 Next, consider asset pricing theory. Ever since Bachelier’s groundbreaking mathematical treatment of asset pricing, financial economists have struggled to find the best way to determine the price developments of securities such as shares, bonds, and derivative instruments such as options. The mathematics of financial returns has received some attention in the literature (de Bruin &amp; Walter 2017; Ippoliti &amp; Chen 2017). Most models assume that returns follow Gaussian random walks, that is, stochastic processes in discrete time with independent and identically distributed increments. Empirical studies show, however, that returns are more peaked than Gaussian distributions, and that they have “fat tails”. This means that extreme events such as financial crises are far less improbable than the models assume. An exception with regards to these assumptions is Benoît Mandelbrot’s (1963) well-known contribution to financial mathematics, and work in this direction is gaining traction in mathematical finance.