Abstract: This study addresses a critical regulatory shortfall by developing a platform to extend stress testing from a microprudential approach to a dynamic, macroprudential approach. This paper describes the ensuing agent-based model for analyzing the vulnerability of the financial system to asset- and funding-based fire sales. The model captures the dynamic interactions of agents in the financial system extending from the suppliers of funding through the intermediation and transformation functions of the bank/dealers to the financial institutions that use the funds to trade in the asset markets. The model replicates the key finding that it is the reaction to initial losses, rather than the losses themselves, that determine the extent of a crisis. By building on a detailed mapping of the transformations and dynamics of the financial system, the agent-based model provides an avenue toward risk management that can illuminate the pathways for the propagation of key crisis dynamics such as fire sales and funding runs.
Abstract: During liquidity shocks such as occur when margin calls force the liquidation of leveraged positions, there is a widening disparity between the reaction speed of the liquidity demanders and the liquidity providers. Those who are forced to sell typically must take action within the span of a day, while those who are providing liquidity do not face similar urgency. Indeed, the flurry of activity and increased volatility of prices during the liquidity shocks might actually reduce the speed with which many liquidity providers come to the market. To analyze these dynamics, we build upon previous agent-based models of financial markets, and specifically the Preis et. al (Europhys Lett 75(3):510–516, 2006) model, to develop an order-book model with heterogeneity in trader decision cycles. The model demonstrates an adherence to important stylized facts such as a leptokurtic distribution of returns, decay of autocorrelations over moderate to long time lags, and clustering volatility. Consistent with empirical analysis of recent market events, we demonstrate the impact of heterogeneous decision cycles on market resilience and the stochastic properties of market prices.