Pricing Stocks with Trading Volumes

TL;DR

This paper introduces a novel stock pricing framework that replaces volatility with trading volume, supported by empirical validation and offering new directions for option pricing models.

Contribution

It proposes a new stock pricing model based on trading volume instead of volatility, with hypotheses supported by market data analysis.

Findings

Price-volume relation inspired by fluid flows

White-noise hypothesis for price rate of change verified empirically

Framework adaptable to local and stochastic volume models

Abstract

The present paper proposes a new framework for describing the stock price dynamics. In the traditional geometric Brownian motion model and its variants, volatility plays a vital role. The modern studies of asset pricing expand around volatility, trying to improve the understanding of it and remove the gap between the theory and market data. Unlike this, we propose to replace volatility with trading volume in stock pricing models. This pricing strategy is based on two hypotheses: a price-volume relation with an idea borrowed from fluid flows and a white-noise hypothesis for the price rate of change (ROC) that is verified via statistic testing on actual market data. The new framework can be easily adopted to local volume and stochastic volume models for the option pricing problem, which will point out a new possible direction for this central problem in quantitative finance.