Cement industry indeed a very important part of industrial sector that plays a essential role in the economic development. Though the cement industry in Pakistan observed its lows and highs in recent past it improved during the last couple of years and floated once again. A basic economic decision deal with a financial intermediary is the mixture of assets to buy and liabilities to sell, a decision that reflects a complex set of economic and institutional considerations. When viewed as a decision under uncertainty, the outcomes from this decision involve interactions among the assets, among the obligations and among assets and obligations. The asset and obligation structures of cement sector of Pakistan necessarily reflect these interactions as well as many regulatory and institutional constraints unique to the cement industry. Multivariate statistical procedures such as canonical correlation analysis are being used more frequently and the methods used in thesis can be applied to other studies. The mixture of assets and liabilities chosen can be viewed as a basic portfolio theory decision. In thesis canonical correlation analysis was applied to examine the relationship between assets and liabilities made by a cross-section of 18 large cement companies of Pakistan listed in stock exchange. Canonical correlation is a multivariate statistical technique that was used to assess the nature and strength of relationship between assets and liabilities. The correlation between each set of assets and each set of liabilities indicates the relationship between assets and liabilities but all of these correlations assess the same hypothesis – that assets influence liabilities. The thesis focused on firms of the Pakistan’s cement industry and the purposes of the thesis was to identify relationships between assets and liabilities exhibited by these corporations and to explain the nature of these relationships. The teaching of corporate finance as reflected in the major textbooks compartmentalizes the decision areas of finance and within each compartment management is assumed to attempt to maximize the firm’s wealth, holding the other areas of the firm constant. For example, capital budgeting decisions are made given a cost of capital or required rate of return (a capital project is evaluated independent of how it is financed), or the capital structure is chosen given the character of the firm’s assets. Cash, receivables, and inventory balances tend to be optimized independently. There is a tradeoff between the rigor afforded by global models of the firm (such as the CAPM) versus the realism afforded by the various approaches used in the compartmented models (e.g., cash management models, equipment replacement models, leasing, etc.). Business practice has the same dilemma; complex organizations must decompose the overall wealth maximization problem into sub problems which, when solved, allow the firm to make satisfactory decisions. Business executives may be uncomfortable with an assumption of independence between investing and financing decisions for two reasons. First, even if the decisions were independent, the decisions may occur simultaneously because of the necessity of raising the funds to invest. Second and more importantly, the assumptions necessary to obtain independence may not be obtained. Several interdependencies might be anticipated between assets and liabilities: Hedging is commonplace, where firms go with maturity structure of their assets and obligations (i.e., short-term assets tend to be financed with short- term obligations and long-term assets tend to be financed with long-term obligations). Some assets are used as collateral for loans. For example, accounts receivable can be used as collateral for short-term bank loans or factor loans and real estate as collateral for mortgages. Commodity-producing firms will maintain inventories which may be financed with credit from suppliers (accounts payable) while service-providing firms may have little of either inventories or accounts payable. High risk businesses may try to manage risk by using less leverage on right hand side of balance sheet (high equity) and by maintaining larger liquidity balances on the left-hand side. This process may enable management to reduce the probability of insolvency It was the objective of the thesis to determine relationships between assets and liabilities on balance sheet exhibited by a sample cement firms of Pakistan. Canonical correlation analysis was used to identify and study the nature of relationship between the structure of the left and right hand sides of the balance sheet. Though canonical correlation analysis is very similar to discriminant and factor analysis, it has not been widely employed in finance. The variables used in this study are, Cash, Account Receivable, Inventories, Long-term Assets, Account Payable, Short-term Debt, long-term Debt and Share Holder Equity.
