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Who is David Aronson?

Pioneer in machine learning & non-linear trading system development and signal boosting/filtering since 1979.

Started Raden Research Group in 1982 and oversaw the development of PRISM (Pattern Recognition Information Synthesis Modeling).

Chartered Market Technician certified by The Market Technicians Association since 1992.

Proprietary equities trader for Spear, Leeds and Kellogg 1997 – 2002.

Adjunct professor of finance teaching a graduate level course in technical analysis, data mining and predictive analytics to MBA and financial engineering students from 2002 to 2011.

Author of “Evidence Based Technical Analysis” published by John Wiley & Sons 2006. First popular book to deal with data mining bias and Monte Carlo Permutation Method for generating bias free p-values.

Co-designer of TSSB (Trading System Synthesis and Boosting) a software platform for the automated development of statistically sound predictive model based trading systems.

Author & editor of Statistically Sound Machine Learning for the Algorithmic Trading of Financial Instruments : Developing Predictive-Model-Based Trading Systems Using TSSB .

Proposed a method for indicator purification and Pure VIX

Innovated the concept of signal boosting: using machine learning to enhance the performance of existing strategies.

Professional Publications

  • Moving Window Correlation Stability and Its Use in Indicator Evaluation, Journal of the Market Technicians Association, Spring 1992 pp. 21-28
  • Pattern Recognition Signal Filters, Journal of the Market Technicians Association, Spring 1991, pp.42-51
  • The Cells Method of Indicator Evaluation, The Encyclopedia of Technical Market Indicators, chapter 15, by Colby and Meyers, Dow Jones-Irwin, 1988
  • Artificial Intelligence / Pattern Recognition Applied to Forecasting Financial Market Trends, Journal of the Market Technicians Association, May 1985 pp. 91-132
  • Artificial Intelligence & Pattern Recognition to Assist the Market Analyst, Financial and Investment Software Review, three part tutorial, Summer, Fall & Winter edition 1984.
  • Cybernetics, The Trading Approach for the ‘80’s, Commodities Magazine, January 1980.
  • Evidence Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals. John Wiley & Sons, November 2006
  • Purified Sentiment Indicators for the Stock Market published in the Journal of Technical Analysis, 2010.

David's outside interests include skiing, hiking, knitting and jazz trumpet.

Who is Tim Masters?

Dr. Timothy Masters has a PhD in statistics, with specializations in applied statistics and numerical computation. He is the author of four highly regarded books on artificial intelligence (“Practical Neural Network Recipes in C++”; “Signal and Image Processing with Neural Networks”; “Advanced Algorithms for Neural Networks”; “Neural, Novel, and Hybrid Algorithms for Time Series Prediction”.

Dr. Masters has worked in the field of automated trading of financial instruments since 1995. Prior to this he developed software for biomedical engineering and remote sensing applications. His current research focuses on algorithms for controlling data mining bias in order to fairly evaluate the performance potential of automated market trading systems. He is also developing graphical and analytic tools to help financial traders better understand market dynamics.

His outside interests include music (he plays keyboard, fiddle, and bass in several bands) and the martial arts (he is a second-degree black belt studying Washin-Ryu Karate with Master Hidy Ochiai.)

More about Tim Masters, including information on his latest book "Assessing and Improving Prediction and Classification", can be found at TimothyMasters.info.