Key Factors Affecting Corporate Liquidity
Info: 5408 words (22 pages) Example Literature Review
Published: 9th Dec 2019
Liquidity was found to be one of the most important unresolved problems in the field of corporate finance (Brealy and Myers, 1996). In addition, the same studies found that the liquidity management was the pinpoint of determining both future investment opportunities and future capacity of external borrowing.
Firms, in general, invested in the liquid assets. Liquid assets made up a substantial division of total capital or assets and had the more important implications for the risk and profitability of firms (John, 1993). For instance, according to Kim, David, and Ann (1998), the average ratio of cash plus marketable securities to total assets (Liquidity) was 8.1% during the period of 1975 to 1994 of a sample of 915 industrial firms of the United States of America. Kim et al. (1998) analyzed both the costs and benefits of holding the liquid assets and concluded that the investment in liquid assets (e.g., Treasury Securities) was more costly because by investing in liquid assets, the firms accepted opportunity cost of investing in less liquid and more rewarding assets; furthermore, the firms also bear transaction costs of trading financial securities. However, firms managed significant and predictable amounts of excess liquid asset holdings because of the capital market imperfections provided a strong logic to maintain some excess liquidity to tackle some emergencies. Huberman (1984), Ang (1991), and Myers and Rajan (1995) had noted that liquid assets might prompt more severe agency problems than less liquid assets.
Specifically, if and only if the external financing was costly then the investment in liquid assets was the most advantageous reply to having to seek costly external financing to fund future production needs or investment opportunities and the costs of external financing included the direct expense to issue securities, the costs arising from potential agency conflicts, and costs arising from the adverse selection problems attributable to asymmetric information (Smith, 1986). Thus, investment in surplus liquidity could be viewed as a cost-effectively rational way to reduce the firm’s reliance on costly external financing. Obviously, any such remuneration must be balanced against the holding costs that liquid assets force on the firm. Liquid assets earned a low rate of return as compared to the less liquid assets. However, the firms despite decided to hold a positive amount of liquid assets provided undecided future in-house funds and costly external financing. Hence, it was concluded that there was a tradeoff between the holding cost of liquid assets (a low rate of return) and the benefit of minimizing the need to seek costly external financing if internally generated funds were insufficient to finance future investment opportunities.
According to Horne and David (1968), liquidity could be expressed as the ability to realize value in an accepted means of exchange. Being the acceptable means of exchange, money was the most liquid asset and was also a benchmark against which the value of other type of monetary assets was compared as to its degree of replacement. In addition, liquidity had two dimensions: the one was the time required to convert the asset into money, and the other was the certainty of the price realized, i.e., the stability of the exchange ratio between the money and the asset.
In the business world, there was the high corporate demand for liquidity and firms in the real, financial and industrial sectors managed its liquidity needs in the numerous ways in order to carry out further production and investment plans efficiently without being stopped by impermanent liquidity deficiencies. The firms’ decisions regarding the future ability to avail financial funds was affected by several key factors such as the capital structure set deadlines for settling the amounts to investors, corporations did not invest all of its resources in the most profitable, long term projects and in fact firms also invested funds in less profitable liquid assets, the corporations engaged in the risk management and derivatives were used to evade the particular risks (such as rate risk, exchange rate risk, etc.), and lastly, international risk burden was also measured by the companies. (Holmstrom and Jean, 2000)
1.2 Problem Statement
In the corporate finance, the liquidity was considered to be one of the most important issues. The main objective behind the study of the corporate liquidity was that this was the most important issue for the present firms either to invest in the more liquid assets or to invest in the less liquid assets. Furthermore, investment in liquid assets was prompted by several other factors such as the future investment opportunities and future uncertain cash flows and the external costly financing. Contrastingly, the investment in less liquid assets attracted the corporations because of the high rate of return of such investments.
The purpose of the study was to notice whether the financial factors explained in detail by Kim and David and Ann (1998), and John (1993), presented the detail regarding the choice of the firm to invest in liquid or non-liquid assets in Pakistan. The scope of study was to analyze the distinctive financial factors which affected the firms’ decisions to place their funds in more liquid assets and on the basis of firms’ financial factors, the research study determined the choice of investing in liquid assets or the choice of having internal liquidity.
