Return and Liquidity Relationships on Market and Accounting Levels in Brazil

Abstract

This article discusses profitability-liquidity relationships on accounting and market levels for 872 shares of publicly-traded Brazilian companies, observed between 1994 and 2013. On the market level, the assumption is that share liquidity is able to reduce some of the risks incurred by investors, making them more willing to pay a higher price for liquid shares, which would lower expected market returns. On the accounting level, the basic hypothesis argues that a firm's holding more liquid assets is related to a conservative investment policy, possibly reducing accounting returns for shareholders. Under the assumption of financial constraint, however, more accounting liquidity would allow positive net present value investments to be carried out, increasing future accounting returns, which would positively affect market liquidity and share prices in an efficient market, resulting in a lower market risk/expected return premium. Under the assumption of no financial constraint, however, more accounting liquidity would only represent a carry cost, compromising future accounting returns, which would adversely affect market liquidity and share prices and result in a higher market risk/expected return premium. Among the hypotheses, the presence of a negative market liquidity premium was verified in Brazil, with shares that traded more exhibiting a higher expected market return. On the margins of the major theories on the subject, only two negative relationships between excess accounting liquidity and market liquidity and accounting return, supporting the carry cost assumption for financially unconstrained firms, were verified. In terms of this paper's contributions, there is the analysis, unprecedented in Brazil as far as is known, of the relationship between liquidity and return on market and accounting levels, considering the financial constraint hypothesis to which the firms are subject.

Full text

R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016 259
Return and Liquidity Relationships on Market and Accounting Levels
in Brazil*
Fernanda Finotti Cordeiro Perobelli
Universidade Federal de Juiz de Fora, Faculdade de Economia, Juiz de Fora, MG, Brazil
Rubens Famá
Universidade de São Paulo, Faculdade de Economia, Administração e Contabilidade, Departamento de Administração, São Paulo, SP, Brazil
Luiz Claudio Sacramento
Fundação Getúlio Vargas, Escola Brasileira de Administração Pública e de Empresas, Rio de Janeiro, RJ, Brazil
Received on 01.12.2015 – Desk acceptance on 02.12.2015 – 4th version approved on 04.15.2016.
ABSTRACT
This article discusses profitability-liquidity relationships on accounting and market levels for 872 shares of publicly-traded Brazilian com-
panies, observed between 1994 and 2013. On the market level, the assumption is that share liquidity is able to reduce some of the risks
incurred by investors, making them more willing to pay a higher price for liquid shares, which would lower expected market returns. On
the accounting level, the basic hypothesis argues that a firm’s holding more liquid assets is related to a conservative investment policy,
possibly reducing accounting returns for shareholders. Under the assumption of financial constraint, however, more accounting liquidity
would allow positive net present value investments to be carried out, increasing future accounting returns, which would positively affect
market liquidity and share prices in an efficient market, resulting in a lower market risk/expected return premium. Under the assumption
of no financial constraint, however, more accounting liquidity would only represent a carry cost, compromising future accounting returns,
which would adversely affect market liquidity and share prices and result in a higher market risk/expected return premium. Among the
hypotheses, the presence of a negative market liquidity premium was verified in Brazil, with shares that traded more exhibiting a higher
expected market return. On the margins of the major theories on the subject, only two negative relationships between excess accounting
liquidity and market liquidity and accounting return, supporting the carry cost assumption for financially unconstrained firms, were ve-
rified. In terms of this paper’s contributions, there is the analysis, unprecedented in Brazil as far as is known, of the relationship between
liquidity and return on market and accounting levels, considering the financial constraint hypothesis to which the firms are subject.
Keywords: market liquidity, accounting liquidity, market risk/expected return, accounting return, financial constraints.
ISSN 1808-057X
DOI: 10.1590/1808-057x201601530
*Paper presented at the XXXVIII ANPAD Congress (EnANPAD), Rio de Janeiro, RJ, Brazil, September 2014.

Fernanda Finotti Cordeiro Perobelli, Rubens Famá & Luiz Claudio Sacramento
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016
260
1 INTRODUCTION
proposed by Fama and French (1993). They concluded
that expected return is negatively correlated to the rate
of turnover, supporting the results obtained by Amihud
and Mendelson (1986). In Brazil, Machado and Medei-
ros (2012), using shares listed on the São Paulo Stock
Exchange (BM&FBOVESPA) between June 1995 and
June 2008, sought to price assets in function of the beta
measured by the CAPM (Capital Asset Pricing Model)
model from Sharpe (1964), passing through Fama and
French (1993), and by the Keene and Peterson (2007)
model, which considers, in the pricing of expected ma-
rket return, the beta factors size, book-to-market, and
market liquidity. This last model, according to its au-
thors, was – compared to the others – the one with the
greatest predictive ability. Minardi et al. (2005) also sou-
ght to verify the presence of a premium for liquidity in
Brazil; highlighting the friction that exists in this market
and the irrelevance of market-maker actions, the authors
concluded that a premium for negative liquidity exists in
the market in question, with more liquid shares exhibi-
ting systematically higher returns.
These results bring about reflections regarding the
market liquidity versus expected market risk/return
relationship in Brazil. Considering the extensive time-
frames and range of assets, comprising all non-financial
company shares traded on the BM&FBOVESPA during
the 20 years of financial stability after the implementa-
tion of the Plano Real in 1994, the first aim of this paper
is to analyze the market liquidity versus expected ma-
rket risk/return relationship for the 872 shares monito-
red quarterly between 1994 and 2013. But not only this;
innovatively, as far as is known, and assuming that the
behavior of share prices in the market can reflect the
economic-financial situation of the issuing companies,
cross-relationships (and potential trade-offs) between
liquidity and accounting return and liquidity and ex-
pected market risk/return will be theoretically discussed
and estimated for the companies that compose the sam-
ple, with joint analysis of the four indicators being the
second, and main aim of this paper.
In accounting terms, what is discussed in the litera-
ture is a possible trade-off between accounting liquidity
and profitability caused by the assumption that com-
panies that carry more liquid assets would be less apt
to generate greater accounting returns for shareholders
(commonly defined as net income per unit of net equity,
or return on equity, or simply ROE).
Higher accounting returns would be the natural
compensation for an increase in operational risk brou-
ght on by greater immobilization of capital (lower ac-
counting liquidity), as argued by Walker (1964). This
author explores the accounting liquidity and accounting
returns relationship for a business, elaborating a the-
ory on working capital that postulates that accounting
profitability would be a function of the ratio between
One important aim of Accounting and Finance re-
search is to provide elements that allow for improved
analysis of financial reports, predictability of firms’ fu-
ture results (Fairfield, Whisenant, & Yohn, 2001), and
ultimately help in agent decision making.
In informationally efficient markets (Fama, 1970,
1991), it is expected that information released relating to
firms is quickly and correctly passed on into their share
prices. However, researchers such as Eberhart, Maxwell,
and Siddique (2004) find evidence that even the most
active and developed markets, such as in the US, are slow
in correctly identifying and evaluating accounting infor-
mation. At times, sluggishness in transmission can result
from the difficulty itself of recognizing a piece of infor-
mation as positive or negative. Take, for example, the
(potential) trade-off between liquidity and profitability.
In the stock market setting, more liquid shares would
represent lower investment exit risk for the investor.
Therefore, they should be recognized as more attractive
assets, enjoying a higher price and lower market risk/
expected return.
Authors such as Amihud and Mendelson (1986,
2000) argue that less liquid shares in the market need
to be traded with a discount in the current price that
attracts investors – or, in other words, they need to offer
a risk premium in order to attract investors to hold the
asset in the long run. According to Demsetz (1968) and
Amihud and Mendelson (1986), market liquidity can be
described as the cost of immediate execution of a buy
or sell order. Not unusually, market liquidity is measu-
red by the bid-ask spread, or the difference between the
price of buying and the price of selling an asset on the
market, as originally proposed by Demsetz (1968). Au-
thors who use a similar concept are: Chordia, Roll, and
Subrahmanyan (2000) and Gopalan, Kadan, and Pevzner
(2012); and, in Brazil, Minardi, Sanvicente, and Montei-
ro (2005), and Correia and Amaral (2012).
For Pastor and Stambaugh (2001), liquidity is the abi-
lity to quickly trade large quantities of assets, at a low cost
and without this altering the price of the asset much. For
Rösch, Subrahmanyam, and Dijk (2013), greater liqui-
dity, represented by trading volume, implies decreased
friction – or transaction costs – in the market, making
it more distribution efficient. Examples of authors who
used trading volume or turnover (volume in terms of the
amount of securities issued) as a proxy for market liqui-
dity in their articles are: Demsetz (1968), Datar, Naik,
and Radcliffe (1998), Chordia, Roll, and Subrahmanyan
(2011), and, in Brazil, Correia and Amaral (2012).
Datar et al. (1998) verified the presence of the liqui-
dity premium witnessed by Amihud and Mendelson
(1986) in the shares of non-financial companies listed
on the NYSE and found that the relationship exists even
after being controlled for variables such as company
size, book-to-market (BTM) ratio, and beta, risk factors

