Proceedings of Applied International Business Conference 2008
WORKING CAPITAL POLICIES: PRACTICES OF FIRMS IN BURSA MALAYSIA
Zariyawati Mohd Ashhari ψ and Annuar Md Nassir
Univeristi Putra Malaysia, Malaysia.
Abstract
There is no doubt that working capital is important to a firm. The efficient working capital management is
an integral part of overall management strategy to create shareholders’ wealth. Further, there is not a single
working capital policy that is suitable for all firms. Each firm requires a policy which can maximised
shareholders’ wealth. However, to have an optimal working capital a firm should strive to balance its risk
and return; it is a trade-off between profitability and liquidity. Therefore, this study aims to investigate the
working capital policies practised among firms in Bursa Malaysia. Results for the degree of aggressive
asset management show the sector had distinctive and significantly different policies. Further, the asset
policies between sectors revealed significant stability over the twelve year study period. The results of this
study also showed a high and significant negative correlation between sector of asset and liability policies.
This is revealed when a firm applied aggressive working capital asset policies which followed by
conservative working capital financial policies.
Keywords: Working capital policy; Management; Bursa Malaysia.
JEL Classification Codes: G14; G24.
1. Introduction
The most widely accepted objective of a firm is to maximize the value of the firm, that is, to maximise
shareholders’ wealth. The objective could be achieved with good management on all aspects including
managing the working capital efficiently. This is especially critical, when making financial decisions. Poor
concerning on working capital of a firm in financial decision making would affect the business failure
(Smith, 1974). This is due to working capital involvements in daily operation. Its short term investment in
nature makes it essential in making decision to ensure a firm’s sustainability in long term period.
The crucial part in managing working capital is to uphold its liquidity in daily operation thus ensure its
smooth running and meets its obligation. Yet, this is not a simple task since managers must make sure that
business operation is running in efficient and profitable manner. There are the possibilities of mismatch of
current asset and current liability during this process. If this happens and firm’s manager failed to manage it
properly then it will affect firm’s growth and profitability (Raheman and Nasr, 2007). This will further lead
to financial distress and finally firms can go bankrupt.
Dilemma in working capital management is to achieve desired tradeoff between liquidity and profitability
(Shin and Soenon, 1998; Smith 1980). Referring to theory of risk and return, investment with more risk
will result to more return. Thus, firms with high liquidity of working capital may have low risk then low
profitability. Conversely, firm that has low liquidity of working capital is facing high risk results to high
profitability. The issue here is in managing working capital, firm must take into consideration all the items
in both accounts and try to balance between the risk and return. Manager always use working capital policy
as a guide in managing firm’s working capital. According to Salawu (1998), the operations of firms are
subject to seasonal or cyclical fluctuations. A conservative policy of working capital management means
that firm finance some or all its temporary current assets with long term funds. This policy provides high
liquidity and low risk but low profitability to a firm. On the other hand, the application of an aggressive
policy of working capital is when firm finances some of its permanent current asset, along with all of its
ψ
Corresponding author: Zariyawati Mohd Ashhari. Department of Accounting and Finance, Faculty of
Economics and Management,University Putra Malaysia, 43400 Serdang, UPM, Selangor. Email:
[email protected]
Proceedings of Applied International Business Conference 2008
temporary current assets with short term funds. Thus, it offers low profitability and high risk but
complimented with high profitability to a firm.
The purpose of this study is to examine the working capital policies between industries in Malaysia. The
primary objective is to investigate if there is significant difference between industries’ working capital
policy. This study also analyses whether firms use aggressive or conservative working capital policies for
its investment and financing purposes.
2. Related literature
Even though there are several working capital policies such as conservative and aggressive that act as
guidance in managing working capital, no single policy is necessary optimal to all firm (Moyer et al.,
2003). Filbeck and Krueger (2005) organised surveyed firms across key components of working capital
management by using the CFO magazine’s annual Working Capital Management Survey. They discovered
that significant differences exist between industries in working capital measures across time. In addition,
they also find out that these measures for working capital change significantly within industries across
time.