1.3 Hypotheses
A central query in front of firms that needed new finance to invest in operational activities was whether to use internal funds generated through the most liquid assets or to raise the costly external financing. Various factors influenced the decision to invest in liquid assets (liquidity). The firm’s characteristics had the great importance in selection of the investment decisions; these characteristics were firm size, operating income divided by sales ratio, operating income divided by total assets ratio, market to book ratio, inventory plus gross fixed assets to total assets ratio, annual sales, total debt ratio, and long term debt ratio. Many authors as Kim and David and Ann (1998), and John (1993) discussed these characteristics in research. The hypothesized relationship of these listed factors with liquidity is provided below:
H1: There is impact of Firm Size on Liquidity.
H2: There is impact of Total Debt Ratio on Liquidity.
H3: There is impact of Long-Term Debt Ratio on Liquidity.
H4: There is impact of the ratio of the Market to Book Value of Equity on Liquidity.
H5: There is impact of the ratio of Operating Income divided by Sales on Liquidity.
H6: There is impact of the Operating Income divided by Total Assets ratio on Liquidity.
H7: There is impact of ratio of Inventory and Gross fixed assets to Total Assets on Liquidity.
H8: There is impact of sales of firms on liquidity.
1.4 Outline of the Study
The research structured as follows. Chapter one was based on the introduction of the thesis, which consisted of the some introduction of the liquidity by different authors, the statement of problem, scope and objectives, hypothesis etc. Chapter two consisted of literature review given by different authors, theories on liquidity and factors affecting the choice of decision to invest in more liquid assets or not. Chapter three described methodology which is composed of justification of the selection of the variables utilized in analysis sample, the data, technique and hypothesis, also estimate model utilized in analysis. In chapter four, analyses of the results were there which were taken after the data processing. Chapter five contained the final results, conclusions and recommendations. References were included in chapter number six.
CHAPTER 2:
LITERATURE REVIEW
When a firm wanted to invest in a project or production facilities, there was a question before the firm that it wanted to use its own funds or retained earnings or to raise an external financing. The firm’s answer to this question did not affect the wealth of security holders in the world of Miller and Modigliani (1961) where the capital markets were perfect. However, among other things, the capital market perfection means the absence of liquidity problems. Resultantly, all assets could be exchanged for cash and vice versa, that exchange was made at the market value, and it did not entail a loss. (Huberman, 1984)
The real markets were not quite perfect and one could see a variety of reasons about it. Consider the example of firms wishing to finance new projects by issuing claims on the projects. If the firms knew more about the projects than the outside world knew and the claims were considered risky, a market collapse may take place (Ackerlof, 1970). If firms believed its projects were good, would perceive that their claims were undervalued by the market and would not issue such claims and only the projects of pessimistic firms would be financed (Huberman, 1984).
Finally, it was the best option that a firm used its own liquid assets to invest quickly without going to the capital market under certain circumstances. Hence, it was the most desirable that a firm possessed the excess liquid assets in the real world of capital markets imperfection (Huberman, 1984).
There was a vast literature available on the liquidity and one of the most prominent theories of liquidity was the Liquidity Preference Hypothesis (LPH).
2.1 Liquidity Preference Hypothesis (LPH):
The Liquidity Preference Hypothesis (LPH) gave details that the return on government securities was a monotonically rising function of the time to maturity. That was, restricted on all on hand information, the probable monthly return on a T-bill with one year to maturity should surpass the probable monthly return on a six month T-bill, which should be better than the sure yield on a one month T-bill, and so on. Regardless of the shape of the term structure or any other economic variables contained in the agent’s information set, the LPH meant this condition. The underlying intuition behind the LPH was that the longer-term bonds are riskier; that was, they were more susceptible to the fluctuations or volatility in interest rate than the shorter-term bonds and the individuals needed to be compensated for the risk of holding these bonds, hence, the higher predicted yield. (Boudoukh and Matthew and Tom and Robert, 1999)
The LPH did not worry about the choices investors made between the whole variety of financial assets, on the one hand, and other broad classes of assets, on the other. LPH took as given the choices determining how much wealth was to be invested in financial assets and concerned itself with the distribution of these amounts among cash and substitute financial assets. An issue could be identified here; that was, why should any balances be held in cash, in preference to other financial assets? The author distinguished two possible sources of liquidity preference, while recognizing that these were not mutually exclusive. The first was inelasticity of expectations of future interest rates. The second was insecurity about be future of interest rates. (Tobin, 1958)
Tobin (1958) argued liquidity preference as the theory of most advantageous portfolio masterpiece in a two-asset (money, bonds) world in which one asset (money) was riskless in his original paper. The basic conclusion of Tobin’s theory of liquidity preference and portfolio choice rested on the properties entitled to these µ-á» curves.
