Agent-Based Simulations of Monetary Policy and Financial Markets
My PhD Thesis on Agent-Based Modelling.
This thesis contributes to the fields of monetary policy and financial market research by applying one of the most popular of emerging methodologies in economics, agent-based modelling (ABM), to four distinct research questions. ABM is a class of computer models in which the interactions of autonomous agents are simulated over time. In this thesis, I use ABMs to study the following questions. (1) How do central bank interest rate changes affect inflation in the short term? (2) Is it plausible that stock prices have become decoupled from their fundamental value? (3) How does stock market volatility affect wealth inequality? (4) How can central bank balance sheet policy best be used to stabilise asset prices? ABM simulations yield the following main results. (1) Interest rate changes have a small effect on inflation because interest rate pass-through to costs, consumption, investment, and bank lending is rather weak. (2) When simple mean-reversion trading strategies start eclipsing fundamentalist strategies, stock prices can start to deviate from their fundamentals, this would be hard to detect using the standard stock price statistics. (3) Stock trading tends to lead to a highly unequal state as the wealth of more and more traders becomes so low that they have to stop trading. Increasing price volatility accelerates the movement towards this state. (4) The central bank can stabilise asset prices without disturbing the average price if it commits to buying stocks that are too far below fundamental value and selling stocks that are too far above it.
This Thesis was
- supervised by professor Dirk Bezemer and professor Lex Hoogduin;
- evaluated by professors Thomas Lux, Jakob de Haan, and Cars Hommes;
- published by the University of Groningen