@Article{CSIAM-AM-5-1,
author = {Duan , BenLi , YutianLu , DaweiLu , Yang and Zhang , Ran},
title = {Pricing Stocks with Trading Volumes},
journal = {CSIAM Transactions on Applied Mathematics},
year = {2024},
volume = {5},
number = {1},
pages = {1--17},
abstract = {<p style="text-align: justify;">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.</p>},
issn = {2708-0579},
doi = {https://doi.org/10.4208/csiam-am.SO-2022-0030},
url = {http://global-sci.org/intro/article_detail/csiam-am/22918.html}
}