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Event(s) on April 2006

  • Friday, 7th April, 2006

    Title: A Quick Introduction to Differential Geometry and to Some of Its Applications
    Speaker: Professor Philippe G. Ciarlet, Department of Mathematics, City University of Hong Kong, HKSAR, China
    Time/Place: 16:30  -  17:30
    Abstract: 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.

  • Tuesday, 11th April, 2006

    Title: Implied Volatility Modelling and Skew Hedging
    Speaker: Profs. Hrdle & Borak, Center for Applied Statistics and Economics, Humboldt University, Berlin, Germany
    Time/Place: 10:30  -  12:30
    FSC 1217
    Abstract: 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.

  • Friday, 28th April, 2006

    Title: Order Imbalance and the Dynamics of Index and Futures Prices
    Speaker: Prof. Joseph K. W. Fung, Department of Finance and Decision Sciences, HKBU, & Research Fellow, Institute for Monetary Research, HKSAR, China
    Time/Place: 11:30  -  12:30
    FSC 1217
    Abstract: 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.



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