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Topic Title: Fractals, Finance and Fat Tails - 6-7 July - London - 10% wilmott.com Discount
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Fractals, Finance and Fat Tails
New Approaches to Derivatives Pricing and Risk Management
July 6 - 7, 2006 • Le Meridien Piccadilly, London, UK


www.iqpc.co.uk/GB-2700/W500a

Ask for your 10% wilmott.com Discount!

DAY ONE

9:00 Chairman’s welcome and opening speech
Michael Weber, Global Head of Hybrid Products, Rabo Securities
Mike has been trading or managing traders since 1989. His background is in physics, with a PhD in theoretical physics from the University of California.

9:15 Fractals and Finance: Practical or just theoretical?
Markets are an example of what the physicists call a "complex system'' with its associated chaos and fractal behaviour. This talk will discuss the evolution of the mathematics behind fractals, the rise in the use of fractals and some of the implications of looking at finance in this way.
  • What Have We Learned?
  • Are Fractals Useful or Just Pretty Pictures?
  • Statistical Implications of Fractals
  • Misuses of Fractals
  • Future Research
    Edgar Peters, Chief Investment Officer, PanAgora Asset Management
    Ed is the premier author on the subject of chaos theory as it relates to the financial markets. As CIO for PanAgora Asset Management, Inc., he manages over $45 billion in assets, and conducts extensive research into the theory and applications of chaos theory and fractals. He is the author of “Chaos and Order in the Capital Markets”.

    10:15 Fractals and Martingales
    There are many ways to model uncertainty but orthodox finance modelling does not tolerate arbitrage, which drastically reduces the choice. I examine what alternative modellings can bring us.
  • How to model uncertainty?
  • Modelling issues: infinite variance, infinite quadratic variation
  • Is fractional BM arbitrageable?
  • Describing the effects or understanding the causes?
    Bruno Dupire, Bloomberg NY
    Bruno joined Bloomberg in New York in 2004 to develop advanced analytics. He is best known for his work on volatility modelling, including the Local Volatility Model (1993), simplest extension of the Black-Scholes-Merton model to fit all option prices, and subsequent results on stochastic volatility and volatility derivatives. He is a Fellow and Adjunct Professor at NYU. He was included in December 2002 in the Risk magazine "Hall of Fame" of the 50 most influential people in the history of derivatives. He is the recipient of the 2005 "Cutting edge research" Wilmott award and has been voted in 2006 the most important derivatives practitioner of the past 5 years in the Global Derivatives industry survey.

    11:15 Continuous cascade models for asset return fluctuations
    This presentation will provide an overview of some continuous cascade processes recently introduced to model asset return fluctuations.
  • Demonstration that these models account in a very parsimonious manner for most of “stylized facts” of financial time series (volatility clustering, intermittency, fat tail distributions...)
  • Review of the log-normal multi-fractal random walk
  • Discussion of its main mathematical properties and notably its appealing stability properties as respect to time aggregation
  • Understand the parameters by which this model is fully determined
    Emmanuel Bacry, CNRS Research Fellow Assistant Professor in Applied Mathematics, Ecole Polytechnique
    Specialised in "multi-fractals" and wavelets, Emmanuel is involved in harmonic analysis, stochastic process and statistic estimators. His research is linked to financial applied mathematics, predictive problems (for example the "cracks"), and provides elements to precisely determine risk. Dr. Bacry has regularly consulted several financial institutions such as Deutsche Bank, and Société Générale.

    12:15 Networking Lunch

    14:00 Case Study: Using continuous cascade models for risk estimation and forecasting
    The aim of this presentation is to illustrate how MRW cascade models introduced by E. Bacry, can be used to estimate and predict risk associated with return fluctuations.
  • How volatility and Value at Risk predictors can be built using these models
  • How models can be adapted to multi-horizon and multi-scale forecasting from intra-day to monthly time scales
  • Emphasis on estimation problems related to the long-memory nature of volatility
  • Using the framework of random cascade processes to show that many usual risk measures (volatility measures, return distribution fat tail exponents) converge to their expected theoretical values only for (unreachable) very large sample sizes
  • Why finer and finer (intra-day) time scales do not reduce estimation bias
  • Comparing theoretical results and numerical simulations to empirical estimations
    Jean-François Muzy, CNRS Research Fellow Assistant Professor, Universite de Corse
    Cumulating in depth knowledge of physics, mathematics (probabilities and statistics) and computer science, Jean-François has done research on time series analysis, including such diverse fields as music, biology, geology, finance; using broad arrays of tools, from chaos theory to wavelets to econometrics. He has also been a consultant to several financial institutions.

    15:00 Multi-fractal volatility modelling
  • A first approach: the 1997 Multi-fractal Model of Asset Returns
  • Fat tails, long memory and moment-scaling
  • An econometric model: Markov-Switching Multi-frequency (MSM)
  • Estimation and forecasting
    Laurent Calvet, Deloitte Professor of Finance, HEC Paris
    Laurent has recently joined HEC from Harvard University, where he was the John L. Loeb Associate Professor of Economics. His research interests include asset pricing and volatility modelling. Laurent's recent works have been published in Journal of Econometrics, Journal of Economic Theory, Journal of Financial and Quantitative Analysis, Journal of Mathematical Economics, Review of Economics and Statistics and Journal of Monetary Economics.

