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Biden administration officials downplay concerns about drone sightings: 'Slight overreaction'

FOX News

New Jersey State Sen. Jon Bramnick joins'Cavuto Live' to discuss his call for a limited state of emergency over unanswered questions about alleged drone sightings. U.S. national security officials appeared to dispel concerns about the mysterious drones flying over the Northeast in a recent call with reporters, one going as far as describing nationwide uneasiness as "a slight overreaction." The call, attended by Fox News Digital Saturday, was hosted by senior Biden administration officials, including representatives from the FBI, the Federal Aviation Administration (FAA), the National Security Council (NSC), the Department of Homeland Security (DHS) and the Department of Defense (DOD). The senior officials remained tight-lipped about the origins of the drones, which are still being investigated. The mysterious aircraft were first spotted flying above northern New Jersey in mid-November and have been repeatedly seen by thousands of residents over the past few weeks.


Behavioral Machine Learning? Computer Predictions of Corporate Earnings also Overreact

Frank, Murray Z., Gao, Jing, Yang, Keer

arXiv.org Artificial Intelligence

There is considerable evidence that machine learning algorithms have better predictive abilities than humans in various financial settings. But, the literature has not tested whether these algorithmic predictions are more rational than human predictions. We study the predictions of corporate earnings from several algorithms, notably linear regressions and a popular algorithm called Gradient Boosted Regression Trees (GBRT). On average, GBRT outperformed both linear regressions and human stock analysts, but it still overreacted to news and did not satisfy rational expectation as normally defined. By reducing the learning rate, the magnitude of overreaction can be minimized, but it comes with the cost of poorer out-of-sample prediction accuracy. Human stock analysts who have been trained in machine learning methods overreact less than traditionally trained analysts. Additionally, stock analyst predictions reflect information not otherwise available to machine algorithms.