The National Centre for Econometric Research (NCER) and QUT's School of Economics and Finance will hold a one-day workshop, entitled Practitioners in Financial Markets at the Gardens Point campus, Queensland University of Technology, Brisbane, on Tuesday 28 October 2008.
Morning tea and lunch will be provided on the day. If you are interested in attending, please contact the Project Officer.
The workshop venue is Z Block, Level 4, Room 303, QUT, Gardens Point campus. (Please see the map for location details.)
Please note there is no cost associated with this workshop, although an RSVP would be appreciated for catering purposes.
Unfortunately, due to the current economic environment, Dr Scott White from Deutsche Bank, Sydney, will not be able to attend the workshop.
Associate Professor Adam Clements, Queensland University of Technology.
The Practitioners in Financial Markets workshop is a one day event where current applications of econometrics in financial markets will be presented by a range of industry practitioners. Five speakers from a range of domestic and international investment firms will discuss their research in a forum designed to bring together practitioners, academics and students.
|8:30 am||ARRIVAL TEA/COFFEE (Z413)|
|9:00 am||Dr Joseph Jeisman (Z411)
Commonwealth Bank, Sydney
|10:00 am||Dr Joseph Clark
|11:00 am||MORNING TEA|
|11:20 am||Dr Vlad Pavlov
Tactical Global Management Limited, Brisbane
|12:20 pm||Craig Louis
|1:20 pm||CLOSING REMARKS|
Calibrating the Libor Market Model by Pedersen’s Method
The Libor Market Model (or Brace-Gatarek-Musiela model) is an interest rate model that is widely used in finance to price interest rate derivatives. This model describes the evolution of a family of forward rates where each of the forward rates are characterised as lognormal processes under a common probability measure. The evolution of the forward rates is governed by a stochastic differential equation which is particularised to a set of market data through the choice of values for its parameters. These parameters (at least in the volatility function) are typically determined by a process known as calibration. This process involves finding the parameter values that enable the model to most accurately (in some sense) price simple interest rate products, such as caps and swaptions, for which market prices are readily available. In this presentation I will provide a brief introduction to the Libor Market Model and then outline the process for implementing an important calibration technique introduced by Pedersen (1998).
The powerlessness of financial econometricians
Econometrics in general, and financial econometrics in particular, offers an alluring promise of revelation. This promise has been vastly oversold to practitioners in the financial markets. The reality of financial econometrics is beset by the evil triplets: specification, identification, and power. The last is perhaps the most insidious since it is typically untested by practitioners. Low power can easily remain hidden, allowing pure nonsense to masquerade as meaningful estimation. This presentation examines the power of some tests common in financial econometric practice and reveals some startling results.
The Tale of One State: Revisiting Bulls and Bears.
In this presentation, I examine the behavior of the S&P500 value index around bear market troughs using a methodology similar to the Pagan and Sossounov (2003) JAE paper.
Liquidity Provision in an Open Limit Order Book Market
This presentation outlines a theoretical model of liquidity supply first put forward by Glosten in 1994 and then modified by Sandas in 2001. The model describes the equilibrium behaviour of a open limit order book, which is rapidly becoming the dominant market micro-structure in financial markets. An empirical example is given using order book and trade data for the E-mini S&P500 futures contract traded on the Chicago Mercantile Exchange. Estimation of the model and inference is carried out using Hansen's (1982) Generalised Method of Moments technique. The model offers a nice example of the benefits that GMM can offer in situations involving highly non normal data.
For further details please contact the Project Officer:
Queensland University of Technology