An agent-based model of intra-day financialmarkets dynamics
Abstract
We build an agent-based model of a financial market that is able to jointly reproduce many of the
stylized facts at different time-scales. These include properties related to returns (leptokurtosis,
absence of linear autocorrelation, volatility clustering), trading volumes (volume clustering,
correlation between volume and volatility), and timing of trades (number of price changes,
autocorrelation of durations between subsequent trades, heavy tail in their distribution, order-side
clustering). With respect to previous contributions we introduce a strict event scheduling borrowed
from the EURONEXT exchange, and an endogenous rule for traders participation. We show that
such a rule is crucial to match stylized facts.
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