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\begin{document}

\title{Volume, Balance Sheet Numbers and Stock Returns: an empirical approach.}



\author[1]{Nelson Seixas dos Santos}%
\author[1]{Lucas Dierings Tanus dos Santos}%
\affil[1]{Universidade Federal do Rio Grande do Sul (UFRGS)}%


\vspace{-1em}



  
  \date{May 07, 2024}


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\section{Introduction}

{\label{446645}}

~\citet*{Amihud} showed illiquidity positively affects ex ante stock
excess return, suggesting that expected stock excess return partly
represents an illiquidity premium.~{Stock excess return, traditionally
called ``risk premium'', has been~}considered a compensation for risk.
This paper proposes that expected stock excess return also reflects
compensation for expected market illiquidity.

~\citet*{BLUME_1994}~investigates the applicability of the informational
role of volume for technical analysis, showing that volume provides
information on quality information for traders, that cannot be deduced
from price statistic. They also show that traders who use information
contained in market statistics do better than traders who do not.

\citet*{Brennan_1996} investigates the empirical relation between monthly
stock returns and measures of illiquidity obtained from intraday data.
They find a significant a significant relation between required rates os
return and these measures after adjusting for the Fama and French risk
factors, and also after accounting for the effects of the stock price
level.

\citet*{EASLEY_1996}~most important empirical result is that the
probability os information-based is lower for high volume stocks. It
also provides evidence of the economic importance of information-based
trading on spreads.

( Pathirawasam (2011)) revealed that stock returns are positively
related to the contemporary change in trading volume. Further, it was
found that past trading volume change is negatively related to stock
returns. Investor~{misspecification about future earnings
or~}illiquidity of low volume stocks can be the reason for the negative
relationship between trading volume and stock returns.

\citet*{Pastor_2001}find that expected stock returns are related
cross-sectionally to the sensitivities of returns to fluctuations in
aggregate liquidity. A liquidity risk factor accounts for half of the
profits to a momentum strategy over a 1966-1999 period.

\citet*{Kim_2014}~research implies that the systematic component
measured by each liquidity proxy is correlated across measures~ and the
shocks to the sistematic and common component of liquidity are an
undiversifiable source of risk.

\citet*{Chiang_2015}

\citet*{Amihud_2012}

\par\null

\par\null

\section{Brazilian Stock Market}

{\label{446645}}

The Brazilian stock market is

\section{}

{\label{446645}}

\section{The Setup}

{\label{446645}}

The model we will use is~

\section{}

{\label{446645}}

\section{Methods and Data}

{\label{446645}}

The model needs one variable, but we don't have this one measured.~
Therefore we collect variable 2 and transform it into variable 1.

\par\null\par\null

\section{Results and Discussion}

{\label{446645}}\par\null\par\null

\section{Conclusion}

{\label{446645}}\par\null\par\null

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