This paper documents significant cross-return predictability of news variables, derived from textual analysis of news articles, for a broad cross-section of currencies. By employing forecasts based on the Least Absolute Shrinkage and Selection Operator (LASSO) that incorporate both news variables and forward discounts, we develop a notably profitable trading strategy. This strategy proves robust against transaction costs, risk adjustments, and controls for currency characteristics. Further analyses indicate that both risks and market frictions contribute to the profitability of the trading strategy, highlighting the crucial role of news in financial markets.

This study investigates the impact of heightened investor attention on stock price manipulation. To establish causality, we employ daily repeated quasi-natural experiments, where investors’ attention is influenced exogenously by price rounding rather than by stocks’ fundamental information. Our findings demonstrate that stocks included in the Winner List attract significant investor attention, which leads to increased stock price manipulation. A two-stage channel analysis reveals that this increased investor attention exacerbates stock price manipulation through noise trading. Moreover, the positive relationship between investor attention and stock price manipulation is more pronounced in stocks with higher firm-specific information asymmetry, fewer rational investors, weaker external monitoring, higher costs of arbitrage, and non-shortability. Additional analyses indicate that this positive relationship intensifies during periods of heightened investor sentiment, greater economic policy uncertainty and increased geopolitical risk. Our study provides original evidence that the saliency of information exacerbates stock price manipulation and destabilizes financial markets.