Stowe,John D,Watson,Collin J & Robertson ,Terry D (1980) observed the relationship between assets and liabilities with the help of canonical correlation analysis. The purpose of research was to identify relations between the two sides of balance sheet (Assets and liabilities) revealed by the corporations and to explain the nature of these relationships. Data from balance sheet for a cross-section of firms was used in the study. For each firm / corporation, a general size (or percentage breakdown) balance sheet was constructed with 4 asset and 4 liability accounts. A big diversity of balance sheet structures was present between 510 firms. A number of remarkable relationships were found in the study i.e. inventories were positively correlated with accounts payable and long-term assets were correlated with long-term debt. On the other hand, stockholder’s equity was not highly correlated with any of the asset proportions. An independence of asset and liability composition of the firm is tilted in much modern financial theory, the independence of investing and financing decision is a prominent part of Modigliani and Miller’s classic capital structure research. Though the distribution of financing and investment decision is an invaluable assumption which greatly makes simpler many business financial decisions, real balance sheets of modern corporations do not exhibit independence between assets and obligations on balance sheet. The aim of the study was (1) to recognize relationships between t assets, obligations and equity on a balance sheet reveal by these firms and (2) to clarify the nature of these relationships. Independence of liability and asset composition is explicit in Modigliani and Miller’s capital structure proposition. In their article, they exhibited that, given a flow of risky earnings; the firm’s total market value and cost of capital are independent of capital structure. The education of corporate finance, as imitated in the major textbooks, compartmentalizes the decision spots of finance and, within each box, management is assumed to effort to maximize the firm’s wealth, holding the other spots of the firm stable. For example, capital budgeting decisions are made given a cost of capital or required rate of return (a capital project is evaluated independent of how it is financed), or the capital structure is chosen given the character of the firm’s assets. Cash, receivables, and inventory balances tend to be optimized independently. There is a tradeoff between the rigors afforded by global models of the firm (such as the CAPM) versus the realism afforded by the various approaches used in the compartmented models (e.g., cash management models, equipment replacement models, leasing, etc.). Business practice has the same dilemma; complex organizations must decompose the overall wealth maximization problem into sub problems which, when solved, allow the firm to make satisfactory decisions. Business executives may be uncomfortable with an assumption of independence between investing and financing decisions for two reasons. First, even if the decisions were independent, the decisions may occur simultaneously because of the necessity of raising the funds to invest. Second and more importantly, the assumptions necessary to obtain independence may not be obtained. Several interdependencies might be anticipated between the assets and liabilities, those are, (1) Hedging is commonplace, where firms go with maturity structure of their assets and obligations (i.e., short term assets tend to be financed with short term obligations and long-term assets tend to be financed with long-term obligations), (2) some assets are used as collateral for loans. For example, accounts receivable can be used as collateral for short-term bank loans or factor loans and real estate as collateral for mortgages, (3) commodity-producing firms will maintain inventories which may be financed with credit from suppliers (accounts payable) while service providing firms may have little of either inventories or accounts payable and (4) high risk businesses may try to manage risk by using less leverage on right hand side of balance sheet (high equity) and by maintaining larger liquidity balances on the left hand side. This process may enable management to reduce the probability of insolvency. It was the intent of the study to determine relationship between assets and liabilities on balance sheet are exhibited by a sample of large corporations. Canonical correlation analysis was used to identify and examine the nature of relationships between the structures of the left- and right-hand sides of the balance sheet. While canonical correlation analysis is very similar to discriminate and factor analysis, it has not been widely employed in finance. There were two general conclusions of study. The first basic purpose of study was satisfied that there are basic relationships between assets and obligations on a balance sheet which were identified with canonical correlation analysis. The assumptions behind much of modern financial theory allow us to separate investing and financing decisions. Relaxation of these assumptions can admit interdependencies between assets and obligations and several interdependencies were found in our empirical study. These relationships across the balance sheet include (1) hedging, (2) the use of collateral for loans, (3) inventories associated with accounts payable, and (4) manage risk with instantaneous use of inferior leverage and larger liquidity balances. The capital structure research since M and M’s original irrelevance argument has attempted to