In fraudulent conveyance cases, plaintiffs allege that by entering into a complex leverage transaction, such as an LBO, a firm’s former owners ensured its subsequent collapse. Proving that the transaction rendered the firm insolvent may allow debtors (or their proxies) to claw back transfers made to former shareholders and others as part of the transaction.

Courts have recently questioned the robustness of the solvency evidence traditionally provided in such cases, claiming that traditional expert analyses (e.g., a discounted flow analysis) may suffer from hindsight (and other forms of) bias, and thus not reflect an accurate view of the firm’s insolvency prospects at the time of the challenged transfers. To address the issue, courts have recently suggested that experts should consider market evidence, such as the firm’s stock, bond, or credit default swap prices at the time of the challenged transaction. We review market-evidence-based approaches for determination of solvency in fraudulent conveyance cases.

We compare different methods of solvency determination that rely on market data. We discuss the pros and cons of these methods and illustrate the use of credit default swap spreads with a numerical example. Finally, we highlight the limitations of these methods.

If securities trade in efficient markets in which security prices quickly impound all available information, then such security prices provide an objective assessment of investors’ views of the firm’s future insolvency prospects at the time of challenged transfer, given contemporaneously available information. As we explain, using market data to analyze fraudulent conveyance claims or assess a firm’s solvency prospects is not as straightforward as some courts argue. To do so, an expert must first pick a particular credit risk model from a host of choices which links the market evidence (or security price) to the likelihood of future default. Then, to implement his chosen model, the expert must estimate various parameter input values at the time of the alleged fraudulent transfer. In this connection, it is important to note that each credit risk model rests on particular assumptions, and there are typically several ways in which a model’s key parameters may be empirically estimated. Such choices critically affect any conclusion about a firm’s future default prospects as of the date of an alleged fraudulent conveyance.

Simply using market evidence does not necessarily eliminate the question of bias in any analysis. The reliability of a plaintiff’s claims regarding fraudulent conveyance will depend on the reasonableness of the analysis used to tie the observed market evidence at the time of the alleged fraudulent transfer to default prospects of the firm.

There is a large body of literature in financial economics that examines the relationship between market data and the prospects of a firm’s future default. However, there is surprisingly little research tying that literature to the analysis of fraudulent conveyance claims. Our paper, in part, attempts to do so. We show that while market-based methods use the information contained in market prices, this information must be supplemented with assumptions and the conclusions of these methods critically depend on the assumption made.