Order book microstructure and policies for financial stability
Authored by Alessio Emanuele Biondo
Date Published: 2018
DOI: 10.1108/sef-04-2017-0087
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Abstract
Purpose The purpose of this paper is two-fold: first, to introduce an
innovative model of financial order book, less simplified than the
existing literature and still able to replicate all statistical features
of true markets; second, to simulate realistically the effects of
policies aimed to reduce the instability of financial markets.
Design/methodology/approach The paper is based on an agent-based model
and the applied methodology is the computational simulation.
Findings The policymaker can actively reduce the instability of
financial market by means of policies aimed to increase the
heterogeneity of investors, both in terms of the behavioral attitude for
market participation and of the differentiation of opinions; favor
investors who show insensibility with regard to market information;
limit the allowed number of counterparts for any market order; reduce
the time validity of orders; and maintain flexibility and efficient
bargaining, reduce transaction costs and avoid Tobin taxes.
Research limitations/implications In future research, an opinion
dynamics engine within a clustered community network will be embedded.
Practical implications Indeed, the obtained results are policy rules
which could be immediately applied.
Originality/value The order book model contained in the paper is
completely new, innovative and original. Innovativeness is based on a
reduced number of simplifying assumptions. The realism of the presented
mechanism is higher than in other existing models. The value of the
model is high because of several factors. From the scientific point of
view, it constitutes the reliable framework on which many other papers
will be based: it is the core center of future research. From the
policymaker's point of view, it represents a credible tool for policy
hypotheses testing.
Tags
Agent-based models
financial markets
fat tails
herd behavior
Price dynamics
Risk
Model
Volatility
Order book
financial instability
Fluctuations
Stock-market
Traders
Stress
Computational simulations