utilize the effect of the current value of interest tax shelter due to debt financing and the effect of expected bankruptcy costs on the firm’s optimal capital structure. The interdependencies between assets and liabilities found in this empirical study could be incorporated into models of capital structure. The second general conclusion was to recommend canonical correlation analysis of financial statement data for other research topics. Much of the published empirical research concerning financial statements is on topics with a single, well defined dependent variable; these topics would include predicting bankruptcy, bond ratings, or loan defaults and explaining market risk measures. Canonical analysis, where there is a set of dependent variables, would allow empirical analysis to proceed where no unique variable can be chosen as the dependent variable. Furthermore, variables which are linear combinations of financial statement proportions might be employed instead of the usual financial ratios.7 Canonical variate scores for a firm could be associated with its bond ratings, probability of default, or systematic risk. These topics usually have been investigated using financial ratios as predictor variables Stowe,John D & Watson,Collin J(1985) did the multivariate analysis on balance sheet composition of life insurer. The purpose of that analysis was to study the empirical relationships between the assets and obligations structure of the life insurer. The assets and liabilities mixture that chosen by life insurer can be viewed in terms of basic portfolio theory decisions. Canonical correlation analysis was used by the researcher to study or examine the internal structure of these portfolio decisions that was made by a cross section of large life insurers. The financial intermediaries study, such as life insurers, is distinguished from that of nonfinancial businesses for several causes. First, the financial intermediaries assets consists just about entirely of financial assets as opposed to the real assets that bulk large on the balance sheets of nonfinancial businesses. As suggested by Moore B. J (1968) in his article an introduction to the theory of finance that the financial assets differ from tangible assets; the financial assets are intangible and they are held for the income they generate as opposed to the direct physical services they yield; financial assets are more liquid and finally financial assets can be more freely converted from one form to another while real assets are indurate. A second difference between intermediaries and nonfinancial businesses involves the nature of their obligations. Financial intermediaries accumulate loan able funds through issuing a variety of claims. For example, the commercial bank’s and life insurer’s claims are quite different from the obligations issued by nonfinancial corporations. A final significant difference between financial intermediaries and other businesses is that the intermediaries normally are more seriously regulated and sometimes are subject to separate taxation from other firms and individuals. Like other intermediaries life insurers have been the subjects of a range of empirical research projects. J. D (1973) Cummins in his article “An econometric model of the life insurance sector” of the U.S economy and J. E Pesando, in his article “The interest sensitivity of the Flow of funds through life insurance companies” presented an econometric analysis for the comprehensive flow of funds through the life insurance sector. J.D Stowe (1978) in his article examines the investments of individual life insurers in a cross-sectional, time-series study. The basic operational hypothesis for the study on balance sheet composition of life insurer was that a number of categories of assets on the left hand side of life insurer balance sheets had more than one pattern of correlations when they are associated with several liability and surplus classes from right hand side of balance sheet. In addition to testing this hypothesis, the natures of the relationships between assets and obligations were examined and the strength of the multivariate relationship was anticipated. The structure of life insurer assets was explained as a function of the structure of the other side of the balance sheet and of some additional firm specific variables. In this study it was necessary to predict several criterion variables simultaneously by means of a second set of predictor variables. Under these circumstances, no single regression equation can presented a fully adequate solution. Any linear combination of the criteria may be used as the dependent variable in a regression equation, and in general not one but a number of regression equations must be used to give an appropriate picture. The problem of finding linear combinations of the criterion variables that can be most accurately predicted from the predictor variables was solved by H. Hotelling in his article “The most predictable criterion” commonly known as canonical correlation analysis. G. Donald Simonson, D. J Stow, and J. Collin Watson (1983) analyzed a canonical correlation analysis between assets and liabilities structure of commercial banks in. They analyze the balance sheets of all 435 domestic U.S banks with assets in excess of $300 million at year end 1979. Data was taken from the December 31, 1979 Foreign and domestic Report of Condition files prepared on magnetic tape by the three federal bank supervisory agencies. They limited the analysis to large banks for two reasons. First, smaller banks do not have the talent or market position to aggressively