According to Lachmann (1937), in current literature there appeared to be present a reasonable amount of conformity among writers that uncertainty had to be looked upon as the foremost determinant of movements in the size of cash balances, i.e., as the main cause of liquidity preference. At more rapid scrutiny, though, this noticeable agreement came out as to some extent full of twists and turns, because diverse writers gave this word a different meaning. In the following, it was only restricted to the assessment of two examples of monetary theories in both of which the most important role was allocated to uncertainty, and it was found based on the research that in each case the word had a different meaning. After that, the results of the critical assessment of these theories would be used in the best way with the intention to find that meaning of “uncertainty” which would enable the research study to regard it as the cause of liquidity preference. Uncertainty was but one of a lot of grounds of liquidity preference. Possibly the failure of the author to set up a causal association between uncertainty and liquidity preference was due to the author’s having used the word uncertainty in too broad and too indefinite a meaning. The endeavor to ascertain a causal association between uncertainty and liquidity preference had up to now driven out to be an absolute failure.
Wells (1983) had publicized that want for liquidity was an indispensable economic reaction to the not able to be understood and considerably variegated future which always lied to the front. Liquidity was valued in an indecisive world because it afforded economic units the preference of not entirely host aging their own economic future to the uncertain future of the economy. Its ownership provided businesses and households the elasticity to reorganize their economic plans, to redistribute their wealth as the future slowly opens out and becomes the past, as acquaintance was gained with the simple passage of time. In short, this was Keynes’s (1937) theory of liquidity preference. And from just this explanation it can be simply understood why his hypothesis, as it was remade by subsequent generation of writers, turned out to be detached from Keynes’s (1937) unambiguous acknowledgment of the central significance of time and uncertainty, of liquidity and liquidity preference. The disconnection came about largely because the fact that “information of the future was unpredictable, indistinguishable, and doubtful” demonstrated to be a perception far too short lived to support contemporary quantitative model building research. Keynes’s concepts were real, but they were necessarily so unclear and imprecise that model builders could not well integrate these phenomena into analytics.
Kaldor (1939) for instance observed that the stress on liquidity preference as a theory of the demand for money had made an immense contribution to the accomplishment of monetarism. As long as the demand for money could be shown statistically to be less than perfectly elastic and the supply of money to be determined independently enough from the demand, the supply of money was the major determinant of economic activity. This investigation presented here put emphasis that liquidity preference was a theory of the desire to hold short- versus long-term assets and that the state of liquidity preference was presided over primarily by the productivity of business. (Mott, 1985-1986)
According to the Keynes’s liquidity preference theory, the authorities achieved their objectives, which the author understood to be set with respect to the level of the interest rate, against the background of liquidity preference. The interest rate was changed not only by varying the rate at which the central bank was all set to discount (Bank rate), but also by open market operations: sale or purchase of securities between the central bank and the other market members.
