Invitation to the Inaugural Stokes Professorship Lecture

05 December 2008

story-fractal-market.jpg

The Fractal market hypothesis

by

Professor Jonathan Blackledge

Professor Jonathan Blackledge
Stokes Professor of Digital Signal Processing, DIT

on
Friday 12th December, 2008 – 10am
in
The Faculty of Engineering
Dublin Institute of Technology
Kevin Street, Room KE4008

Overview of the Lecture

The current world economic crisis, that started with the ‘Credit Crunch’ in the Summer of 2007, appears to be spiralling out of control irrespective of government intervention. With the recent collapse and effective bankruptcy of major banks and financial organisations such as Northern Rock and Lehman Brothers, there is clearly something going on in the world economy that is more than just a technical hitch. Given all the financial modelling systems, checks and balances and sophisticated macroeconomic forecasting techniques that pervade the financial sector, why was the current economic situation not predicted? It was, using among other methods, the approach discussed in this lecture which is based on the paper: Application of the Fractal Market Hypothesis for Macroeconomic Time Series Analysis, J M Blackledge, International Society for Advanced Science and Technology, Transactions on Electronics and Signal processing, No. 1, Vol. 2, 78-101, 2008.

Financial time series modelling is a well established practice. This includes the use of certain partial differential equations for describing financial systems such as the Black-Scholes equation for options pricing. Attempts to develop accurate stochastic models for financial time series, which are essentially digital signals composed of ‘tick data’ (data that provides traders with daily tick-by-tick data - time and sales – of trade price, trade time, and volume traded, for example, at different sampling rates as required), can be traced back to the late Nineteenth Century when Louis Bachelier, in his PhD Thesis, The Theory of Speculation, proposed that fluctuations in the prices of stocks and shares (which appeared to be yesterday’s price plus some random change) could be viewed in terms of random walks in which price changes were entirely independent of each other. This idea underpins what is now known in economics as the ‘Efficient Market Hypothesis’. It is based on a number of questionable assumptions, one of the most important being, that economic time series are normally or Gaussian distributed, an assumption, upon which, models such as the Black-Scholes equation are ultimately based.

It has long been known that economic time series are non-Gaussian and, moreover, that they contain similar features, in a statistical sense, over different time scales – ‘Elliot waves’. However, these observations are rarely included in the economic models that can end up affecting us all. In this lecture, an approach to macroeconomic modelling is considered that is based on a process known as fractional diffusion, incorporates the fact that the statistics of economic times series are non-Gaussian, non-stationary and self-affine or ‘fractal’, and is thus based on a ‘Fractal Market Hypothesis’. It is demonstrated how this approach can provide an accurate and robust ‘gauge’ for economic forecasting.

 

Professor Jonathan Blackledge
Stokes Professor of Digital Signal Processing, DIT –http://eleceng.dit.ie/blackledge

Jonathan Blackledge graduated in physics from Imperial College, and in music from the Royal College of Music, London, in 1980. He gained a PhD in theoretical physics from London University in 1984 and was then appointed a Research Fellow of Physics at Kings College, London, from 1984 to 1988, specializing in inverse problems in electromagnetism and acoustics. During this period, he worked on a number of industrial research contracts undertaking theoretical and computational research into the applications of inverse scattering theory for the analysis of signals and images. In 1988, he joined the Applied Mathematics and Computing Group at Cranfield University as Lecturer and later, as Senior Lecturer and Head of Group where he promoted postgraduate teaching and research in applied and engineering mathematics in areas which included computer aided engineering, digital signal processing and computer graphics. While at Cranfield, he co-founded Management and Personnel Services Limited through the Cranfield Business School which was originally established for the promotion of management consultancy working in partnership with the Bedfordshire Chamber of Commerce in England.

In 1994, Jonathan Blackledge was appointed Professor of Applied Mathematics and Head of the Department of Mathematical Sciences at De Montfort University where he established the Institute of Simulation Sciences. He was appointed to the Stokes Professorship of DSP at DIT in 2008, a position that is funded by the Science Foundation Ireland. He is a Visiting Professor in the Advanced Signal Processing Research Group, Department of Electronics and Electrical Engineering at Loughborough University, England (a group which he co-founded in 2002 as part of his appointment) and Professor Extraordinaire of Computer Science in the Department of Computer Science at the University of the Western Cape, South Africa (2004-date). He is also a co-founder, co-investor and director of a group of product development companies specializing in information and communications security technology (Lexicon Data Limited), management consultancy and training (European Management Development Limited) and audio post-production (Tamborine Productions Limited).

Professor Blackledge has published over one hundred scientific and engineering research papers and technical reports for industry, six industrial software systems, fifteen patents, twelve books and has been supervisor to over fifty research (PhD) graduates. He is an acknowledged authority on Digital Signal Processing and its applications, lectures widely to a variety of audiences composed of mathematicians, computer scientists, engineers and technologists in areas that include cryptology, communications technology and the use of artificial intelligence in process engineering, financial analysis and risk management. His current research interests include computational geometry and computer graphics, digital signal/image processing and analysis, nonlinear dynamical systems modelling and computer network security, working in both an academic and commercial context. He holds Fellowships with England's leading scientific, engineering and management Institutes and Societies including the Institute of Physics, the Institute of Mathematics and its Applications, the Institution of Engineering and Technology, The Institute of Mechanical Engineers, the British Computer Society, the Royal Statistical Society, the City and Guilds London Institute, the Institute of Leadership and Management and the Chartered Management Institute.

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