Analysis of Stock Price Motion Asymmetry via Visibility-Graph Algorithm - Liu, Ruiyun; Chen, Yu (Frontiers in Physics, 2020)
This paper is the first to differentiate concave and convex price motion trajectories by applying visibility graph and invisibility graph algorithms to the analyses of stock indices. Concave and convex indicators for price increase and decrease motions are introduced to characterize accelerated and decelerated stock index increases and decreases. Upon comparing the distributions of these indicators, it is found that asymmetry exists in price motion trajectories and that the degree of asymmetry, which is characterized by the Kullback-Leibler divergence between the distributions of rise and fall indictors, fluctuates after a change in time scope. Moreover, asymmetry in price motion speeds is demonstrated by comparing conditional expected rise and fall returns on the node degrees of visibility and invisibility graphs.