Showing 1 - 10 of 11
We propose a one-month market-timing model constructed from 15 diverse variables. We use weighted least squares with stepwise variable selection to build a predictive model for the one-month-ahead market excess returns. From our statistical model, we transform our forecasts into investable...
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Commonality in idiosyncratic volatility cannot be completely explained by time-varying volatility. We decompose the common factor in idiosyncratic volatility (CIV) of Herskovic et al. (2016) into two components: idiosyncratic volatility innovations (VIN) and time-varyingidiosyncratic volatility...
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This paper takes a cross-country and cross-sector perspective to investigate the drivers of commodity momentum strategies. Commodity momentum strategies deployed in the U.S. and Chinese markets generate positive average returns with non-negligible correlations, but their premia are primarily...
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Size, value, and momentum are well known common factors to stock returns. I document size, value, and momentum premiums in industries are strongly correlated with themselves across industries. The correlation structures indicate strong common factor structure at the industry level. The strong...
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We introduce a novel application of support vector machines (SVM), an important machine learning algorithm, to determine the beginning and end of recessions in real time. Nowcasting, forecasting a condition in the present time because the full information will not be available until later, is...
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