Market Directional Information Derived From (Time, Execution Price, Shares Traded) Sequence of Transactions. On The Impact From The Future

TL;DR

This paper proposes a method to extract market directional signals from transaction sequences by solving a dynamic equation that predicts future prices based on maximizing shares traded, with automatic time scale selection.

Contribution

It introduces a novel approach that uses non-stationary solutions of a dynamic equation to derive market directionality from transaction data, including automatic time scale determination.

Findings

Effective extraction of market direction from transaction sequences

Automatic time scale selection based on execution flow

Ability to compute both lagging and advancing prices

Abstract

An attempt to obtain market directional information from non-stationary solution of the dynamic equation: "future price tends to the value maximizing the number of shares traded per unit time" is presented. A remarkable feature of the approach is an automatic time scale selection. It is determined from the state of maximal execution flow calculated on past transactions. Both lagging and advancing prices are calculated.