According to Reilly and Keith (2005), the theory of Liquidity Preference stated that the higher returns must be given on the long term investments than the shorter ones because some of the yields and returns to invest in the short term investments were given up by the investors in order to avoid the greater price fluctuations of the securities having longer life. Another way to interpret the liquidity preference hypothesis was to say that lenders preferred short term loans, and, to induce them to lend long term, it was necessary to offer higher yields. The liquidity preference theory was also called the Term Premium Theory and it asserted that uncertainty and volatility caused investors to favor short term issues over bonds with longer maturities because short term securities were less volatile and can easily be converted into predictable amounts of cash should unforeseen events occur. This theory argued that the yield curve generally sloped upward and that any other shape should be viewed as a temporary deviation. To see how the liquidity preference theory predicted the future yields and how it compensated with the pure expectations hypothesis, to predict future long term rates from a single set of one year rates: 6 percent, 7.5 percent, and 8.5 percent. The liquidity preference theory suggested that investors added increasing liquidity premiums to the successive rates to derive actual market rates. As an example, investors might arrive at rates of 6.3 percent, 7.9 percent, and 9.0 percent. As a matter of the historical fact, the yield curve showed an upward bias, which implied that, some combination of the liquidity preference theory and expectations theory would more accurately explain the shape of the yield curve than either of these alone. Specifically, actual long term rates consistently tended to be above what was envisioned from the price expectations hypothesis. This tendency implied the existence of a liquidity premium. The liquidity premium was provided to compensate the long term investor.
CHAPTER 3:
RESEARCH METHODS
3.1 Method of Data Collection
Data was collected from Karachi Stock Exchange KSE 100 Index as given by State Bank of Pakistan in publication of Balance Sheet Analysis of Joint Stock Companies Listed on the KSE (2003-2008). The period of study covered six years, 2003-08. The opted sample size of 70 non-financial firms was taken from KSE 100 Index and all of the non-financial firms listed on KSE 100 Index were selected for the samples that were either manufacturing firms or service providing firms excluding the financial firms. The objective behind the exclusion of the financial firms from the sample was that liquidity impact of the financial firms and non-financial firms was entirely different.
3.2 Sample Size
A sample of 70 non-financial firms from KSE 100 Index was taken. Only firms were used in the samples that were only the non-financial firms that included the industrial firms and service providing firms listed on the KSE 100 Index form 2003-2008. The impact of the different financial factors on the liquidity was analyzed on all of the non-financial firms selected as the sample.
3.3 Research Model Developed
There were various financial factors of the non-financial firms which affected the liquidity of the firms. This research study analyzed the impact of different factors on the liquidity. The factors’ relation with the liquidity, measurement formula and relationship with liquidity were discussed below following the discussion after ‘Liquidity’.
3.3.1 Liquidity
According to Horne and David (1968), Liquidity could be expressed as the ability to realize value in an accepted means of exchange. Being the acceptable means of exchange, money was the most liquid asset and is also a benchmark against which the value of other type of monetary assets was compared as to its degree of replacement. In addition, liquidity has two dimensions: the one was the time required to convert the asset into money, and the other was the certainty of the price realized, i.e., the stability of the exchange ratio between the money and the asset. Kim and David and Ann (1998), and John (1993) both measured the liquidity as cash and marketable securities divided by total assets.
3.3.2 Firm Size and Liquidity
Recent research showed that small firms were more likely to face borrowing constraints than large firms (Whited, 1992), and (Fazzari and Petersen, 1993). In addition, Barclay and Jr. (1996) argued that the cost of external financing was smaller for larger firms because of scale economies resulting from a substantial fixed cost component of security issuance costs.
H1: There is impact of firm size on liquidity.
3.3.3 Total Debt Ratio and Liquidity
The firm’s debt ratio was likely to be adversely related to liquid assets. There were at least two reasonable reasons. Baskin (1987) argued that as the firm’s debt ratio increased, the cost of funds used to invest in liquidity increased thereby reducing funded liquidity. Additionally, John (1993) argued that firms with access to debt markets-as proxied by the debt ratio-can use borrowing as a substitute for maintaining a stock of liquid assets. Firms with complete right of entry to liability markets and additional sources of borrowing can also use liability as a alternate for liquidity protection.
H2: There is impact of total debt ratio on liquidity.
