New findings on currency and equity return drivers

This thesis brings together three empirical studies that examine what drives returns in currency and U.S. equity markets. The first essay breaks down the predictable influence of economic fundamentals on currency returns, showing that cross-sectional signals are more consistently informative and that many fundamentals jointly matter when combined in a Bayesian average.

The second essay finds that a volatility-based currency premium forecasts future currency appreciation and excess returns, especially at longer horizons, and links this premium to periods of macroeconomic distress. The third essay proposes a new equity risk factor based on how much market value can be recovered in bankruptcy, documenting a clear inverse relation between this recovery rate and later risk-adjusted returns.

What the study examined

This work collects three empirical essays that explore determinants of returns in currency and equity markets. The first part investigates how macroeconomic fundamentals help predict currency returns, separating the predictive power into cross-sectional signals and a Dollar-related component.

The second part looks at a volatility-based currency premium and its ability to predict future currency movements and excess returns over time. The third part introduces a new equity cross-sectional measure, the equity recovery rate, defined as the fraction of market equity expected to be recovered in bankruptcy, and examines its relation to future returns.

Key findings

• Currency fundamentals: Predictability from fundamentals can be decomposed into a cross-sectional component that is more robust and a Dollar component. When many fundamentals are combined using a Bayesian averaging approach, a dense pricing relation emerges in which many variables each contribute noisy information.
• Bayesian averaging improves pricing: An aggregated Bayesian Model Averaged pricing relation shows better out-of-sample pricing performance than simpler, more parsimonious models, suggesting value in combining information rather than relying on a single indicator.
• Volatility premium and forecasts: The Currency Volatility Risk Premium (VRP) and its term structure significantly forecast currency appreciation and excess returns, with stronger predictive power at longer horizons. This premium is associated with macroeconomic distress, indicating it may compensate investors for bearing risk in bad states.
• Equity recovery rate: The newly proposed recovery-rate measure has a robust, inverse relationship with subsequent risk-adjusted returns in U.S. equities. This relation appears distinct from compensation for leverage, standard distress measures, and other known factors.

Why it matters

The three essays together highlight that multiple sources of information matter when explaining returns across markets. Combining many weak signals with a formal averaging procedure can reveal a more complete pricing picture than focusing on a single variable.

The link between a volatility-based premium and macroeconomic distress provides evidence that compensation varies with economic conditions. Introducing the equity recovery rate offers a new dimension for understanding cross-sectional differences in stock returns, separate from traditional measures of distress or leverage.

Overall, the findings emphasize the value of integrating diverse signals and careful statistical aggregation to better describe patterns in market returns.