How news and its context drive risk and returns around the worldCharles W. Calomiris, Harry Mamaysky2019-03-12articleJournal of Financial Economics240 citationsclosedNo readable copy stored yet — this record is metadata only.Financial Markets and Investment StrategiesFinancial Risk and Volatility ModelingStock Market Forecasting MethodsAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 240 citations exist upstream.References1998Law and Finance2016Measuring Economic Policy Uncertainty*1981Biases in Dynamic Models with Fixed Effects2011When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks2007Giving Content to Investor Sentiment: The Role of Media in the Stock Market1969The Adjustment of Stock Prices to New Information1988Dividend yields and expected stock returns2007Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy?Cited by2024Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis2021A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news2020Anomalies and the Expected Market Return2020Social Media Sentiment in International Stock Returns and Trading Activity2020Taper Tantrums: Quantitative Easing, Its Aftermath, and Emerging Market Capital Flows2024Sentiment trading with large language models2022Machine learning methods in finance: Recent applications and prospects2023The impact of climate policy uncertainty on ESG performance, carbon emission intensity and firm performance: evidence from Fortune 1000 firms