3.3.4 Long Term Debt Ratio and Liquidity
Baskin (1987) argued that as the firm’s long term debt ratio increased, the cost of funds used to invest in liquidity increased thereby reducing funded liquidity. Additionally, John (1993) argued that firms with access to debt markets-as proxied by the long term debt ratio-can use borrowing as a substitute for maintaining a stock of liquid assets. Firms with complete right of entry to liability markets and additional sources of borrowing can also use liability as a alternate for liquidity protection.
H3: There is impact of long term debt ratio on liquidity.
3.3.5 Operating Income divided by Total Assets and Sales Ratio and Liquidity
According to John (1993), in the same way, operating incomes presented a organized basis of liquidity. Firms with complete right of entry to liability marketplace and extra sources of loans could also utilize arrears as a replacement for liquidity protection. Therefore, firms that had high quality working proceeds (OI/S or OI/TA) or complete foundation of borrowing could tolerate to have low ranks of liquidity. For this reason, liquidity would be low for firms which have high working proceeds.
H4: There is impact of operating income divided by total assets ratio on liquidity.
H5: There is impact of operating income divided by sales ratio on liquidity.
3.3.6 Inventory and Gross Fixed Assets to Total Assets Ratio and Liquidity
An additional gauge of liquidity expenses of asset reorganization was the “security value” of resources (Shleifer and Vishny, 1992). Titman and Wessels (1988) suggested alternatives for the “security value.” Ratio of inventory and gross fixed assets to total assets (IGP/TA) was certainly connected to security value. The liquidity expenses of asset reorganization were pessimistically linked to “security value.” A firm which had resources of lofty security worth wanted only to keep short ranks of liquidity. Hence, liquidity procedures will be diminishing in IGP/TA.
H6: There is impact of inventory and gross fixed assets to total assets ratio on liquidity.
3.3.7 Market to Book Ratio and Liquidity
Myers and Rajan (1995) argued that risky debt financing might engender sub- optimal investment incentives when a firm’s investment opportunity set included growth options. Managers acting on behalf of equity holders may fail to exercise profitable investment options because debt captured a portion of equity holders’ return in the form of a reduction in the probability of default. The firm can reduce the risk of financial distress and thereby mitigate the incentive to under invest in growth options by maintaining excess liquidity. This view also predicted a positive relation between corporate liquidity and the market-to-book ratio.
H7: There is impact of market to book ratio on liquidity.
3.3.8 Sales and Liquidity
According to John (1993), the variable sale was one of power variables to report for the point of liquidity vindicated by deal and preventive intentions. The variable sales substituted for the deal wants of the firm.
H8: There is impact of sales on liquidity.
The model developed was a linear model and its specifications are provided below:
LIQR = a0 + a1FIRM + a2DEBT + a3LTD + a4SALES + a5OI/S + a6OI/TA+
a7 IGP/TA+ a8Market to Book Ratio + Ñ”
LIQR = sum of cash and marketable securities divided by total assets
FIRM = natural log of the book value of total assets
DEBT = ratio of shorter period plus longer period debt to total assets
LTD = ratio of longer period debt to total assets
SALES = annual sales
OI/S = operating income divided by sales ratio
OI/TA = operating income divided by total assets ratio
IGP/TA = inventory and gross fixed assets to total assets ratio
Є = the error term
3.4 Statistical Technique
Multiple Linear Regression Analysis (MLR) technique was used for this research study to examine the impact of the distinctive financial characteristics of the non-financial firms on their liquidity of the selected firms; Statistical Package for the Social Sciences (SPSS) was used for the examination of the secondary data.
Multiple Regression Analysis technique was used for the purpose of prediction of the decision of the non-financial firms to invest in the liquid assets or not. The selected technique was used to study the impact of the different independent variables (financial factors as listed in the previous chapters) on the dependent variable i.e., liquidity. The multiple regression analysis was selected for this study because the multivariate analysis was more suitable than univariate investigation. In such a way, to openly taking into consideration, the interaction between multiple regressing variables, the study included the derivation of the linear regression function. It showed the intensity of the impact on liquidity during year 2003-2008 based on several independent variables.
CHAPTER 4:
RESULTS
The sample of 70 non-financial firms from the Karachi Stock Exchange KSE 100 Index was taken; Multiple Regression Analysis (MLR) technique was used for this research study. Researcher examined the distinctive financial characteristics of non-financial firms which invest in the more liquid assets. The selected technique was used to study the impact of the different independent variables on the Liquidity.
