This article analyzes the manifold situations in which the efficient-market hypothesis (EMH) has influenced — or has failed to influence — federal securities regulation and state corporate law, and the prospective roles for the EMH in these contexts. In federal securities regulation, the EMH...

We identify all return leader-follower pairs among individual stocks using Granger causality regressions. Thus-identified leaders can reliably predict their followers' returns out of sample, and the return predictability works at the level of individual stocks rather than industries. Our results...

We propose a methodology for forecasting the systemic impact of financial institutions in interconnected systems. Utilizing a five-year sample including the 2008/9 financial crisis, we demonstrate how the approach can be used for timely systemic risk monitoring of large European banks and...

We show that realized volatility, especially the realized volatility of financial sector stock returns, has strong predictive content for the future distribution of market returns. This is a robust feature of the last century of U.S. data and, most importantly, can be exploited in real time....

I construct an estimable statistic that predicts whether a financial innovation will spread. The approach embeds the multi-host SIR model from epidemiology within a financial model of correlated securities trade; and takes advantage of the related predictive tools from mathematical epidemiology,...

We develop an adaptive learning game to rethink efficient markets. We use the stochastically stable state of this game, which is a mixed Nash equilibrium, to form an adaptive expectation model that provides an estimate of the confidence interval for prices on the next day. The estimate is most...

We find that an increase in the ``unusualness'' of news with negative sentiment predicts an increase in stock market volatility. Similarly, unusual positive news forecasts lower volatility. Our analysis is based on more than 360,000 articles on 50 large financial companies, published in...

In this study, we apply a rolling window approach to wavelet-filtered (denoised) S&P500 returns (2000–2020) to obtain time varying Hurst exponents. We analyse the dynamics of the Hurst exponents by applying statistical tests (e.g., for stationarity, Gaussianity and self-similarity), a...