Weinraub and Visscher (1998) use Compustat data that including ten diverse industry groups to examine
the relative relationship between their aggressive or conservative working capital policies. The results show
that the industries had significantly different current asset management policies. Additionally, the relative
industry rankings of the aggressive or conservative asset policies display remarkable stability over time.
Besides, industry policies concerning relative aggressive or conservative liability management were also
significantly different. Further, the evident also showed high and significant negative correlation between
industry asset and liability policies. They suggested aggressive working capital asset management seems
balanced by conservative working capital financial management.
The later research by Salawu (2006) examines the existence of the aggressive or conservative working
capital between industries in Nigeria. Data were sourced from the annual reports of the companies and the
publications of Nigerian Stock Exchange. The result is consistent to Weinraub and Visscher (1998) study
which show that the industries had significantly different current asset management policies. Moreover, the
relative industry ranking of the aggressive or conservative asset policies show signs of remarkable stability
over time. He also founds a significant negative correlation between industry asset and liability policies. He
suggested that in deciding its working capital policies, a firm should consider the policies adopted in that
particular industry in which it operates. When a firm is pursuing aggressive working capital investment
policy, it should match to a conservative working capital financing policy.
3. Methodology
The data used in this study were gained from Datastream. The data includes annual figure of Current
Assets, Current Liabilities and Total Assets of firms in Bursa Malaysia (formerly Kuala Lumpur Stock
Exchange) between years 1995 to 2006. The reason to analyse 12 years data is to take into consideration of
period before, during and after economic crisis. A firm needs to increase working capital during expanding
economic activity and decrease during contracting economic activity (Lamberson, 1995). Firm that merged
or took over by other firm is excluded from the sample. The sectors that have less than 10 firms are also
excluded from the sample. Final sample consists of 189 firms from six sectors, after segregation of the
criteria and expelled firms which have missing data. The range of firms is between 10 and 62 in each
sector. To remove the effects of seasonality, quarterly data for all firms in each sector were added and
averaged together.
The degree of aggressiveness level is gained by calculate the ratio of Currents Assets (CA) and Current
Liabilities (CL) divided to Total Assets (TA). The degree of aggressiveness of working capital investment
(DOAI) is calculated by current assets divide to total assets. The higher the ratio is the more aggressive
working capital investment policy.
DOAI = CA/TA
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Proceedings of Applied International Business Conference 2008
While, the degree of aggressiveness of financing policy (DOAF) is calculated by Current Liabilities divide
to Total Assets. The higher the ratio is the more aggressive working capital financing policy.
DOAF = CL/TA
Table 1 exhibit twelve year industry means and standard deviation for each sector. From the table,
Consumer Product sector has the most aggressive of working capital investment policy due to the current
assets is more than 52.6% of total assets. However, the most aggressive working capital financing policy is
Industrial Product sector that shows the results of total assets is financed by more than 46% current
liabilities.
Sector
Construction
Consumer Product
Industrial Product
Plantation
Property
Trading/Services
Table 1: Twelve-Year sector means and standard deviations
CA/TA
TCL/TA
No. of
Firms
Mean
STD
Mean
13
0.4926
0.0353
0.3930
31
0.5261
0.0282
0.4128
62
0.4342
0.0184
0.4606
22
0.2596
0.0212
0.1707
10
0.3360
0.0826
0.2033
51
0.3854
0.0268
0.3207
STD
0.0537
0.0444
0.1159
0.0621
0.0373
0.0292
4. Results
Differences in policies
One-way ANOVA was applied to the set of 12 years average ratio means as an analysis to achieve
objective of the study that is to examine the determine if a significant difference exists in the aggressive or
conservative working capital policies between sectors. To find the different between sectors for investment
working capital policy, the current asset to total asset ratio is used in this analysis. Table 2 shows F-ratio of
68.69 and it indicates the differences in the means are highly significant. Further the strength of differences
between sector values is examined using Tukey’s HSD test by comparing the sector means on a paired
sample basis. These results are also presented in Table 2 and show that 12 of the 15 comparisons are
significant at the 1% level, one more at 5% and only 2 comparisons are not statically significant. Both The
ANOVA and Tukey’s HSD tests clearly show a distinctive difference in the asset management policies
between sectors.