4.1 Findings and Interpretation of the results
Initially, the regression technique was applied on the data collected using SPSS. It was obvious from the results that there was the existence of strong multicollinearity among the predictors of the liquidity and this implies that there was strong interrelationship present among the independent variables. Hence, the results generated through SPSS were purely biased. In addition, there was the absence of the normality among the variables. Due to non-normality, the results were not providing the true picture of the impact of the different predictors on the study variable. While resolving the problem, it was noticed that the main cause of the multicollinearity among the predictors was due to the two independent variables including firm size and annual sales. Hence, the multicollinearity issue was resolved by taking the original variable of annual sales.
In resolving the issue of normality, various transformations were applied on the variable in order to normalize the variable so that the results could be more reliable; and accurate outlook of the true picture of liquidity can be made. Ultimately, all the issues were successfully resolved which were creating hindrances in the way of accuracy of results. Now, proceeding with the analysis of the results because the data was normal and there was no multicollinearity issue in the data. The interpretation and analysis is presented in the next sections of this research study.
TABLE 4.1 : Model Summary
Models
R
R Sq.
Adj.
R Sq.
1
.744a
.554
.460
Table 4.1 showed the summary regarding the regression model. The Adjusted R square of 46.0% in the above table showed that the all the predictors of liquidity combined together explained 46.0% variation in the dependent variable and the remaining variation was unexplained or latent predictors were not included in the model.
TABLE 4.2 : ANOVA
Models
Sums of Sq.
Df
Means Sq.
F
Sig.
1
Regressions
.216
8
.027
5.896
.000a
Residuals
.174
38
.005
Total
.390
46
The table 4.2 checked the significance of the linear regression model in such a way that the reliability of the data file regarding the applicability of the regression technique can be understood from the above table; however, ANOVA table was reliable test of checking the linear regression model’s ability to explain any variation in the dependent variable of liquidity. This was perfectly obvious from the sig value of .000 that meant that the linear regression model was highly significant for the data collected for the research study conducted.
TABLE 4.3 : Coefficients
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
Collinearity Statistics
B
Std. Error
Beta
Tolerance
VIF
1
(Constant)
0.4
0.173
2.315
0.026
Debt Ratio
0.23
0.467
0.079
0.493
0.625
0.461
2.169
Long-Term Debt Ratio
0.556
0.815
0.107
0.682
0.499
0.478
2.094
Operating Income to Total Assets Ratio
0.338
0.994
0.068
0.34
0.736
0.296
3.374
Operating Income to Total Sales Ratio
0.628
0.398
0.283
1.577
0.123
0.364
2.746
Inventory and gross fixed assets to total assets
-0.758
0.175
-0.597
-4.331
0.000
0.619
1.617
Market to Book ratio
0.001
0.018
0.013
0.083
0.934
0.458
2.184
Sales
0.000
0.000
0.229
1.584
0.122
0.561
1.783
Firm Size
-0.008
0.011
-0.108
-0.762
0.451
0.584
1.712
In the table 4.3, the final model of regression included only one independent variable that was inventory and gross fixed assets to total assets ratio. This was included in the model because this was the only variable that was highly significantly illuminatining the discrepancy in dependent variable of liquidity ratio. In short, these results were not consistent with the results of Kim and David and Ann (1998), and John (1993). The other independent variables were not significant in illuminatining the discrepancy in the dependent variable of liquidity ratio because firstly, the economic and the financial environment was different; secondly, the behavior of the non financial firms was not same as that of the foreign firms in regard of liquidity; and lastly, the decisions of the firms regarding the portion of their investments in liquidity were affected by the political situation and the security threats of Pakistan.
4.2 Hypotheses Assessment Summary
The hypothesis of the study was distinctive financial factors had significant impact on the non-financial firms’ decision to invest in more liquid assets. These financial characteristics were market to book ratio, inventory and gross fixed assets to total assets ratio, operating income divided by sales ratio, firm size, operating income divided by t
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