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  Using Past Violence and Current News to Predict Changes in Violence 

  Mueller, H.; Rauh, C. (Faculty of Economics, University of Cambridge, 2022-03-22)

  This article proposes a new method for predicting escalations and de‐escalations of violence using a model which relies on conflict history and text features. The text features are generated from over 3.5 million newspaper ...
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  Forecasting with panel data: estimation uncertainty versus parameter heterogeneity 

  Pesaran, M. H.; Pick, A.; Timmermann, A. (Faculty of Economics, University of Cambridge, 2022-03-21)

  We develop novel forecasting methods for panel data with heterogeneous parameters and examine them together with existing approaches. We conduct a systematic comparison of their predictive accuracy in settings with different ...
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  Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data 

  Bu, R.; Li, D.; Linton, O.; Wang, H. (Faculty of Economics, University of Cambridge, 2022-03-16)

  In this paper, we consider estimating spot/instantaneous volatility matrices of high-frequency data collected for a large number of assets. We first combine classic nonparametric kernel-based smoothing with a generalised ...
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  In platforms we trust: misinformation on social networks in the presence of social mistrust 

  Charlson, G. (Faculty of Economics, University of Cambridge, 2022-01-12)

  We examine the effect social mistrust has on the propagation of misinformation on a social network. Agents communicate with each other and observe information sources, changing their opinion with some probability determined ...

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