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working capital held and fixed capital. If the ratio be-
tween working capital and fixed capital increased, this
would mean that a company would be more liquid, that
is, assuming lower operational risks, and as a result of
this reduction in risk, it would also be generating lower
accounting returns.
Authors such as Lazaridis and Tryfonidis (2006),
using the cash conversion cycle (CCC) concept – which
is defined as equal to the sum of the average timefra-
me for receiving payments from client and the average
timeframe for storage minus the average timeframe for
paying for purchases -, conclude that, in fact, there is
a negative relationship between CCC and profitability,
measured by the authors via gross operational return.
The authors observed that low gross operational returns
are associated with an increase in the number of days
for accounts payable. This leads them to the conclusion
that companies with lower accounting profitability wait
longer to meet their obligations with suppliers, accumu-
lating funds. The same effect is verified in the negative
relationship between receivables and company accoun-
ting profitability, which would be: the higher the liquidi-
ty stored in receivables, requiring more working capital,
the lower the accounting profitability.
There are, however, authors such as Chan (2010) who
argue in favor of a positive relationship between accoun-
ting liquidity and profitability in a context of financial
constraint, consistent with the idea postulated by Hiri-
goyen (1985) and verified both by Baghiyan (2013) and
by Ding, Guariglia, and Knight (2010) for developing
markets. Baños-Caballero, García-Teruel, and Martínez-
-Solano (2013) are authors who find a U-shaped rela-
tionship for the two indicators, showing that both little
working capital and excess working capital can be preju-
dicial to firm performance.
In Brazil, Pimentel (2008) found a positive rela-
tionship between accounting liquidity and profitability
in the long run. Using a sample composed of companies
listed among the “500 Biggest and Best” in the Revista
Exame, between 2000 and 2005, the concepts of current
liquidity (current assets divided by current liabilities)
and return on assets (net income divided by total assets)
and the panel data methodology, the author found that
current liquidity was positively related to return on as-
sets, supporting the hypothesis from Hirigoyen (1985).
Following on from the paper by Pimentel (2008),
Vieira (2010) also sought to verify whether there was a
negative relationship between accounting liquidity and
profitability in the short run, and a positive one in the
long run. The sample was global, composed on 48 airli-
ne companies, observed between 2005 and 2008. Again
using current liquidity as a measure of liquidity, and re-
turn on assets for profitability, the author concluded that
accounting liquidity and profitability exhibited a posi-
tive relationship, contrary to the idea usually presented
in the literature under the assumption of no financial
constraint.
More recently, Pimentel and Lima (2011) related,
over time series, dry liquidity indicators (current assets
minus stock divided by current liabilities) and the pro-
fitability of companies from the textiles sector traded
on the BM&FBOVESPA between March 1995 and Mar-
ch 2009. They concluded that, in the medium to long
run, there was, in fact, a positive relationship between
liquidity and profitability; that is, companies with low
accounting profitability would also be those with low
accounting liquidity, which would again contradict a po-
tential trade-off between liquidity and return on the ac-
counting level. The authors, however, could not establish
a causal relationship between liquidity and profitability,
with an inverse relationship being observed, for most of
the companies analyzed, between profitability and liqui-
dity. In other words, liquidity ends up resulting from the
observed profitability (self-funding), and not being a de-
terminant of this profitability.
The concepts of current and dry liquidity, however,
treat different investments and financing in the same
way, whether they are of a permanent nature (operatio-
nal) or of a seasonal nature (financial), and greater dis-
crimination between these items is necessary. Fleuriet,
Kehdy, and Blanc (2003) argue that in order to define
excess accounting liquidity, i.e., that which is really able
to destroy accounting profitability, it is first necessary to
reclassify current assets and liabilities. The cash balance,
according to Fleuriet et al. (2003), represents a residual
value obtained from the difference between Net Working
Capital (long term funds raised by the company in ex-
cess of its long term investments, or simply long term
liabilities minus long term assets) and the Working Ca-
pital Requirement (requirements of a permanent nature
or clients plus stock minus suppliers). If Net Working
Capital is not enough to fund the Working Capital Re-
quirement, there will be a negative Cash Balance. This
situation indicates that a company is funding part of its
permanent requirements with short term funds, whi-
ch may cause its risk of insolvency to increase. In this
model, a company that has a positive cash balance finds
itself in a state of greater financial security; however, if
this balance is very high, the company ends up incurring
liquidity carry costs, possibly generating lower accoun-
ting returns for shareholders, with many funds ceasing
to be allocated to more risky assets, which could gene-
rate higher accounting profitability, respecting the the-
oretical relationship between risk and return. The cash
balance value therefore has to be calculated, as well as its
quadratic version, in order to consider, in a more precise
way, excess accounting liquidity – taken care of in this
paper, unlike in the others found in the literature.
As Almeida and Eid (2014) highlight, since working
capital is an important component of cash flow from ope-
rations, and this is part of firms’ free cash flow, it is cor-
rect to conclude that efficient management of working
capital has effects on the value of firms. The authors also
mention that, over the years, the study of the optimal
level of working capital in order to maximize the value
of firms has received attention from researchers, such

