Over the last few years there has been a surge of activity within the physics community
in the emerging field of Econophysics—the study of economic systems from
a physicist's perspective. Physicists tend to take a different view than economists
and other social scientists, being interested in such topics as phase transitions and
fluctuations.
In this dissertation two simple models of stock exchange are developed and
simulated numerically. The first is characterized by centralized trading with a market
maker. Fluctuations are driven by a stochastic component in the agents' forecasts.
As the scale of the fluctuations is varied a critical phase transition is discovered.
Unfortunately, this model is unable to generate realistic market dynamics.
The second model discards the requirement of centralized trading. In this
case the stochastic driving force is Gaussian-distributed "news events" which are
public knowledge. Under variation of the control parameter the model exhibits two
phase transitions: both a first- and a second-order (critical).
The decentralized model is able to capture many of the interesting properties
observed in empirical markets such as fat tails in the distribution of returns, a brief
memory in the return series, and long-range correlations in volatility. Significantly,
these properties only emerge when the parameters are tuned such that the model
spans the critical point. This suggests that real markets may operate at or near
a critical point, but is unable to explain why this should be. This remains an
interesting open question worth further investigation.
One of the main points of the thesis is that these empirical phenomena are not
present in the stochastic driving force, but emerge endogenously from interactions
between agents. Further, they emerge despite the simplicity of the modeled agents;
suggesting complex market dynamics do not arise from the complexity of individual
investors but simply from interactions between (even simple) investors.
Although the emphasis of this thesis is on the extent to which multi-agent
models can produce complex dynamics, some attempt is also made to relate this
work with empirical data. Firstly, the trading strategy applied by the agents in the
second model is demonstrated to be adequate, if not optimal, and to have some
surprising consequences.
Secondly, the claim put forth by Sornette et al. that large financial crashes
may be heralded by accelerating precursory oscillations is also tested. It is shown
that there is weak evidence for the existence of log-periodic precursors but the signal
is probably too indistinct to allow for reliable predictions.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU.2429/11108 |
| Date | 11 1900 |
| Creators | Blok, Hendrik J. |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Relation | UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/] |
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