practice liabilities management and therefore their balance sheets are not as likely to reflect differentiated policies relative to bearing interest rate risk. Second, the three federal agencies require only banks with assets over $300 million to report maturities of both de posits and selected loans, as well as a breakdown of loans in to those with predetermined versus floating interest rates. These large bank data permit us to construct several key balance sheet accounts on the basis of interest sensitivity. Six asset and six liability/capital categories were expressed as a proportion of total assets for each of the 435 banks in the study. The purpose of a study was to identify and describe the relationship including heading behavior of a single dependent variable as a function of a set of independent variables, canonical correlation analysis relates two sets of variables. In the present case one set of variables is the composition of the left hand side of the balance sheet and the other set is the right hand side. The variables used in this study are asset and liability/ capital categories expressed as proportion of total bank assets. These portions were used in lieu of the more usual financial ratios and no information exogenous to the bank was employed. During the past two years bankers and bank analysts have been concerned about how interest rate risk is derived from cross balance sheet relationships. The mismatching of maturities or interest sensitivities whether interest sensitive assets financed with long term liabilities or long term assets financed with interest sensitive liabilities creates interest rate risk. For example high interest rates and a downward sloping yield curve, one whose short term rates exceed long term rates for borrowers of similar creditworthiness, especially expose institutions which pursue the traditional financial intermediation formula of borrow short lend long. In commercial banking, the exposure is greatest for banks which finance fixed rate term loans and long term fixed income securities with short term funds at money market rates. Banks can defend themselves against this exposure by practicing asset/liability management; by coordinating their procurement of funds and acquisition of assets. There was early theoretical appreciation of the necessity for management of the maturities of asset and liability portfolios. In a simple three variable model D.H Pyle (1971) in his article “theory of financial intermediation” shows that assuming banks maximize the expected utility of terminal wealth, banks’ choices of assets (liability) portfolio will be conditioned upon the parameters, including maturity, of their liability (assets) portfolios (given nonzero covariance of liability and assets yields). According to the applied asset/liability management dictum, banks with volatile short term interest sensitive source of funds should attempt to structure their asset portfolios to emphasize short term and floating rate movements and in general maturities of asset and liability portfolios should be matched. Such banks can be said to adopt defensive loan portfolios. Other banks by their nature are less dependent on short term market rate funds and are in a better position to offer fixed rate loan terms to borrowers their customers provide a relatively large core of stable savings and time deposits with average interest costs well below current market rates. As result these banks have to be free to acquire long term assets at predetermined interest rates that are they can adopt aggressive loan portfolios. HO, T.S.Y in his article (1980) “The determinants of bank interest margin” showed that balance sheet hedging is a rational response to interest margin uncertainty which results from the interplay between volatile interest rates and asset and liability structural interrelationships. Their research attempts to find evidence of such asset/ liability hedging practices among U.S banks during a period of high and volatile interest rates and a downward sloping yield curve. If banks in aggregate tend to hedge interest sensitive funds with core funds, the banking industry would appear to be coping appropriately with interest rate risk. On the other hand, if there is a systematic tendency for many banks to combine fixed rate long term assets with volatile short term funds, the industry might be excessively exposed to interest rate risk. The issue of capital adequacy also concerned with the comparative maturity structure and duration of the two sides of the balance sheet. S.T. Maisel and R. Jacobson in his article Interest rate changes and commercial banks revenues and costs they showed that over the period 1962 to 1975 for the average bank, the threat of insolvency due to the instability of economic returns stemmed primarily from the mismatch of asset and liability durations. They concluded that unheeded interest rate risk might require additional equity capital. Other sources of risk, such as default risk, would dictate a positive relationship between the amount invested in riskier loans and securities and the amount of equity capital. Research was limited because data on the market values of asset and liability items are not available. Presumably, potential changes in cross balance sheet market values are transmitted to changes in the market value of the firm. There was a considerable literature addressing asset-liability management in banks. One of the key motivators of asset-liability management worldwide was the Basel group. The Basel group Banking Supervision (2001) formulated broad supervisory standards and guidelines and