 |
|
Event(s) on April 2006
- 7/4/2006
| 題目: |
A Quick Introduction to Differential Geometry and to Some of Its Applications |
| 講員: |
Professor Philippe G. Ciarlet, Department of Mathematics, City University of Hong Kong, HKSAR, China |
| 時間/地點: |
16:30 - 17:30
NAB209
|
| | |
| 摘要: |
Differential Geometry is often considered as a "classical" field
in Mathematics. Yet it has recently been the object of a substantial
renewed interest, thanks in particular to various applications
where it plays an essential role.
After a quick review of some basic notions of Differential Geometry,
such as the fundamental forms of a surface or the fundamental
theorem of surface theory, some applications - old and new -
will be likewise briefly reviewed, such as cartography, the theory
of elastic shells, or the optimization of the shape of gears.
This lecture is intended for undergraduate and graduate students.
No a priori knowledge of Differential Geometry will be assumed.
|
- 11/4/2006
| 題目: |
Implied Volatility Modelling and Skew Hedging |
| 講員: |
Profs. Hrdle & Borak, Center for Applied Statistics and Economics, Humboldt University, Berlin, Germany |
| 時間/地點: |
10:30 - 12:30
FSC 1217
|
| | |
| 摘要: |
Topic: Dynamic Semiparametric Factor Models
The statistical analysis of many dynamic phenomena of economic
and financial data requires a combination of flexible functional
modelling and dimension reduction methods. A prime example is
modelling the term structure of interest rates. In this case,
functional flexibility is mandatory, because neither economic
nor statistical theory provides complete and sufficient guidelines
for the form of the model components. In a addition, a joint
analysis of several financial products naturally involves high-dimensional
data, especially on an intra-day level. On first sight, flexible
modelling and high-dimensional data analysis seem to be conflicting
goals, in particular in a dynamic context. Semiparametric factor
models though combine both goals by incorporating flexible (nonparametric)
basis functions with low-dimensional (parametric) driving factors
that propagate through time.
Topic: Skew Hedging with Dynamic Semiparametric Factor Models
The price of many financial options strongly depends on the
shape of the implied volatility surface (IVS). Barrier options
for instance can be understood an option on the implied volatility
skew. The IVS, however, is a highly dynamic object, that is subjected
to considerable deformations as time passes. Consequently, the
hedging performance of these options crucially depends on the
strategy to extract the key factors of the IVS dynamics. We extract
these factors by applying dynamic semiparametric factor model
and study the hedging performance of the barrier options. The
vega hedging approach is extended by defining the sensitivity
measures with respect to the most common IVS movements namely
level and skew movements. The performance of the hedging is studied
in local volatility models and applied to DAX index options.
|
- 28/4/2006
| 題目: |
Order Imbalance and the Dynamics of Index and Futures Prices |
| 講員: |
Prof. Joseph K. W. Fung, Department of Finance and Decision Sciences, HKBU, & Research Fellow, Institute for Monetary Research, HKSAR, China |
| 時間/地點: |
11:30 - 12:30
FSC 1217
|
| | |
| 摘要: |
This study examines empirically with complete transaction records
of index futures and of the index stocks, as well as the bid/ask
price quotes of the latter, the impact of stock market order
imbalance on the dynamic behavior of index futures and the underlying
cash index. The study purges spurious correlation in the index
by using an estimate of the true index with highly synchronous
and active quotes of individual stocks. To capture the nonlinear
dynamics of the index and futures prices, the study adopts a
smooth transition autoregressive error-correction model (STECM)
to describe the joint dynamics between the two prices. The study
finds that order imbalance in the cash stock market significantly
affects the error-correction dynamics of index and futures prices.
Moreover, order imbalance impedes error-correction when the two
forces countervail each other. This finding supports our conjecture
that order-imbalance helps explain why real potential arbitrage
opportunity may persist over time. The results also show that
incorporating order imbalance in the STECM framework significantly
improves the explanatory power of the framework. Furthermore,
the speed of transition increased substantially for the cash
index during the crisis period. It can be inferred from the findings
that stock market microstructure which allows a speedy resolution
of order imbalance promotes dynamic arbitrage efficiency between
the futures and the underlying cash stocks.
|
|
|
|
|
