Quantitative Tightening

Quantitative trading, also known as quant trading or algorithmic trading, represents a data-driven approach to financial markets. Utilizing mathematical models, statistical analysis, and computer algorithms, quantitative trading aims to make objective trading decisions relying on predetermined rules rather than human judgment. In this enlightening discourse, we delve into the intricate workings of quantitative trading, deciphering its core components and unveiling its inner mechanisms.

During the pandemic alone, the U.S. Federal Reserve bought a whopping $3.3 trillion in Treasury bonds and $1.3 trillion in mortgage-backed securities to lower borrowing costs. The reverse process, quantitative tightening (QT), where central banks reduce balance sheets, is much rarer. The Fed is the only central bank that has actually made such an attempt, but it had to stop abruptly in 2019 because of market turmoil. So the asset reduction plan would take the central bank into relatively uncharted territory.