    16:00 Empirical evaluation of multi-fractal models
  • GMM and maximum likelihood
  • Short- and long-run forecasts
  • Volatility co-movement
  • Value-at-risk
    Adlai Fisher, Professor of Finance, University of British Columbia
    Adlai’s research interests include Corporate Decisions and Asset Prices, Empirical Finance / Financial Econometrics, Volatility Modelling, Derivatives, Mergers and Acquisitions. Adlai’s recent works have been published in the Journal of Finance, Review of Economics and Statistics and the Journal of Financial Econometrics

    17:00 Chairman’s closing remarks

    17:15 Networking Drinks Reception

    DAY TWO

    9:00 Chairman’s welcome
    Michael Weber, Global Head of Hybrid Products, Rabo Securities

    9:15 Heterogeneous markets and fractal behaviours - empirical evidence and modelling
    This talk will discuss empirical properties of (high-frequency) data in finance. These properties are reproduced by the EMA-HARCH model; a discrete-time model with long-range dependence. The results of the calibration reveal the heterogeneous and fractal nature of financial markets, where different traders have very different views and act differently. The following aspects are discussed - both as empirical phenomena and parts of the model:
  • Distributions with heavy tails
  • Clusters and lead-lag structure of volatilities of different time resolutions
  • The role of heterogeneous time frames and the fractal structure of markets
    Ulrich Mueller, Senior ALM Consultant, Converium
    Ulrich studied physics and fluid dynamics at the Swiss Federal Institute of Technology where his prize-winning Ph. D. thesis led to a patented thermo-acoustic heat-pump. Afterwards, he moved to industrial risk assessment and finance. His research work led to numerous publications in scientific journals. In 2002, Ulrich joined the re-insurer Converium. He developed the company's Asset-Liability Management (ALM) model including a comprehensive Economic Scenario Generator.

    10:15 Pricing options via generalized Black-Scholes and Martingales
    It is suggested that there are two separate methods for pricing options under a no arbitrage condition: the generalized Black-Scholes partial differential equation (PDE) following from the price stochastic differential equation (SDE) combined with the condition for a risk neutral portfolio, and the explicit construction of a Martingale based on the corresponding price SDE.
    This talk will point out that:
  • Why option prices necessarily diverge if returns distributions with fat tails are used
  • Demonstrate that options are correctly priced when the exponential distribution is used, and that that distribution is empirically observed for small to moderate returns
    Joe McCauley, Physics Department, University of Houston
    Joe McCauley is a Professor of Physics. He was Lars Onsager's last graduate student. Professor McCauley has written numerous books on Chaos Theory and Fractals. His main research fields are economics and finance (econophysics), nonlinear dynamics, and statistical physics.

    11:15 Non-Gaussian option pricing and multi-timescale models of volatility
    A multi-scale model of volatility assumes that the volatility is governed by the observed past price changes on different time scales.
  • Obtaining a model that captures most stylized facts of financial time series
  • Reproducing the time asymmetry of financial time series: past large-scale volatility influence future small scale volatility
  • Choosing parameters
  • Empirical observations
  • Generalizing the models to account for jumps, skewness and multi-asset correlations
    Lisa Borland, Senior Research Scientist, Evnine-Vaughan Associates, Inc
    Physicist Lisa Borland uses her scientific background to tackle problems in the world of finance. Currently, Lisa is at Evnine-Vaughan Associates Inc., a San-Francisco based hedge fund. Her main focus lies in the research and development of new trading strategies.

    12:15 Networking Lunch

    14:00 Case Study: Fat tails in structured credit derivatives
    Modelling the fat tails associated with portfolio credit derivatives (especially CDO’s) is a central aspect of analysing risk and return. The technique that will be demonstrated is not fractals, but rather copula models that link the marginal probability of defaults of the assets in the portfolio to arrive at the joint probability distribution.
  • Copula modelling approaches to account for tail dependency in portfolio credit derivatives
  • May 2005 - when models failed - how to overlay supply and demand dynamics into risk neutral models
  • Value flows in the CDO market - a principal component analysis to identify trade opportunities
  • Correlation strategies - what are the most common strategies used by leveraged investors?
  • Latest modelling developments - from forward base correlation to HJM-type approaches
    Lorenzo Isla, Head of European Structured Credit Derivatives Research, Barclays Capital
    Lorenzo Isla is responsible for the CDO / structured credit research and quantitative strategy at Barclays Capital in London. Prior to his current role he was a lecturer at Harvard University and worked for Panagora Asset Management, the Boston based hedge fund.

    15:00 Markov Processes, Hurst Exponents, and non-linear diffusion equations with application to finance
    This talk will show by explicit closed form calculations that a Hurst exponent H≠1/2, without extra conditions, does not imply long time correlations like those found in fractional Brownian motion.
  • The construction of scaling solutions
  • Does the process of scaling Markov with the Hurst exponent have non-stationary increments?
  • Why the usual simple argument that H≠1/2 implies correlations fail for Markov processes with scaling solutions
    Gemunu H. Gunaratne, Professor, Physics Department, University of Houston
    Gemunu is a Professor and Associate Chairman of Physics. His research interests include Pattern Formation, Vibrational Assessment of Bone and Random Walks with Variable Step Sizes. He has written extensively on the use of fractals and chaos in the financial markets.

    16:00 Panel Session: The future of fractals in finance
    Will the SV process that reproduces all the stylised facts of real markets, such as power law fat tails, vol clustering, realistic vol of vol, etc, be implemented across the financial markets?
  • Multi-time scale models vs. the multi-fractal approach: Which one wins?
  • What will the potential market impact of this implementation be?
    Panellists include speakers from the programme

    17:00 Chairman’s closing remarks and end of conference

    www.iqpc.co.uk/GB-2700/W500a



    -------------------------
    James Fahy
    Administrator

    Edited: Thu May 18, 06 at 09:00 AM by Administrator
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