A Joint Review of Technical and Quantitative Analysis of Financial Markets

This paper presents a joint review on professional technical analysis and academic quantitative analysis of the financial markets, aiming at bridging the deep gulf between the two fields and unifying them under a general science of intelligent finance or financial intelligence. While econometricians and econophysicians have recently reexamined technical analysis, most of their effort is focused on chart patterns and technical indicators, leading to some simplicity impression of technical analysis. In our view, the most valuable core and also the hardest part of technical analysis is the fractal and quantum nature of Elliott waves and Gann price-time cycles and angles. On the quantitative analysis side, since Mandelbrot’s discovery of fractals in financial time series, both empirical and fundamental progresses have been made, mainly in the last decade, including a third-order power law asymptotic behavior in return distribution, an accelerated crossover from the power law towards a Gaussian, a theoretical framework of crashes as critical points, and multi-agent game models of the financial markets. Inspired by these developments from the two fields we point out the possibility of developing an adaptive computational model of Elliott waves and Gann price-time cycles and angles using multilevel power laws, log-periodicity and instantaneous phase estimation.