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The Geneva Research Collaboration (GRC) is a non-profit Swiss foundation dedicated to the support of interdisciplinary research in natural and social sciences, to the development of novel economic applications of this research, and to contributing to make Geneva a node of excellence in an international scientific and economic research network. The current research of GRC is concentrated on mathematical and econophysics models applied to financial forecasting, high performance computing, and risk management. The applications endeavour to use new conceptual model structures which are developed into operational tools through the integration of advanced computing techniques. Continue to GRC Objectives

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GRC Seminar - Tuesday 17 June, 16.30-17.30 hours

Location: PS conference room 2-024 building 6, CERN, Meyrin

Note: Participants from outside CERN, please confirm participation with name and affiliation by e-mail, at the latest one day in advance .

Dr. A. Din, Geneva Research Collaboration

"Trend analysis of financial time series"

Abstract:
A large part of the many claims for succesfully predicting the directional movement of financial markets is based on some kind of scheme for "riding the right trend". A problem with such claims is the lack of general agreement about the definition of what constitutes a "trend" and how good it is. The talk discusses financial time series in terms of a discrete change representation which allows for a rather straightforward definition of a trend process and a range process associated with the time series. . Trend analysis is first carried out for random walks so as to determine a certain reference probability distribution for the range process. It is shown how it may be possible to identify a statistically significant signal for trendy behaviour of a financial time series through the appearance of enhancements of the lower tail of the cumulative range probability distribution function. This distribution function leads in a natural way to the definition of a Trend Index a Range Index. As an example, the range properties of daily prices for a few currency crosses, world indices and blue chip stocks are investigated. Results are presented for these time series which show distinct trend characteristics of importance for better understanding the dynamics of financial forecasting.