Microstructure Models with Short-Term Inertia and Stochastic Volatility
Partially observed microstructure models, containing stochastic volatility, dynamic trading noise, and short-term inertia, are introduced to address the following questions: (1) Do the observed prices exhibit statistically significant inertia? (2) Is stochastic volatility (SV) still evident in the p...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2015-01-01
|
| Series: | Mathematical Problems in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2015/323475 |
| Summary: | Partially observed microstructure models, containing stochastic volatility, dynamic
trading noise, and short-term inertia, are introduced to address the following questions:
(1) Do the observed prices exhibit statistically significant inertia? (2) Is
stochastic volatility (SV) still evident in the presence of dynamical trading noise? (3)
If stochastic volatility and trading noise are present, which SV model matches the
observed price data best? Bayes factor methods are used to answer these questions
with real data and this allows us to consider volatility models with very different
structures. Nonlinear filtering techniques are utilized to compute the Bayes factor
on tick-by-tick data and to estimate the unknown parameters. It is shown that
our price data sets all exhibit strong evidence of both inertia and Heston-type
stochastic volatility. |
|---|---|
| ISSN: | 1024-123X 1563-5147 |