Using virtual stock markets with artificial interacting software investors, aka agent-based models (ABMs), we present a method to reverse engineer real-world financial time series. We model financial markets as made of a large number of interacting boundedly rational agents. By optimizing the...

We present a detailed synthesis of the development of the Human Genome Project (HGP) from 1986 to 2003 in order to test the “social bubble” hypothesis that strong social interactions between enthusiastic supporters of the HGP weaved a network of reinforcing feedbacks that led to a widespread...

We introduce the concept of “negative bubbles” as the mirror image of standard financial bubbles, in which positive feedback mechanisms may lead to transient accelerating price falls. To model these negative bubbles, we adapt the Johansen-Ledoit-Sornette (JLS) model of rational expectation...

We review the “social bubble” hypothesis, which holds that strong social interactions between enthusiastic supporters of new ventures weave a network of reinforcing feedbacks that lead to a widespread endorsement and extraordinary commitment by those involved in the projects, beyond what...

Using a recently introduced method to quantify the time varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be...

Following Levy and Roll [2010], we posit that the market portfolio is the efficient tangent Markowitz portfolio, i.e., it is mean-variance efficient. We then reverse engineer the expected returns and variance terms with constraints imposed by empirical data on a hierarchy of asset baskets. This...