Table 2: Significance levels for industry mean differences of the current asset / total asset ratio (F test
and Tukey’s HSD)
F- statistic = 68.69
Construction
Consumer
Industrial
Plantation
Property
Product
Product
Consumer Product
-0.1072**
Industrial Product
0.0584*
0.0919**
Plantation
0.2330**
0.2665**
0.1746**
Property
0.1566**
0.1900**
0.0982**
-0.0764**
Trading/Services
0.1072**
0.1407**
0.0488
-0.1258**
0.0494
Notes: *Significant at 5% level. ** Significant at 1% level.
Differences in the relative degree of aggressive or conservative liability management were measured by
performing a one way ANOVA on the current liability means to total asset means. Table 3 displays F-ratio
was 42.39. Tukey’s HSD was also applied to this data and that is 10 of the 15 comparisons shows a
significant difference at the one percent level. The balances of 5 comparisons are not statistically different.
This is reveals that significant sectors differences do exist in the relative degree of aggressive or
conservative working capital policies for both asset and liability management. However, from the result the
evident from ANOVA and Tukey’s HSD tests shows the differences are more significant on asset
management policies compared to liability management policies.
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Proceedings of Applied International Business Conference 2008
Table 3: Significance levels for industry mean differences of the current liability / total asset ratio (F
test and Tukey’s HSD)
F- statistic =42.39
Construction
Consumer
Industrial
Plantation
Property
Product
Product
Consumer Product
-0.0197
Industrial Product
-0.0640
-0.0442
Plantation
0.2223**
0.2420**
0.2863**
Property
0.1897**
0.2094**
0.2536**
0.0326
Trading/Services
-0.0723
0.0920**
0.1363**
-0.1500**
-0.1174**
Note.: ** Significant at 1% level.
Stability between policies
The stability of relative differences between sectors over time is examined after established the twelve year
ratio means were significantly different between sectors. To test relative stability the analysis of rank order
correlations is applied to data. The Current Asset to Total Asset ratio for each of the twelve years was
computed for each sector and then ranked from the highest to lowest ratio. The base year ranking is 1995.
The sequential is compared to the rankings of each succeeding year. The results are presented in Table 4.
Results show the relative level of aggressiveness with respect to working capital investment for each sector
sustained over time at 1% significant level.
The sectors were also ranked each year on the basis of current liabilities to total assets ratio to examine the
relative stability on working capital financing policy. The results of rank order correlations are also
presented in Table 4. The relationship between these ratios is also stable at 1% significant level which is
consistent to the Current Asset to Total Asset ratios except in year 2005. However, liability management
policy stable again in year 2006. The unexpected change of Trade/Service sector to the lowest rank in 2005
compared to never in the lowest rank before was affected the policies stability in 2005.
Table 4: Rank order correlations and z values between base year and each succeeding year for
current assets/total assets and total current liabilities/total assets
Year
CA/TA
Z-Value
CL/TA
Z-Value
1996
1.000
**
1.000
**
1997
1.000
**
1.000
**
1998
1.000
**
1.000
**
1999
1.000
**
1.000
**
2000
1.000
**
1.000
**
2001
1.000
**
1.000
**
2002
1.000
**
1.000
**
2003
1.000
**
1.000
**
2004
1.000
**
1.000
**
2005
1.000
**
0.771
2006
1.000
**
1.000
**
Note.: ** Significant at 1% level.
Relationship between asset and financing policies
Table 5 displays results of relationship between the asset management policy and liability management
policy, which means, how aggressive asset management corresponded to aggressive financial management
for twelve year study period. This relationship was tested on a year by year basis. For the first year, the
sectors were ranked from low Current Asset to Total Asset ratios to high ratios, corresponding to ascending
order of relatively aggressive policies. Then, rankings were also ordered from high to low Current Liability
to Total Asset ratios for the first year, again corresponding to an ascending order of aggressiveness.
