Publications

Construction, Real Uncertainty, and Stock-Level Investment Anomalies (with K. Aretz) Journal of Financial and Quantitative Analysis, forthcoming.

We show that the negative relation between real investments and future stock returns is primarily driven by the subsample of firms building additional capacity. We develop a real options model to rationalize that evidence based on the premise that firms need to learn how to best operate modern capacity vintages, inducing idiosyncratic uncertainty in that capacity’s production costs over the learning period. Conversely, the uncertainty lowers the expected return of firms with newly-built capacity until it is resolved. Further evidence based on profit sensitivities to aggregate conditions; analyst forecast-error volatilities; and high-vs.-low tech industry subsamples supports our uncertainty explanation.

Is Firm-Level Political Risk Priced in the Equity Option Market? (with T. Ho and J. Wang) Review of Asset Pricing Studies 14, 153-195, (2024).

We find a negative relation between firm-level political risk and future delta-hedged equity option returns. A quasi-natural experiment based on Brexit corroborates this finding since after the referendum there is a decrease in the option returns of the positive-Brexit exposure firms. The predictability is driven by the jump risk component of political uncertainty, is more pronounced in periods of high intermediary constraints and is stronger among high-demand pressure options but weaker among politically active firms. Finally, consistent with a risk-based explanation, investors of options on politically risky firms get compensated with high returns when major unexpected political shocks take place.

Factor Timing with Portfolio Characteristics (with I. Nolte, S. Nolte and N. Vasilas) Review of Asset Pricing Studies 14, 84-118, (2024) .

In a factor timing context, academic research has focused on identifying a set of predictors that can explain the dynamics of factor portfolios. We propose an alternative approach for timing factor portfolio returns by exploiting the information from their portfolio characteristics. Different combinations of dimension reduction techniques are employed to independently reduce both the number of predictors and portfolios to predict. Characteristic-based models outperform existing methods in terms of exact predictability, as well as investment performance. 

Dispersion in Options Investors' versus Analysts' Expectations: Predictive Inference for Stock Returns (with P. Andreou, P. Maio and D. Philip) Critical Finance Review 10, 65-81, (2021). [Data] [Codes] [SSRN] 

We create a market-wide measure of dispersion in options investors’ expectations by aggregating across all stocks the dispersion in trading volume across moneynesses (DISP). DISP exhibits strong negative predictive power for future market returns and its information content is not subsumed by several alternative equity premium predictors. Consistent with the implications of theoretical models that link dispersion to overpricing, the predictive power of DISP is particularly pronounced in relatively optimistic periods. Although an aggregate analysts’ forecasts dispersion (AFD) measure also performs well in optimistic periods, it delivers insignificant overall predictability. This is because in the aftermath of the 2008 financial crisis, AFD was heavily driven by pessimistic forecasts and hence its increase did not reflect a true overpricing. As a result, AFD does not appear to be a robust equity premium predictor in recent years.

The Information Content of Forward Moments (with P. Andreou, D. Philip and A. Taamouti) Journal of Banking and Finance 106, 527-541, (2019). [Online Appendix] [Data]

We estimate the term structures of risk-neutral forward variance and skewness, and examine their predictive power for equity market excess returns and variance. We use Partial Least Squares to extract a single predictive factor from each term structure that is motivated by the theoretical implications of affine no-arbitrage models. The empirical analysis shows that an increased forward variance factor, FVF (forward skewness factor, FSF) corresponds to a more negatively sloped forward variance (more U-shaped forward skewness) term structure, and significantly forecasts higher future market excess returns and variance. More importantly, FSF exhibits predictive power for market returns that is stronger than, and incremental to, that provided by FVF. However, it does not outperform FVF in terms of excess variance predictability.

Differences in Options Investors’ Expectations and the Cross-Section of Stock Returns (with P. Andreou, D. Philip and R. Tuneshev) Journal of Banking and Finance 94, 315-336, (2018). [Online Appendix] [Data]

We provide strong evidence that the dispersion of individual stock options trading volume across moneynesses (IDISP) contains valuable information about future stock returns. Stocks with high IDISP consistently underperform those with low IDISP by more than 1% per month. In line with the idea that IDISP reflects dispersion in investors’ beliefs, we find that the negative IDISP-return relationship is particularly pronounced around earnings announcements, in high sentiment periods and among stocks that exhibit relatively high short-selling impediments. Moreover, the IDISP effect is highly persistent and robustly distinct from the effects of a large array of previously documented cross-sectional return predictors.