the relevance of an information source to trading from an adaptive-markets hypothesis perspective

I propose a framework motivated by the Adaptive Markets Hypothesis (AMH) to analyze the relevance of a specific information source for the trading of a given security. To illustrate the applicability and advantages of this methodology, I explore the extent to which the financial statement (FS) is relevant for Credit Default Swap (CDS) trading. Specifically, I adopt a Bayesian Model Averaging approach to examine properties of the accounting metrics that enter the implied trading heuristics of the market participants. Hypothesis-testing is conducted on various horizons around the announcement dates of corporate results. The diversity of trading rules and the shift in the heuristics mix that occurred after 2008 support the AMH perspective. Overall, results show that there is a significant component of profit-motivated trading in the CDS market that relies on financial statement information, even after controlling for information transmission from alternative trading forums. Out of sample trading strategies confirm the robustness the main findings.