pseudo-harmonic FOREX prediction with machine learning (part one)

“Harmonic” trading methods seek patterns in the relationships between neighboring peaks and valleys in the time series. Particularly, harmonic traders seek pre-specified ratios in the price differences among a series of peaks and valleys. For example, a trader might observe the following pattern: Let A, B, C, D, and E be the points in the […]

picking stocks by graph database (part 2: machine learning)

In our last post, we demonstrated a graph database created to enable study of the stock market, particularly the study of causality relationships. So how to proceed from there? At this stage we want to pick winning stocks, not write an academic paper, so our focus turns toward practical machine learning. Source Data We start […]