Develops design-based causal inference methods for spatial treatments using counterfactual candidate locations, extends double ML for spatial correlations, and applies to grocery store effects on foot traffic.
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News embeddings from financial text improve out-of-sample realized volatility forecasts for stocks, with stronger effects for stock-specific news and high-volatility periods, and yield gains when combined with benchmarks.
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Realised Volatility Forecasting: Machine Learning via Financial Word Embedding
News embeddings from financial text improve out-of-sample realized volatility forecasts for stocks, with stronger effects for stock-specific news and high-volatility periods, and yield gains when combined with benchmarks.