recommended statements of best practice in banking supervision. The purpose of the committee was to encourage global convergence toward common approaches and standards. In particular, the Basel II norms (2004) were proposed as an international standard for the amount of capital that banks require setting to the side to protect against the types financial and operational risks they face. Basel II proposed setting up accurate risk and capital management necessities designed to make sure that a bank holds capital reserves suitable to the risk banks picture their self to throughout its lending and investment practice. In general, these regulations mean that the larger risk to which the bank is showing, the larger the amount of capital the bank requires to hold to defend its solvency and whole economic strength. This would ultimately help to defend the international monetary system from the kind of problems that may take place should a major bank or a sequence of banks collapse. Gardner and Mills (1991) discussed the principles of asset-liability management as a part of banks’ strategic planning and as a response to the changing environment in prudential direction, e-commerce and new taxation treaties. Their text provided the foundation of subsequent discussion on asset-liability management. Haslem (1999) used canonical analysis and the interpretive structure of asset/liability management to identify and interpret the foreign and domestic balance sheet approach of large U.S. banks. Their study found that the least money-making very large banks have the biggest size of foreign loans, yet they give emphasis to domestic balance sheet (asset/liability) matching strategies. on the other hand, the most money-making very large banks have the smallest size of foreign loans, but, however, they emphasize foreign balance sheet matching strategies. Vaidyanathan (1999) discussed issues in asset-liability management and elaborates on various categories of risk that require to be managed in the Indian context. In the past Indian banks were primarily concerned about adhering to statutory liquidity ratio norms but in the changed situation, namely moving away from administered interest rate structure to market determined rates, it became important for banks to equip themselves with some of these techniques, in order to immunize them selves against interest rate risk. Vaidyanathan argued that the problem gets accentuated in the context of change in the main liability structure of the banks, namely the maturity period for term deposits. For instance, in 1986, nearly 50% of term deposits had a maturity period of more than five years and only 20%, less than two years for all commercial banks, while in 1992, only 17% of term deposits were more than five years whereas 38% were less than two years Vaidyanath. It was found that several banks had inadequate and inefficient management systems. Also argued that Indian banks were more exposed to international markets, especially with respect to forex transactions, so that asset liability management was essential, as it would enable the bank to maintain its exposure to foreign currency fluctuations given the level of risk it can handle. It was also found that an increasing proportion of investments by banks were being recorded on a market to market basis, thus being exposed to market risks. Is was also suggested that, as bank profitability focus has increased over the years, there is an increasing possibility that the risk arising out of exposure to interest rate volatility would be built into the capital adequacy norms specified by the regulatory authorities, thus in turn requiring efficient asset-liability management practices. Vaidya and Shahi (2001) studied asset-liability management in Indian banks. They suggested in particular that interest rate risk and liquidity risk are two key inputs in business planning process of banks. Using firm-level data, an extensive accounting literature focuses on the contemporaneous correlation of stock returns and earnings. Despite the statistically reliable positive association between stock returns and earnings, Ball and Brown (1968), Beaver, Clarke, and Wright (1979), Beaver, Lambert, and Morse (1980), Easton and Harris (1991), Collins, Kothari, Shanken, and Sloan (1994), and others find that the explained fraction of stock return variation was significantly less than one (typically under 10 percent). Lev (1989) and others suggest that the relatively low explanatory power stems from earnings’ lack of timeliness and/or value-irrelevant noise in earnings. The idea that correlation between a cash-flow proxy and stock return may be due to any of the three components was not novel. Fama (1990), Schwert (1990), Kothari and Shanken (1992), Campbell and Ammer (1993), and others recognize that when stock returns are regressed on cash flow proxies, any of the three effects may be driving the regression coefficients. They do not, however, clearly quantify the relative importance of these three effects. Thus, in the end, it is still unclear why cash-flow proxies are or are not related to stock returns. The fundamental subject of working capital is to provide optimal balance between each element forming working capital. Most of the efforts of finance directors in a firm are the efforts they make to carry the balance between current assets not at optimal level and responsibilities to an optimal level Lamberson (1995). One reason for this was the decisive influence of current assets on others, another reasons was liabilities of completion of present responsibilities. The combination of the elements