Agent-Based Simulations of Monetary Policy and Financial Markets

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

Fundamentals unknown:momentum, mean-reversion and price-to-earnings trading in an artificial stock market

The use of fundamentalist traders in the stock market models is problematic since fundamental values in the real world are unknown. Yet, in the literature to date, fundamentalists are often required to replicate key stylized facts. The authors present an agent-based model of the stock market in which the fundamental value of the asset is unknown. They start with a zero intelligence stock market model with a limit-order-book. Then, the authors add technical traders which switch between a simple momentum and mean reversion strategy depending on its relative profitability. Technical traders use the price to earnings ratio as a proxy for fundamentals. If price to earnings are either too high or too low, they sell or buy, respectively

Monetary Policy Transmission in a Macroeconomic Agent-Based Model

In this paper we explore the variety of monetary policy transmission channels in an agent-based macroeconomic model. We identify eight transmission channels and present a model based on [Caiani et al., J. Econ. Dyn. Contr. 69 (2016) 375–480], extended with an interbank market. We then analyze model simulation results of interest rate shocks in terms of GDP and inflation for four of the transmission channels. We find these effects to be small, in line with the view that monetary policy is a weak tool to control inflation