New York Times (February 5)
“A sense of foreboding,” carried over from the pandemic, remains shared by many Americans. Though this “sense of insecurity has seeped into the crevices of everyday experience,” it increasingly seems to “conflict with data points that reflect an unambiguous strengthening of the American economy. Incomes have risen, unemployment remains low and consumer confidence is improving.”
Tags: Conflict, Data points, Economy, Everyday, Foreboding, Incomes, Insecurity, Pandemic, Strengthening, U.S., Unemployment
Institutional Investor (May 30)
Firms “are doubling down on machine learning and other quantitative investing efforts.” More advanced than rule-based algorithms, “with machine learning, a computer sifts through billions of data points, picking up patterns. Armed with this knowledge, it learns trading behaviors such as buying dips or selling high over time, based on what it has gleaned about the market from past and present data.” Despite the inroads, however, human ingenuity remains essential.
Tags: Algorithms, Computer, Data points, Dip, Firms, Ingenuity, Investing, Machine learning, Market, Patterns, Quantitative, Trading
Institutional Investors (August 15)
“As earnings season winds down, investors around the globe are left to consider how a shifting macro environment will impact different asset classes and geographies.” Fears of a continuing yuan devaluation “will factor into perceptions of nearly all the major data points that will emerge.”
Tags: Asset classes, Data points, Devaluation, Earnings, Geographies, Investors, Macro environment, Yuan