Fernanda Finotti Cordeiro Perobelli, Rubens Famá & Luiz Claudio Sacramento
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016
262
as Deloof (2003) and Howorth and Westhead (2003).
Therefore, it would be interesting to verify not only the
relationship between market liquidity and market risk/
expected return and between accounting liquidity and
accounting return, but also cross-relationships between
the four indicators.
Cross-checking accounting and market liquidity,
Gopalan et al. (2012) observe that papers such as those
from Chordia, Roll, and Subrahmanyam (2007) and Fo-
ley, Hartzell, Titman, and Twite (2007) show a simulta-
neous growth in market liquidity and in the accounting
liquidity of firms in a context of constraint. In the un-
folding of the subprime mortgage crisis of 2008, a joint
decline in the liquidity of the assets of financial compa-
nies and in the liquidity of their shares was observed.
The question that naturally arises from observation of
this fact is whether there is a relationship between ac-
counting (firm) liquidity and market liquidity (of the
securities that concede rights over firms’ assets). And,
moreover, it questions – observing the arguments from
Amihud and Mendelson (1986, 2000) – whether firms
with greater accounting and market liquidity trade at a
higher price, reflecting greater accounting returns in a
context of constraint and enjoying a lower market risk/
expected return.
The first hypothesis from Gopalan et al. (2012) is that
there is a relationship between accounting liquidity and
market liquidity, but that this relationship may be both
positive and negative. More accounting liquidity redu-
ces the uncertainty related to future investments, via a
reduction in financial constraint, which would increase
the liquidity of shares. On the other hand, more accoun-
ting liquidity allows more discretionary future invest-
ments and implies carry costs, increasing investor risk
and reducing share liquidity. The results found by the
authors indicate that the two dimensions are positively
related and that this relationship is more positive in fir-
ms with few growth opportunities, that is, those with less
discretion in choosing projects and which face greater
financial constraint. The authors measure growth op-
portunities using the market-to-book (MTB) ratio and
capital expenditures (CAPEX). As proxies for financial
constraint, the authors consider size, lack of credit ratin-
gs, and a high likelihood of default.
Gopalan et al. (2012) also argue that in markets wi-
thout friction and operating according to the assump-
tions from Modigliani and Miller (1958), investments
are independent from the source of funding. However,
in markets with financial constraints and without so
many investment opportunities capable of leading to
overinvestment or exacerbating the constraint problem,
the holding of liquid assets can bring value to firms and,
according to Diamond and Verrecchia (1991), raise their
price – which would reduce their market risk/expected
return and cost of capital. Almeida and Eid (2014) also
remind us that for financially constrained companies,
greater accounting liquidity can increase the likelihood
of firms implementing projects with positive net present
value, which would be abandoned under the hypothesis
of not maintaining accounting liquidity. For firms that
are not subject to this restriction, however, this benefit
would simply not exist.
In Brazil, the study by Correia and Amaral (2012), in
agreement with Gopalan et al. (2012), observes that ac-
counting liquidity – measured by financial flexibility of
cash flow – is reflected in the market liquidity of shares.
According to the authors, more cash in hand diminishes
the uncertainty associated with future cash flow and this
improves the market liquidity of shares, making them
more attractive, more expensive, and with a lower ma-
rket risk/expected return.
Almeida and Eid (2014), using a sample of Brazilian
companies listed on the BM&FBOVESPA, between 1995
and 2009, found evidence that an increase in the level
of working capital at the start of the financial year redu-
ces the value of company shares, increasing their market
risk/expected return.
Outside the context of financial constraint, another
explanation for the negative relationship between ac-
counting liquidity and market risk/expected return is
provided by Hirshleifer, Hou, Teoh, and Zhang (2004).
For these authors, as information is vast and the abili-
ty to process it is limited, investors end up using rules
of thumb for decision making that lead to suboptimal
choices. In their paper, the authors argue that the level of
accounting liquidity (defined as operational assets mi-
nus operational liabilities divided by total assets) is not
fully evaluated in terms of effects on future accounting
returns. In a simple way, investors evaluate information
of more accounting liquidity as always being positive, so
that there is never conflict between accounting liquidi-
ty and accounting return. They then go on to overvalue
shares in firms with greater accounting liquidity and de-
mand a lower market risk premium for these shares.
For a potentially positive relationship between ac-
counting return and expected market return, a similar
explanation is given by Anderson and Garcia-Feijoo
(2006) and Cooper, Gullen, and Schill (2008). These au-
thors claim that growth of assets (measured by the an-
nual variation in total assets) raises share prices – again,
without a complete evaluation of the long term effects
of such growth – and, therefore, depresses market risks/
expected returns. Considering that total assets, or the
portion of these assets funded by shareholder equity,
are the most common denominators in accounting re-
turn measurements, their growth, unaccompanied by a
proportional increase in profitability brought about by
investments, would also reduce companies’ accounting
return. Therefore, there may be a positive relationship
between market risks/expected returns and accounting
returns in a context of incomplete evaluation of informa-
tion on the part of investors.
As argued by Fairfield et al. (2001), as well as in Hir-
shleifer et al. (2004), these failures in the complete eva-
luation of information indicate market inefficiency in
evaluating what would be good or bad news associated

