The investment industry has evolved dramatically over the last several decades and continues to do so amid increased competition, technological advances, and a challenging economic environment. This section will review several key trends that have shaped the investment environment in general, and the context for algorithmic trading more specifically, and related themes that will recur throughout this book.

The trends that have propelled algorithmic trading and ML to current prominence include:

• Changes in the market microstructure, such as the spread of electronic trading and the integration of markets across asset classes and geographies
• The development of investment strategies framed in terms of risk-factor exposure, as opposed to asset classes
• The revolutions in computing power, data-generation and management, and analytic methods
• The outperformance of the pioneers in algorithmic traders relative to human, discretionary investors

In addition, the financial crises of 2001 and 2008 have affected how investors approach diversification and risk management and have given rise to low-cost passive investment vehicles in the form of exchange-traded funds (ETFs). Amid low yield and low volatility after the 2008 crisis, cost-conscious investors shifted $2 trillion from actively-managed mutual funds into passively managed ETFs. Competitive pressure is also reflected in lower hedge fund fees that dropped from the traditional 2% annual management fee and 20% take of profits to an average of 1.48% and 17.4%, respectively, in 2017.