Although analysis of a single factor and cryptocurrency combination, as above, is of interest, more general findings across multiple cryptocurrency/factor combinations can also be pursued. Fig 7 shows, for each cryptocurrency and factor combination, the mean coherence values during the bubble and non-bubble regimes. Each horizontal subplot shows a different coherence period band, from the lowest period band (2–4 days) at the top to the highest period band (256–512 days) at the bottom. As the duration of data for each cryptocurrency varies, certain ranges are left blank when that cryptocurrency does not have enough data to produce values for such bands.
— In a 1,500-word memo obtained by The New York Times over the weekend, the company’s top lobbyist, Nick Clegg, sought to rebut Haugen’s allegations ahead of her unveiling in an episode of “60 Minutes” on Sunday night. “Social media has had a big impact on society in recent years, and Facebook is often a place where much of this debate plays out,” he said in the memo, in which he called Haugen’s impending accusations, which included blaming Facebook for January’s insurrection at the Capitol, “misleading.” He wrote that “what evidence there is simply does not support the idea that Facebook, or social media more generally, is the primary cause of polarization.”

RIVERHEAD, N.Y. (AP) — An employee cost a New York county at least $6,000 in electricity bills by allegedly secretly installing dozens of machines at his workplace in a cryptocurrency scheme, authorities said Wednesday, announcing charges against him.
More importantly, we find that the ACP and ANET factors can price cryptocurrency returns. In particular, all of our five cryptocurrencies have positive and significant exposures to the fundamental factors. The explanatory power of ACP and ANET is over and above any effects related to the Bitcoin and momentum factors. This finding is non-trivial given that the five cryptocurrencies in our sample have consistently accounted for between 80% to 95% of the total cryptocurrency market capitalisation. Furthermore, we extend our factor analysis to an out-of-sample set of 33 cryptocurrencies obtained from the Bittrex exchange. We find that the aggregate computing power and network factors also price cryptocurrencies in this large out-of-sample data set.