Return and Liquidity Relationships on Market and Accounting Levels in Brazil
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016 263
with risk and with expected company performance and
that of their shares.
That said, the second aim of this paper is not only to
evaluate the trade-off between accounting return and li-
quidity, but also the way these two indicators are percei-
ved by the market in terms of variation in prices, market
risk/expected return, and market liquidity of company
shares. As far as is known, joint observation of the four
indicators (return and liquidity, at the accounting and
market levels) is unprecedented in the literature.
Considering the wide set of theoretical relationships
related to the issue, the results found for developed ca-
pital markets, and the still few papers relating to develo-
ping countries – which do not jointly evaluate the (po-
tential) trade-off between liquidity and profitability at
the accounting and market levels -, the theoretical con-
cepts discussed will be tested paying special attention to
the role performed by the financial constraint the firms
are subject to, which will be considered via the proxies:
size, market-to-book ratio (Gopalan et al., 2012), divi-
dends per share, dividend payout, and dividend yield
(Almeida & Campello, 2010), self-funding, the financial
leverage multiplier, and cost and quality of debt – Table
1 contains the operational description of all of the varia-
bles used.
The hypotheses of interest, according to the theories
exposed and under the assumption of no financial cons-
traint, are:
H1a: there is a negative relationship between market
risk/expected return and market liquidity;
H2a: there is a positive relationship between market
risk/expected return and accounting liquidity;
H3a: there is a negative relationship between accoun-
ting return and accounting liquidity;
H4a: there is a positive relationship between accoun-
ting return and market liquidity;
H5a: there is a negative relationship between market
risk/expected return and accounting return;
H6: there is a negative relationship between market
liquidity and accounting liquidity.
That is, under no constraint, companies do not need
to carry more liquid assets as a liquidity reserve; if they
do so, they sacrifice accounting returns, are less traded
in the market, have lower prices, and enjoy a higher ma-
rket risk/expected return premium.
Under the assumption of financial constraint, we
have:
H2b: there is negative relationship between market
risk/expected return and accounting liquidity;
H3b: there is a positive relationship between accoun-
ting return and accounting liquidity;
H6b: there is a positive relationship between market
liquidity and accounting liquidity.
That is, under constraint, companies would need to
carry more liquid assets as reserve liquidity; when they
do so, they guarantee higher accounting returns, are
more traded in the market, have higher prices, and enjoy
a lower market risk/expected return premium.
Hypotheses 1, 4, and 5 are not related to carrying ac-
counting liquidity to alleviate potential financial cons-
traints, and therefore do not change with regards to the
two scenarios considered.
Under the assumption of failure in evaluating infor-
mation on the part of investors:
H5b: there is a positive relationship between market
risk/expected return and accounting return.
2 METHODOLOGY
With the aim of investigating the proposed hypo-
theses, a database was elaborated based on the Eco-
nomática® software – containing accounting and sha-
re price data for all of the companies listed on the
BM&FBOVESPA, observed between the third quarter
of 1994 and the third quarter of 2013. As the “market”
level is important in this study, the prices and volumes
traded for ordinary and preference shares and their
combinations (Units) were considered, as well as ac-
tive and cancelled shares, observed in order to avoid
survival bias. Companies from the financial sector
were excluded from the database, since their indicators
are interpreted in a specific way. The final sample was
composed of a maximum of 77 quarters under obser-
vation and 872 shares.
The database was constructed in panel form, or ra-
ther, predicting the variability of shares and the change
in their values over time. They were piled in obser-
vational units, as suggested by Wooldridge (2010). In
order to place all of the data in this same scale, the
average and standard deviation for each variable was
removed from the original values, returning all of the
data in terms of deviations in relation to the average.
In order to avoid the influence of outliers in the esti-
mations, observations above and below 3 standard de-
viations were ignored.
Table 1 presents the operational description of the
variables considered in this study. Table 2 presents the
descriptive statistics of these variables, while Table 3
presents the correlations between them.
Analyzing the correlations larger than 5% (in mag-
nitude) in Table 3, it is possible to verify the following
linear relationships for the study sample:
1. In relation to volume traded: analyzing the VOL
variable, shares that traded more exhibited a greater
variation in price in the quarter, a bigger current and
future beta, higher business turnover, and a bigger
difference between maximum and minimum price
(spread). They belonged to larger companies (both in
terms of assets as well as market value), with higher
accounting returns in the period, which turned over
their assets less, held more net working capital and

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264
cash balance, practiced greater self-funding, paid more
dividends, and contracted loans at lower rates than the
operational return from the activity (measured by the
EBIT – Earnings Before Interest and Taxes). The re-
lationships indicate that large companies with no fi-
nancial constraints are concerned. The QBUS_TURN
variable – also related to volume traded, but standar-
dized by the volume of assets in circulation – brought
as additional information the fact that such companies
would also be those requiring more working capital.
The QS _TURN variable did not contribute any addi-
tional information.
2. In relation to the spread in prices: analyzing the
SPREAD variable, shares that traded with a bigger di-
fference between maximum and minimum price were
those that exhibited a greater variation in the prices for
the period and a bigger current and future beta; they
belonged to larger companies with less turnover, as al-
ready indicated by the VOL variable. In other words,
this variable also contributed no additional informa-
tion in relation to that resulting from the analysis of
volumes traded.
3. In relation to the variation in prices in the quar-
ter (VAR_PRICE) variable and the (current and future)
BETA variable, shares that exhibited a greater varia-
tion in prices and a bigger beta were those with greater
volume traded and spread. They were also those with
greater market value and volume of assets. Again, the-
re was no new information in relation to those presen-
ted in (1) and (2).
4. Analyzing the variables related to company size
(accounting/SIZE and in market value of shares/MV_
EQUITY), the two calculated proxies are quite corre-
lated (47%). As already shown, the volume of assets
held by a company is positively related to the variation
in prices and beta, to the volume traded, and to the
spread. Companies that were bigger were those that
operate with higher margins and lower turnover, more
net working capital and cash balance, a lower working
capital requirement, a lower quadratic cash balance
(excess liquidity), more self-funding, a better quality
of funding, and that paid more dividends. These cor-
relations indicate that financially unconstrained com-
panies are concerned.
5. Observing the BTM and MTB variables, neither
is correlated. Companies with higher BTM – such as
“value” shares – and shares with higher MTB, such as
“growth” companies (Fama & French, 1993), may be
concerned. In the sample analyzed, companies with
higher BTM traded more, generated more net margin,
used more self-funding, and held more net working
capital and cash balance. They also had more working
capital requirements. Companies with higher MTB ge-
nerated lower ROE and were more in debt.
6. In relation to accounting return, companies that
generated higher ROE were the least in debt, obtained
funding at suitable rates, and paid more dividends.
They were those with lower MTB (growth opportuni-
ties) and traded more in the period. The results indica-
te that mature companies are concerned.
7. In relation to accounting liquidity, net working
capital (NWCASS) and cash balance (CBASS) are per-
fectly correlated. The quadratic cash balance (CBASS2)
is negatively correlated with both. As already shown,
larger companies – with higher BTM, which used more
self-funding and practiced bigger margins – presented
more net working capital. These companies traded
more in the market.
8. Regarding working capital requirements
(WCREQ), smaller companies with higher turnover
exhibited higher working capital requirements than
the rest.
9. In relation to self-funding (SELFF) and the quali-
ty of funding obtained (QFUND_D), larger companies
with a higher BTM ratio obtained more capital in both
ways (they are less constrained). These companies
exhibited a higher ROE, margin, more net working ca-
pital and working capital requirements, a lower qua-
dratic cash balance, and paid more dividends. Their
shares traded more.
10. Finally, the companies that paid more dividen-
ds (DPS, DY, and DP) were the largest, with a greater
capacity for self-funding, a higher quality of funding,
and a higher ROE. The shares in these companies were
traded more. As indicated in (6), the results signal that
mature companies are concerned.
The estimation of the four regressions of interest
was carried out with the aim of verifying the liquidity-
-expected return relationship on the market and ac-
counting levels. Moreover, control variables, chosen
according to the literature from the area, were used in
the four estimated regressions:
1. “MARKET RISK/EXPECTED RETURN” regres-
sion: according to the proposal from Fama and French
(1993), this variable is related to company size (total
assets and market value of shares) and the book-to-
-market ratio. Additionally, it was the aim of this paper
to relate it to market liquidity (volume, turnover, and
spread in prices), to accounting liquidity (net working
capital, working capital requirement, cash balance,
and quadratic cash balance) and to accounting return
(ROE). As it is expected that an increase in accoun-
ting liquidity on date zero, in a context of constraint,
has effects on investments and future accounting re-
turns, the ROEF1 variable was also worked with – in
the regression – which represents accounting returns
4 quarters ahead. Moreover, constraint proxies were
used as independent control variables (dividend per
share, dividend yield and dividend payout, market-to-
-book, self-funding, cost of third-party capital, quality
of funding raised). As a dependent variable, the BE-
TAF1 variable was chosen to represent the market risk/
expected return premium (Sharpe, 1964). As this va-
riable is constructed using observed returns in 60 pre-
vious months until the quarter in question, the varia-
ble was considered 4 quarters ahead. One final point is