forming working capital are change over time. Need for working capital manipulate liquidity stage and profitability of a company. As a result, it affects investment and financing decisions, too. Amount of current assets to be calculated at a level where total cost is of a least degree means an optimal working capital level. The optimal working capital point is case wherein balance between risk and effectiveness is provided.. The entire current assets hold by a firm known as working capital. Net working capital is calculated when short term obligations are took out from current assets. Return of total assets of a firm as a result of an activity is closely related to level and distribution of assets of the firm and efficiency in application of these assets. In lots of firms current assets called working capital make up of a remarkable part of community assets. (Note 1) But it is clear that working capital is ignored in finance journalism compare to long term financing decision. Corporate finance studies usually concentrate on core decisions like, dividend, capital structure and capital budgeting. Though, the sum of assets group is a important part of entire asset and called working capital (inventories, quasi money and money. short term liabilities and trade receivables) is a focus matter in all main books relating to corporate finance where efficiency level of distribution and application of assets influence profitability and risk level of the company. The major purpose of a company is to increase the market worth. Working capital management influence profitability of the company, its risk and thus its value Smith, (1980). Further, effective management of working capital is a key component of the broad strategy aim to increase the market rate (Westhead and Howorth (2003). Since the flexibility of this group of assets is very high in terms of adapting to changing conditions and due to these uniqueness they can frequently be applied to understand the major aim of financial management through policy changes. Success of a firm mainly depends on efficient management capability of finance director to manage receivables, inventories and liabilities (Filbeck and Krueger, 2005). Firms can strengthen their funding capabilities or decrease the source cost reducing source amount they allocate to current assets. In finance literature there is a common opinion about the importance of working capital management. Explanations about why effective capital management is important for a company usually concentrate on the association between effectiveness in working capital management and company profitability. Effective working capital management includes controlling and planning of present assets and liabilities in such a way it avoid extreme investments in current assets and prevents from working with few currents assets insufficient to fulfill the responsibilities. In relevant studies the measure taken as an indicator of efficiency in working capital management is generally cash conversion cycle. For firm cash conversion cycle is the period during which it is transited from money to good and again to money. In the studies conducted by Shin and Soenen (1998), Deloof (2003), Raheman and Nasr (2007) and Teruel and Solano (2007) it was concluded that there is a negative relationship between profitability of a firm and cash conversion cycle. Thus, it is possible to increase firm profitability through more effective working capital management. It is necessary to realize that major basics of cash conversion cycle (short term account receivables, short term trade liabilities and inventories) should be managed in a way they maximize firm profitability. An efficient working capital management will increase free cash flows to the firm and growth opportunities and returns of stockholders. Working capital level of a firm indicates that it wants to take a risk. The more working capital amounts, the liquidity risk and profitability become lower. The working capital strategies of firms differ according to the segments and within each segment it varies over time Filbeck and Krueger (2005). Ganesan (2007), put forward that the firms in less competitive sectors focus on cash conversion minimizing receivables, while the firms in more competitive sectors have a relatively higher level of receivables. Lazaridis and Tryfonidis (2005) stated that small firms focus on inventory management, the firms with low profitability on credit management. Statements in literature of finance about the significance of working capital for companies are being once further emphasized in these unstable days of international economy. While firms make efforts to increase return on assets in a way they pay their due obligations as late as possible and keep the cash, decreases in activity volume decreases the cash flow, too and this case increases the liquidity risk (Hofler, 2009). All these raise the importance of working capital. In the following part our study the practice section where the association between efficiency level of companies being operated in ISE in working capital management and their gain on total asset is handled. Classical risk theory mostly focuses on the liabilities of insurance companies and therefore on the study of claims, including their frequency and their amount. As explained in e.g. Parker (1997), the insurance companies do not only have to deal with insurance risk but also with investment risk like liquidity risk, risk of change and most importantly the interest rate risk. The insurance risk, due to the risk insured (e.g. mortality, fire, car accidents), can be decreased