# Scaling Features of Price-Volume Cross-Correlation

## TL;DR

This paper investigates the multifractal and power-law properties of price and trading volume correlations across different markets using MF-DXA, revealing market-specific differences in their coupling and independence.

## Contribution

It applies the MF-DXA method to analyze the fractal features of price-volume coupling, highlighting differences between developed and emerging markets.

## Key findings

- Price, volume, and their coupling are multifractal and follow power laws.
- Developed markets show significant negative correlation in price-volume coupling.
- Emerging markets exhibit less contribution of price to the coupling and greater independence between price and volume.

## Abstract

Price without transaction makes no sense. Trading volume authenticates its corresponding price, so there exist mutual information and correlation between price and trading volume. We are curious about fractal features of this correlation and need to know how structures in different scales translate information. To explore the influence of investment size (trading volume), price-wise (gain/loss), and time-scale effects, we analyzed the price and trading volume and their coupling by applying the MF-DXA method. Our results imply that price, trading volume, and price-volume coupling exhibit a power law and are also multifractal. Meanwhile, considering developed markets, the price-volume couplings are significantly negatively correlated. However, in emerging markets, the price has less of a contribution to price-volume coupling. In emerging markets in comparison with the developed markets, trading volume and price are more independent.