Return and Liquidity Relationships on Market and Accounting Levels in Brazil
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016 265
important: under the informationally efficient markets
hypothesis, favorable information regarding future in-
come and cash flow should have the power to increase
share prices on date zero and reduce their market risk/
expected return premium, making it necessary to draw
a distinction between the two variables, which should
be negatively correlated. Thus, an additional variable
was considered (VAR_PRICE), which deals with price
changes resulting from new information received.
2. “MARKET LIQUIDITY” regression: this variable
was related to the market risk/expected return (beta
and future beta, size, and book-to-market ratio), to ac-
counting liquidity (net working capital, working capi-
tal requirement, cash balance, and quadratic cash ba-
lance), and accounting return (ROE and future ROE),
to price variations, and to the constraint proxies (divi-
dend per share, dividend yield, and dividend payout,
market-to-book, self-funding, cost of third-party capi-
tal, quality of funding raised). As a dependent variable,
the QBUS_ TURN (business turnover over the stock of
shares issued) variable was chosen to represent market
liquidity, since it is less subject – in comparison to the
VOL and SPREAD variables – to the scale effect of the
market value of shares. The VOL and SPREAD varia-
bles, however, were used as controls in this regression.
3. “ACCOUNTING RETURN” regression: accor-
ding to the thoughts of Correia and Amaral (2012),
Soares and Galdi (2011), and Matarazzo (2003), sha-
reholder accounting return is related to net margin, to
asset turnover, and to the financial leverage multiplier.
Additionally, it was the aim of this study to relate it to
market risk/expected return (current and future beta,
size, and book-to-market ratio), to market liquidity
(volume, turnover, and spread in prices), to accoun-
ting liquidity (net working capital, working capital
requirement, cash balance, and quadratic cash balan-
ce), and to the variation in share prices. Moreover, the
same constraint proxies were used as controls. As a de-
pendent variable, as it is expected that an increase in
accounting liquidity at date zero, in a context of cons-
traint, has effects on investments and future accoun-
ting returns, the ROEF1 variable was worked with,
which represents accounting returns 4 quarters ahead.
4. “ACCOUNTING LIQUIDITY” regression: it was
the aim of this study to relate it to market risk/expected
return (beta and future beta, size, and book-to-market
ratio), to market liquidity (volume, turnover, and spre-
ad in prices), and to accounting return (ROE and fu-
ture ROE), as well as verifying its effects on variations
in share prices, these were the independent variables
considered in this regression. Moreover, the constraint
proxies were again used as controls. As a dependent
variable, the NWCASS (net working capital per unit
of total assets) variable was chosen to represent ma-
rket liquidity, given its perfect correlation with cash
balance. Quadratic cash balance was also considered
as a control variable in this regression, together with
working capital requirement.
Table 1 Operational description of the variables used in the study
Nº Name Variable Functional Form Reference
1 Dividend per Share DPS Dividends Paid Correia and Amaral
(2012)
Total outstanding shares (issued)
2 Income per Share IPS Net Income Assaf and Lima
(2009)
Total outstanding shares (issued)
3 Market-to-Book MTB Market Value =
〖Price〖fech*Total outstan-
ding shares (issued) Gopalan et al.
(2012)
Accounting Value Net Equity
4 Book-to-Market BTM
Accounting Value
=
Net Equity Fama and French (1993), and Datar
et al. (1998)
Market Value 〖Price〖fech*Total outstan-
ding shares (issued)
5 Market size MV_EQUITY ln (Market Value) = ln (〖Pricefech*Total outs-
tanding shares (issued)
Fama and French (1993), Pastor and
Stambaugh (2001), and Amihud
(2002)
6 Return on Equity (ROE) ROE Net Income
Kania and Bacon (2005), Assaf and
Lima (2009), Soares and Galdi (2011),
and Correia and Amaral (2012)
Net Equity
7Turnover – Quantity of
Securities TURN_QS
Quantity of Securities Traded Demsetz (1968), Datar et al. (1998),
Machado and Medeiros (2012), and
Correia and Amaral (2012)
Total outstanding shares (issued)
8Turnover – Quantity of
Business TURN_QBUS Quantity of business carried out
Demsetz (1968), Chordia et al. (2000),
and Correia and Amaral (2012)
Total outstanding shares (issued)
9 Volume VOL ln (Volume of Business in R$)
Chordia et al. (2000), Minardi et
al. (2005), Machado and Medeiros
(2012), and Correia and Amaral (2012)
10 Spread SPREAD ln Own Elaboration
Pricemaximum t
( )
Priceminimum t