Further, rank order correlations for year one were computed between the two policies. This procedure was
repeated for each of the remaining eleven years.
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Proceedings of Applied International Business Conference 2008
Without exception the correlations between the two policies were highly negative for each year, and they
are significant at the one percent except for 2003 and 2005 which is at 5% significant level. This negative
relationship evident consistent to the study (Weinrub and Visscher, 1998; Salawu, 2003) that sector which
pursued relatively aggressive asset policies simultaneously followed relatively conservative financing
policies.
Table 5: Rank correlation per year of aggressive asset policies and aggressive financing policies
Year
Correlation
Z-value
1995
-1.000
**
1996
-1.000
**
1997
-1.000
**
1998
-1.000
**
1999
-0.943
**
2000
-0.943
**
2001
-1.000
**
2002
-0.943
**
2003
-0.886
*
2004
-1.000
**
2005
-0.829
*
2006
-0.943
**
Policies changes
Evident above were show that sector policies change over time. However the question arises whether they
change in the same direction and at the same time, representing a possible macroeconomic influence. To
examine the relationship in the changes between sectors regression analysis was used to data.
The twelve current asset to total asset ratios for each sector were regressed against the ratios for each other
sector. The results of the regressions of the 15 pairs of sectors are presented in Table 6. Two third
relationships are positive, and 3 regressions have significant results 5% level. The balance of 5
relationships is negative and not significant. The 3 regression that have significant result is belong to sector
Consumer Product and Industrial Product due to nature of business compliment to other sector that change
together with them. In general, the natures of business for each sector that is extremely different results to
different direction and time of working capital investment policies changes.
Table 6: Regressions, between industries, of current asset / total asset ratios for the ten year period
(R-Squared and t values)
Construction
Consumer
Industrial
Plantation
Property
Product
Product
Consumer Product
-0.042
Industrial Product
0.287
0.566
Plantation
0.259
-0.692
-0.203
Property
0.524
-0.070
0.671*
0.077
Trading/Services
0.238
0.692*
0.706*
-0.497
0.413
Note: *Significant at 5% level.
Regarding changes in working capital financing policies, there are also three regressions were significant at
the 1% or 5% level the exhibit in Table 7. Industrial Product, Plantation and Property were correlated with
another sector respectively. However, the correlation between Industrial Product and Plantation is
negatively at 1% significant level.
The lack of correlation between the working capital investment policies and working capital financing
policies of these sectors appears to suggest that the policies are independent of any external factors. In
addition, changes in financing policies over time may influence by sectors’ factors rather than investment
policy changes.
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Proceedings of Applied International Business Conference 2008
Table 7: Regressions between industries of current liability / total asset ratios for the twelve year
period (R-Squared and t values)
Construction
Consumer
Industrial
Plantation
Property
Product
Product
Consumer Product
0.280
Industrial Product
0.434
0.221
Plantation
-0.196
0.210
-0.823**
Property
0.583
0.245
0.382
0.583
Trading/Services
0.063
0.441
-0.476
0.769**
0.587*
Notes: *Significant at 5% level. ** Significant at 1% level.
5. Conclusion
This study examined the relative relationship between their aggressive or conservative working capital
policies at twelve diverse industry sectors in Bursa Malaysia. Regarding the degree of aggressive asset
management, the industries had distinctive and significantly different policies. Additionally, the relative
nature of the asset policies among sectors exhibited remarkable stability over the twelve year of study
period. Besides, sectors policies regarding the relative degree of aggressive liability management also were
significantly different or with the same stability except in year 2005. Interestingly, this study also showed a
high and significant negative correlation between industry asset and liability policies. It appears that when
relatively aggressive working capital asset policies are followed they are balanced by relatively
conservative working capital financial policies. This is important to mitigate the risk being faced under
working capital investment policies by safety involved with conservative working capital policies.
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