Richard M Bookstaber

Market Liquidity and Heterogeneity in the Investor Decision Cycle

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 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. We show that the heterogeneity in decision cycles can increase the severity of market shocks, and even absent a shock can have notable effects on the stochastic properties of market prices.

Information Flows, the Accuracy of Opinions, and Crashes in a Dynamic Network

Markets coordinate the flow of information in the economy, aggregating it through the price mechanism. We develop a dynamic model of information transmission and aggregation in financial and other social networks in which continued membership in the network is contingent on the accuracy of opinions. Agents have opinions about a state of the world and form links to others in a directed fashion probabilistically. Agents update their opinions by averaging those of their connections, weighted by how long their connections have been in the system. Agents survive or die based on how far their opinions are from the true state. In contrast to the results in the extant literature on DeGroot learning, we show through simulations that for some parameterizations the model cycles stochastically between periods of high connectivity, in which agents arrive at a consensus opinion close to the state, and periods of low connectivity in which agents’ opinions are widely dispersed. We add varying degrees of homophily through a model parameter called tribal preference and find that crash frequency is decreasing in the degree of homophily. Our results suggest that the information aggregation function of markets can fail solely because of the dynamics of information flows, irrespective of shocks or news.

A Map of Collateral Uses and Flows

All flows of secured funding in the financial system are met by flows of collateral in the opposite direction. A network depicting secured funding flows thus implicitly reveals a network of collateral flows. Collateral can also be presented as its own network to show collateral arrangements with bilateral counterparties, triparty banks, and central counterparties; the purpose and incentives of collateral exchanges; and participants involved. We create a collateral map to show how this function of the financial system works, especially with secured funding and derivatives activity. This paper provides insights into the increased demand for collateral, the reduced capacity for banks to act as collateral intermediaries, and examples of risks and vulnerabilities in collateral flows.