Complex Phenomena in Social and Financial Systems: From Bird Population Growth to the Dynamics of the Mutual Fund Industry

Citation

Schwarzkopf, Yonathan (2011) Complex Phenomena in Social and Financial Systems: From Bird Population Growth to the Dynamics of the Mutual Fund Industry. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/6Y9G-WM75. https://resolver.caltech.edu/CaltechTHESIS:08112010-110422842

Abstract

This work explores different aspects of the statics and dynamics of the mutual fund industry. In addition, we answer a major question in the field of complex systems; the anomalous growth fluctuations observed for systems as diverse as breeding birds, city population and GDP.

We study how much control is concentrated in the hands of the largest mutual funds by studying the size distribution empirically. We show that it indicates less concentration than, for example, personal income. We argue that the dominant economic factor that determines the size distribution is market efficiency and we show that the mutual fund industry can be described using a random entry, exit and growth process.

Mutual funds face diminishing returns to scale as a result of convex trading costs yet there is no persistence nor a size dependence in their performance. To solve this puzzle we offer a new framework in which skillful profit maximizing fund managers compensate for decreasing performance by lowering their fees. We show that mutual fund behavior depends on size such that bigger funds charge lower fees and trade less frequently in more stocks. We present a reduced form model that is able to describe quantitatively this behavior.

We conclude with an investigation of the growth of mutual funds due to investor funds flows. We show that funds exhibit the same unusual growth fluctuations that have been observed for phenomena as diverse as breeding bird populations, the size of U.S. firms, the GDP of individual countries and the scientific output of universities. To explain this we propose a remarkably simple additive replication model. To illustrate how this can emerge from a collective microscopic dynamics we propose a model based on stochastic influence dynamics over a scale-free contact network.

Thesis Files