Fundamental framework for "technical analysis" of market prices

Starting from the characterization of the past time evolution of market pri ces in terms of two fundamental indicators, price velocity and price accele ration, we construct a general classification of the possible patterns char acterizing the deviation or defects from the random walk market state and i ts time-translational invariant properties, The classification relies on tw o dimensionless parameters, the Froude number characterizing the relative s trength of the acceleration with respect to the velocity and the time horiz on forecast dimensionalized to the training period. Trend-following and con trarian patterns are found to coexist and depend on the dimensionless time horizon. The classification is based on the symmetry requirements of invari ance with respect to change of price units and of functional scale-invarian ce in the space of scenarii. This "renormalized scenario" approach is funda mentally probabilistic in nature and exemplifies the view that multiple com peting scenarii have to be taken into account for the same past history. Em pirical tests are performed on about nine to thirty years of daily returns of twelve data sets comprising some major indices (Dow Jones, SP500, Nasdaq , DAX, FTSE, Nikkei), some major bonds (JGB, TYX) and some major currencies against the US dollar (GBP, CHF, DEM, JPY). Our "renormalized scenario" ex hibits statistically significant predictive power in essentially all market phases. In contrast, a trend following strategy and trend + acceleration f ollowing strategy perform well only on different and specific market phases . The value of the "renormalized scenario" approach lies in the fact that i t always selects the best of the two, based on a calculation of the stabili ty of their predicted market trajectories.