Fernanda Finotti Cordeiro Perobelli, Rubens Famá & Luiz Claudio Sacramento
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016
266
11 Accounting Size SIZE ln (Total Assets)
Beaver, Kettler, and Scholes (1970),
and Oda, Yoshinaga, Okimura, and
Securato (2005)
12 Cost of Debt CSTER Financial Expenses Matarazzo
(2003)
Total ST Loans+Total LT Loans
13 Net Margin NETMAR Net Income Correia and Amaral
(2012)
Net Revenue (Sales)
14 Asset Turnover TURN Net Revenue (Sales) Matarazzo
(2003)
Total Assets
15 Self-funding SELFF Net Income+Depreciation-Dividends Paid Fleuriet et al.
(2003)
Total Assets
16 Dividend Payout DP DPS
IPS
Beaver et al. (1970), Oda et al.
(2005) and Kania and Bacon (2005)
17 Dividend Yield DY DPS
Pricefech
Correia and Amaral
(2012)
18 Net Working Capital NWCASS Net Working Capital Fleuriet et al.
(2003)
Total Assets
19 Working Capital Require-
ment WCRASS Working Capital Requirement Fleuriet et al.
(2003)
Total Assets
20 Accounting Liquidity CBASS Cash Balance Fleuriet et al.
(2003)
Total Assets
21 Excess Accounting Liquidity CBASS2 Cash Balance Own Elaboration
Total Assets
22 Financial Leverage Mul-
tiplier FLM Total Assets Soares and Galdi
(2011)
Net Equity
23 Variation in price VAR_PRICE ln Own Elaboration
24 Quality of Funding Dummy QFUN_D “IF” Function > ccthird = 1 (true) Own Elaboration
25 Market Risk BETA ,with: i=share;
m=market (IBOVESPA)
Sharpe
(1964)
Pricefecht
( )
Pricefecht-1
( )2
EBIT
Total Assets
Cov(i,m)
Var(m)
Note. In the SPREAD variable the maximum value divided by the minimum share quotation was considered, since that way there would be positive values and the natural
logarithm could be applied, with the intention of linearizing the measurement. The BETA variable used the returns from 60 months before the quarter of reference. The
variables related to dividends, because they contained many missing values, were completed with the average for each share, with the aim of making better use of the
database without fundamentally influencing the results obtained.
Table 2 Descriptive Statistics
Variable N Average Standard
Deviation Min. Max.
var_price 36832 -0.0270 0.7270 -2.9920 2.9820
beta 36832 -0.0220 0.1770 -2.8300 2.9710
betaf1 33369 -0.0220 0.1800 -2.8300 2.9710
size 36832 0.0130 0.9550 -2.9840 2.9970
mv_equity 36832 -0.0070 0.9090 -2.9150 2.9970
btm 36832 -0.0100 0.0000 -0.0350 0.0000
vol 36832 0.0010 0.9250 -2.9610 2.5970
qs _turn 36832 -0.0090 0.0010 -0.0090 0.2100
qbus_turn 36832 -0.0120 0.0910 -0.0360 2.2280
spread 36832 -0.3290 0.8420 -1.2730 2.9980
roe 36832 0.0290 0.2040 -2.9980 2.9880
netmar 36832 -0.0180 0.0810 -2.7330 2.1320
turn 36832 -0.2440 0.7230 -1.8740 2.9870
Table 1 Cont.

Relações entre Liquidez e Retorno nas Dimensões Contábil e de Mercado no Brasil
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016 267
Table 2 Cont.
m 36832 -0.0360 0.2120 -2.9230 2.9770
nwcass 36832 0.0320 0.1690 -2.9870 0.3220
wcrass 36832 0.0120 0.4730 -2.9720 2.9940
cbass 36832 0.0320 0.1680 -2.9880 0.3200
cbass2 36832 -0.0110 0.0420 -0.0140 2.5850
selff 36832 0.0140 0.1120 -2.8220 2.3040
ccthird 36832 -0.0400 0.1010 -2.1900 2.6930
Qfun_ d 36832 0.0000 1.0000 -0.3550 2.8130
dps 36832 -0.1020 0.0740 -0.2470 2.7770
dy 36832 -0.0950 0.0760 -0.4280 2.9870
dp 36832 -0.0530 0.0730 -2.7010 2.4390
mtb 36832 -0.0070 0.0860 -2.9850 2.9640

