Academic Research
Paul Cadman Research
Professor Paul Cadman’s research sits at the intersection of law, markets, and decision-making. His work looks at how legal risk, public attention, and information flows shape behaviour across firms, industries, and investors. He is particularly interested in class actions, reputational dynamics, and how uncertainty travels through markets. He uses real-time data and applies empirical methods to test where risk concentrates, how it spreads, and what it means for capital allocation.
Broad research interests
- Litigation risk and corporate behaviour
- Class actions and collective redress
- Market reactions to regulatory and legal change
- Attention, media salience, and information demand
- Reputation and trust as economic drivers
- Information spillovers across firms and industries
- Risk transmission, contagion, and connectedness
- Forecasting and early warning indicators for decision makers
- Corporate governance, accountability, and stakeholder outcomes
Working Papers
The paper is now available on SSRN. Download and read it here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6189438
We study whether class action litigation attention contains forward-looking information for stock returns and whether it is associated with cross-industry spillovers. We construct a litigation attention index from Google Trends search activity related to class action lawsuits and examine its predictive content for next-month market and industry portfolio returns. Our forecasting design follows standard practice in the return predictability literature. We estimate expanding-window predictive regressions, compare forecasts to an expanding historical mean benchmark, and evaluate performance using out-of-sample R-squared and the Clark-West test for nested forecast comparisons.
[2] Measuring Uncertainty in the Small Firm Economy: Evidence from the UK Small-Cap Market. The paper is now available on SSRN. Download and read it here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6614018
Uncertainty is central to many areas of entrepreneurship, from investment, hiring, and financing decisions, yet most widely used uncertainty proxies are macro wide or policy focused and often reflect the behaviour of large listed firms. This paper constructs a small-firm equity-uncertainty index for the UK using the FTSE Small Cap. The index follows the logic of modern uncertainty measurement: uncertainty is the conditional volatility of outcomes that are hard to forecast, rather than realised volatility of the series itself. Using monthly FTSE SmallCap returns, we first estimate predictable components via an autoregressive model and then measure uncertainty as the volatility of the forecast error. Two operational estimators are produced: a rolling window estimate and an exponentially weighted moving average estimate. The resulting index captures prominent UK and global stress episodes and offers a targeted proxy for uncertainty faced by smaller listed firms. It also differs from popular market wide uncertainty measures, with smaller sensitivity to episodes largely concentrated in large growth equities. The index is easy to update, transparent, and designed to support empirical work on small firm returns, small firm financing conditions, and the broader small business cycle.