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
New York Times (April 19)
“Civilization’s understanding of Earth has expanded enormously in recent decades, making humanity safer and more prosperous.” But a new “dark age is a growing possibility” as our ability to predict future weather patterns is disrupted by climate change. Without the ability to accurately forecast long-term phenomena, “we will face huge challenges feeding a growing population and prospering within our planet’s finite resources.”
Tags: Challenges, Civilization, Climate change, Dark age, Disrupted, Earth, Forecast, Humanity, Patterns, Population, Predict, Prosperous, Resources, Weather
CFO.com (October Issue)
“After years of treating Big Data almost exclusively as a way to aid marketers and drive revenue, companies are starting to explore its risk management capabilities. Increasingly, they’re looking for patterns in their internal emails and audio files and on social media to spot and avert a plethora of potential risks.”
Tags: Audio files, Big Data, Capabilities, Emails, Marketers, Patterns, Revenue, Risk management, Social media