Fernanda Finotti Cordeiro Perobelli, Rubens Famá & Luiz Claudio Sacramento
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016
268
var_price beta beta_f1 size mv_
equity btm mtb vol turn_qs turn_
qbus bid bid_qs bid_
qbus roe roe_f1 netmar turn flm nwcass wcrass stat stat2 selff qfun_d ccthird dps dy dp
var_
price 1
beta 0.0111 1
beta_
f1 0.0031 0.1075 1
size 0.0414 0.1355 0.1203 1
mv_
equity 0.0474 0.1019 0.0907 0.4658 1
btm 0.0046 0.0047 0.0077 0.0435 0.0393 1
mtb -0.0171 -0.0009 0.0035 -0.0171 0.076 0.0007 1
vol 0.0592 0.2069 0.1745 0.5026 0.3456 0.0448 -0.0104 1
turn_
qs 0.0257 0.0158 0.012 0.0023 -0.0447 0.0599 -0.0017 0.0407 1
turn_
qbus 0.0086 0.1081 0.0886 0.1792 0.0039 0.0051 -0.0112 0.3775 0.078 1
bid 0.0801 0.165 0.1149 0.0833 0.0315 0.0155 0.0335 0.2186 0.0379 0.0969 1
bid_qs -0.0022 -0.0108 -0.0017 0.003 0.0855 0.0008 -0.0005 -0.0637 -0.0019 -0.0128 0.0358 1
bid_
qbus 0.0058 -0.0046 -0.003 0.0416 0.138 0.0019 0.0694 -0.1169 -0.0046 -0.0306 0.0851 0.3012 1
roe 0.0407 -0.0047 0.0001 0.0326 -0.0054 -0.004 -0.0736 0.0541 0.0023 0.0317 -0.0033 -0.0164 -0.0044 1
roe_f1 0.0261 0.0071 -0.0058 0.0252 0.0017 -0.0025 -0.0214 0.0394 0.0012 0.026 -0.0006 -0.02 -0.0065 0.0496 1
netmar 0.0147 -0.0042 -0.0112 0.0819 0.0524 0.0453 0.0007 0.0406 -0.0008 0.0258 -0.0178 0.0006 0.0016 0.0003 0.0006 1
turn 0.0189 -0.0364 -0.0372 -0.1274 -0.1112 0.0173 0.005 -0.0923 -0.004 -0.0283 -0.0456 0.0042 -0.0051 0.0176 0.005 0.011 1
m -0.0045 -0.0183 -0.0008 0.0292 0.0276 0.0104 0.0626 -0.0374 -0.003 -0.0124 -0.0095 0.0061 0.0533 -0.4031 -0.0056 0.01 0.0544 1
nw-
cass 0.0222 0.0174 0.0185 0.1788 0.1204 0.1738 0.007 0.0891 0.0011 0.0144 0.0052 0.0024 0.0067 -0.0177 -0.0064 0.3295 0.0129 0.0356 1
wcrass -0.0089 0.0066 0.0045 -0.0835 -0.0901 0.0469 -0.0141 0.0289 0.0079 0.0556 -0.0319 -0.0312 -0.0471 0.0098 -0.015 0.0552 0.1898 -0.0089 0.1276 1
stat 0.0222 0.0174 0.0183 0.1812 0.1223 0.1739 0.0073 0.0892 0.001 0.0133 0.0063 0.003 0.0076 -0.0177 -0.006 0.3304 0.0088 0.0357 0.9992 0.1082 1
stat2 -0.0128 0.0035 0.0058 -0.0966 -0.0534 -0.0356 -0.0026 -0.0241 -0.0002 -0.0094 0.0084 -0.003 -0.0067 0.0076 0.0029 -0.1827 -0.0198 -0.0194 -0.1629 -0.0359 -0.1633 1
selff 0.0337 0.014 0.0105 0.2016 0.0979 0.091 0.0018 0.0916 0.0016 0.0322 -0.0066 0.0016 0.004 -0.0039 0.0032 0.2175 0.0418 0.0321 0.5363 0.0854 0.5378 -0.3787 1
qfun_d 0.0444 0.041 0.0349 0.2035 0.0759 0.0002 0.0001 0.1629 -0.0018 0.0958 0.0123 -0.0092 -0.0135 0.072 0.0429 0.025 0.032 -0.0066 0.0383 0.0464 0.0376 -0.0071 0.0736 1
ccthird 0.0009 -0.0201 -0.0032 -0.0453 -0.0033 -0.0056 -0.0078 -0.0274 -0.0031 -0.0153 -0.0155 0.0008 -0.006 0.0056 -0.0061 -0.0084 0.0175 0.005 -0.0119 0.0018 -0.012 0.0138 -0.0309 -0.0474 1
dps 0.005 0.0105 0.0083 0.155 0.0216 0.0032 -0.0079 0.116 0.0015 0.1407 -0.0299 -0.009 -0.0214 0.05 0.0311 0.0234 0.0315 -0.0054 0.0248 0.0377 0.024 -0.01 0.0606 0.1108 -0.0125 1
dy -0.0025 0.0134 0.0103 0.1071 -0.0347 0.0084 -0.0074 0.0958 0.0076 0.1076 -0.0049 -0.0085 -0.0198 0.0369 0.0278 0.0233 0.0359 -0.0071 0.0263 0.0217 0.0258 -0.0093 0.0541 0.0856 -0.0126 0.4535 1
dp 0.0061 0.0155 0.0116 0.0897 0.0257 0.0018 -0.0046 0.0883 0.0011 0.0876 -0.0025 -0.0039 -0.0107 0.0174 0.0104 0.0099 0.0034 -0.0029 0.016 0.0215 0.0155 -0.0061 0.0283 0.0476 -0.0112 0.204 0.1861 1
Table 3 Correlations between variables

Return and Liquidity Relationships on Market and Accounting Levels in Brazil
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016 269
3 RESULTS AND ANALYSES
As explained, four panel regressions were estima-
ted for market risk/expected return (dependent varia-
ble = BETAF1); market liquidity (dependent variable =
QBUS_TURN); accounting return (dependent variable =
ROEF1), and accounting liquidity (dependent variable =
NWCASS). e Hausman test was then carried out, com-
paring the xed and random eects models and verifying
the null hypothesis that there is no systematic dierence
in the coecients generated by the two models (Wooldri-
ge, 2010). In rejecting the null hypothesis, the use of xed
eects is admitted with the best estimator. All of the tests
revealed the presence of xed eects and these will be the
results discussed. e time xed-eects were also tested,
which involved including a dummy variable for each year.
However, the results were not aected and, for prudence,
we kept only that related to 2008, due to the global cri-
sis. Additionally, all of the regressions were estimated with
cluster corrections related to the shares, which eliminates
the eect of autocorrelation and heteroskedasticity in the
panel estimation. e signicant variables in each regres-
sion are shown in Tables 4, 5, 6, and 7 and are discussed
following each table.
coefficient four quarters ahead is negatively related to
the variation in prices in the current quarter, which
allows it to be used as a proxy for market risk/expec-
ted return. Statistically, the regression revealed that a
higher market risk/expected return was positively rela-
ted to a higher volume of trading, turnover, and spread
in prices for the assets in the sample and the period in
question. Additionally, shares that exhibited higher ma-
rket risk/expected return belonged to larger companies,
but which paid fewer dividends per share. These shares
performed worse in 2008. Thus, no hypotheses relating
to market risk/expected return and firms’ accounting
return and accounting liquidity (H2 and H5) were sup-
ported. The positive relationship between market risk/
expected return and turnover, volume, and spread in
prices indicates a negative premium for market liquidity
in the Brazilian market, as already verified by Minardi
et al. (2005).
Table 4 Regression 1 (Market risk/expected return)
Table 5 Regression 2 (Market Liquidity)
betaf1
var_price -0.002
(0.001)
vol 0.011***
(0.003)
spread 0.009***
(0.002)
size 0.014**
(0.005)
dps -0.028*
(0. 012)
yd2008 -0.013***
(0.003)
Constant -0.021***
(0.001)
Observations 33,369
R20.004
ρ0.116
p-value for F (6,852) 0.000
vol
spread 0.051***
(0.009)
var_price 0.051***
(0.004)
beta 0.184***
(0.026)
betaf1 0.092***
(0.024)
size 0.342***
(0.052)
btm 129.024***
(14.886)
m -0.080**
(0.027)
wcrass 0.053*
(0.027)
qfun_d 0.032***
(0.006)
dp 0.229***
(0.055)
dps 0.179*
(0.078)
yd2008 0.155***
(0.018)
Constant 1.348***
(0.152)
Observations 33,369
R20.069
ρ0.603
p-value for F (12,852) 0.000
According to the first regression of interest, there is
an indication (despite not being statistically significant
with fixed effects and correction for autocorrelation and
heteroskedasticity, but significant in the estimations for
minimum squares and for random effects) that the beta
Note. Standard deviations in brackets.
* p < 0.05, ** p < 0.01, *** p < 0.001
Note. Standard deviations in brackets.
* p < 0.05, ** p < 0.01, *** p < 0.001

