Pietro Terna wrote:
Some patterns seem to emerge just from the trading rules.
*********
Just to be clear, in this case the `trading rules' were not agent
behaviors. The agents behaviors were assumed to be random, and the
market mechanism, an order book, itself was modeled in a realistic way.
This type of analytical model explained around 70% of the variance
in the spread of book prices as a function of a set time-aggregated
measurements from historical London Stock Exchange data -- different
subsets of millions of observations per different stocks. Delving
into the ecology of agents wasn't necessary.
This is in contrast to the approach of building up a simulation
model like ASM and expecting to reproduce global phenomena from
different ensembles and parameterizations of agent behaviors. I
don't doubt there are situations where it is useful to do employ the
synthetic ASM approach, but if an explanations seems simple from
theory or data mining, perhaps it just is?
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