We propose a regression-based method for combining analyst forecasts to improve forecasting efficiency. This significantly reduces the bias in earnings forecasts, and generates that consistently outperform consensus over time across firms of different characteristics. Incorporating firm-level macroeconomic information model further improves performance. Forecasting gains increase with dispersio...

Abstract We show that analyst behavior changes in response to a randomly assigned shock exogenously varies the timeliness and cost of accessing mandatory disclosures cross-section investors: analysts reduce coverage issue less optimistic, more accurate, bold, informative forecasts. Our evidence indicates strategic component their behavior: are stronger among with incentives like affiliated or r...

In this work we undertake the creation of a framework for testing the degree to which network intrusion detection systems (NIDS) detect and handle evasion attacks. Our prototype system, idsprobe, takes as input a packet trace and from it constructs a configurable set of variant traces that introduce different forms of ambiguities that can lead to evasions. Our test harness then uses these varia...