Fernanda Finotti Cordeiro Perobelli, Rubens Famá & Luiz Claudio Sacramento
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016
270
Analyzing the regressions related to market liquidi-
ty, it was observed that shares with higher turnover per
unit of shares issued were of lower market value (scale
factor), but also exhibited greater trading volume and
higher spread in prices and belonged to companies with
more assets. Because they had more assets, these compa-
nies turned over less, were less in debt, and carried less
net working capital, despite contracting loans at favora-
ble rates and paying more dividends. e results indicate
that nancially unconstrained companies are concerned.
Again, it is veried that these companies’ shares enjoyed
greater market risk/expected return, generating a nega-
tive premium for liquidity. e negative relationship be-
tween market and accounting liquidity (NWCASS) sup-
ports H6 in a context of no constraint. H4 (relationship
between market liquidity and accounting return) cannot
be conrmed.
Table 6 Regression 3 (Accounting Return)
Table 7 Regression 4 (Accounting Liquidity)
roef1
m 0.026*
(0.012)
var_price 0.005**
(0.002)
qfun_d 0.005***
(0.001)
dps 0.032***
(0.009)
dy 0.017*
(0.007)
yd2008 0.012*
(0.005)
mtb -0.053*
(0.022)
wcrass -0.017**
(0.006)
Constant 0.034***
(0.001)
Observações 33,369
R20.003
ρ0.107
p-value for F (8,852) 0.000
nwcass
netmar 0.075
(0.043)
m 0.005*
(0.002)
wcrass 0.033**
(0.012)
selff 0.423***
(0.068)
ccthird 0.013
(0.008)
dps -0.030***
(0.009)
mtb 0.004***
(0.001)
Constant 0.024***
(0.002)
Observations 36,832
R20.113
ρ0.372
p-value for F (7,871) 0.000
Note. Standard deviations in brackets.
* p < 0.05, ** p < 0.01, *** p < 0.001
Note. Standard deviations in brackets.
* p < 0.05, ** p < 0.01, *** p < 0.001
Observing the third regression, related to accoun-
ting return (ROEF1), it can be verified that companies
with higher accounting return 4 quarters ahead were
those that held more self-funding, were more in debt,
captured favorable rates, paid more dividends, but were
smaller (in total assets and market value) and faced
fewer growth opportunities (lower MTB) in the period.
In relation to the market variables, their assets expe-
rienced greater variations in prices. Again, it appears
that unconstrained companies are concerned, but with
few growth opportunities. The hypotheses relating
ROE to accounting liquidity (H3), to market liquidity
(H4), and to market risk/expected return (H5) could
not be confirmed.
In the fourth and last regression, related to accounting
liquidity (NWCASS), it can be observed that companies
that carried more net working capital in the period were
those with more working capital requirement, but opted
to hold excess liquidity (CBASS2), practicing more self-
-funding and fewer dividend payments. ey were also
the ones that operated with higher margins (NETMAR).
ese companies exhibited lower accounting returns and
lower market liquidity, supporting H3 and H6. It is belie-
ved that the rst order eect in this regression is not one
of constraint, but of carrying excess liquidity. e hypo-
thesis related to market risk/expected return (H2) cannot
be conrmed.
4 FINAL REMARKS
As the first proposed aim, we sought to identify whe-
ther more liquid shares exhibited lower market risk/
expected return. In Regression 1, it was observed that
shares that enjoyed greater market risk/expected return

Return and Liquidity Relationships on Market and Accounting Levels in Brazil
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016 271
traded more and with a higher spread in prices, genera-
ting a negative market liquidity premium in the sample
and period considered, as in Minardi et al. (2005). These
shares belonged to companies with more assets and with
fewer dividend payments per share.
With regards to market liquidity, it was observed that
shares with higher turnover in the period were those
with a lower market value of shares (scale factor). These
shares also exhibited a higher spread in prices and be-
longed to companies with more assets. Because they had
more assets, these companies turned over more, were
less in debt, and carried more net working capital, des-
pite contracting loans at favorable rates and paying more
dividends. The results indicate that financially uncons-
trained companies are concerned.
The second aim of this paper was to verify whe-
ther carrying more liquid assets, or rather, more ac-
counting liquidity, would entail lower accounting re-
turn, given that operational risk would decrease with
a more conservative investment policy, or whether the
presence of financial constraint would make this rela-
tionship positive, as well as observing the breakdown
of accounting measures regarding return and market
liquidity indicators.
In Regression 3, it could be verified that higher future
accounting return was observed in companies that held
more self-funding, were more in debt, captured favora-
ble rates, paid more dividends, but were smaller (in to-
tal assets and market value) and faced fewer investment
opportunities. In relation to the market variables, their
assets experienced greater price variations. It appeared
that mature, unconstrained companies with fewer gro-
wth opportunities were concerned. The accounting re-
sults of these companies only generated effects on short
term price variations, not having a relationship with ac-
counting liquidity, with market liquidity, or with market
risk/expected return.
Finally, in relation to accounting liquidity, it could be
observed that companies that carried more net working
capital in the period were those with more working capi-
tal requirement, but also those that opted to hold excess
liquidity, practicing more self-funding and fewer divi-
dend payments. They were also those that operated with
higher margins. These companies exhibited a lower ac-
counting return and lower market liquidity. It is believed
that both effects result from choosing excess accounting
liquidity and not from potential financial constraints,
supporting hypothesis H3 (negative relationship betwe-
en accounting return and excess accounting liquidity)
and H6 (negative relationship between market liquidity
and excess accounting liquidity).
No relationship between market risk/expected re-
turn and accounting return and liquidity could be es-
tablished in the – still underdeveloped – Brazilian ma-
rket, with investors preferring to trade shares in larger
and less constrained companies enjoying a negative li-
quidity premium.
On the margins of the main theories regarding the is-
sue, only the negative relationships between accounting
liquidity and market liquidity (H6) and accounting re-
turn (H3) – in a context of no financial constraint – were
correctly verified with regards to Brazil.

Fernanda Finotti Cordeiro Perobelli, Rubens Famá & Luiz Claudio Sacramento
R. Cont. Fin. – USP, São Paulo, v. 27, n. 71, p. 259-272, mai./jun./jul./ago. 2016
272
Correspondence Address:
Fernanda Finotti Cordeiro Perobelli
Universidade Federal de Juiz de Fora, Faculdade de Economia
Rua José Lourenço Kelmer, s/n – CEP: 36036-900
São Pedro – Juiz de Fora – MG
Email: fernandanotti.perobelli@ufjf.edu.br
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