as the number of policies in the portfolio increases (however, a perfect and complete pooling will never occur). The investment risk does not decrease with an increasing number of policies since the rates of return are highly correlated. Interest rates both influence the active and the passive side of the balance and become very important when the insurance policies are long-term contracts. It is therefore essential to devise asset liability models appropriate to insurance companies. In thesis, concentration was made on the mismatching of assets and liabilities, namely the times that the value of the assets becomes lower than the value of the liabilities. Focusing on ALM for banks, Janssen (1992) modeled both the assets and the liabilities by geometric Brownian motions. Study was on an extension of the Janssen model in which the asset fund A takes into account fixed-income securities and this introduces asymmetry for A and B. That is particularly useful for insurance companies whose investments are more in bonds than in shares. It was assumed that the liability course of action is defined by a geometric Brownian motion with drift, which is correlated with the asset process in a constant way. In this generalized un- segmented Janssen model, study was on the perfect matching and final matching of assets and liabilities by determining the probability of mismatching and the degree of mismatching. In case of perfect matching, the study will be on the influence of the parameters of the asset and liability processes on the probability of no perfect matching in order to obtain general implications of the model to the company asset liability management and the difference between the models seems with a Cox-Ingersoll-Ross process and an Ornstein- Uhlenbeck process. Study further focus on a multidimensional model in which it was assumed that the assets and liabilities are segmented in respectively m and n pools, for example into different investments and into different insurance contracts. First concentration was on the case that the assets contain only shares. Afterwards, distinct shares and fixed-income securities which mainly differ since shares can be modeled by a geometric Brownian motion, but the interest-rate derivatives cannot. Since these financial instruments depend on the yield curve, was assumed a stochastic interest rate process. Soocheong (Shawn) Jang (2005) used canonical correlation analysis. The study examined interdependencies in investing and financing decisions of restaurant firms. The results indicated that the similar four cross-balance sheet interdependencies exist in the restaurant industry as identified by previous studies for different industries and companies in various countries: (1) maturity matching structure of assets and liabilities, (2) use of long-term assets as collateral for long-term debt, (3) use of accounts payable to finance operational assets (e.g., inventories and other current assets), and (4) concurrent use of cash and stockholders’ equity to manage risk. Additionally, this study discovered the unique financing features of the restaurant industry: (1) restaurant firms did not relate account receivables to short-term liabilities, and (2) they financed their operational assets with stockholders’ equity in addition to account payable. The findings are expected to contribute to the understanding of restaurant financing behavior as related to assets structures. This study also demonstrated the usefulness of canonical correlation analysis in extracting information related to financial management strategy.
The chapter forms the core of the research work. This chapter provides the detail information regarding hypothesis development, empirical model, characteristic of variables, statistical test, the source of data or the data collection technique & sample size,. It also highlights the tools that have used in the study. The statistical tools also mentioned to give clear idea about the data collected and its treatment.
H1: There is significant and positive relationship between Account Receivables and Account Payables H2: There is significant and positive relationship between Cash and Account Receivables. H3: There is significant and positive relationship between Inventories and Account Payables H4: There is significant and positive relationship among Long Term Assets and Long Term Liabilities H5: There is significant and positive relationship between Inventories and Current Debt
Consequently canonical correlation analysis was used to investigate the type of interaction between assets and liabilities on the balance sheet. The variables of the asset side are denoted Xi1,, Xi2, Xi3, and Xi4 and the variables of the equity/liability side are Yi1, Yi2, Yi3, and Yi4. The scores of an observation, i, for each canonical variate pair, as i increase from 1 to n can be expressed as: u1= a1X11 + a2X12 + a3X13 + a4X14
un= a1Xn1 + a2Xn2 + a3Xn3 + a4Xn4, and v1= b1Y11 + b2Y12 + b3Y13 + b4Y14
vn= b1Yn1 + b2Yn2 + b3Yn3 + b4Yn4 The a’s and b’s are the canonical weights. A canonical correlation is obtained for each of the canonical variate pairs by correlating u and v across observations. The nature of the canonical variates, derived to have maximum correlations, can be examined by utilizing canonical loadings. The nature of the structure of the canonical loadings may be simplified using the canonical rotation analysis methods described by Cliff and Krus (1976) and also by Perreault and Spiro (1978). The canonical loadings for both sets of variables can be rotated simultaneously using Kaiser’s normalized varimax criterion (1958). The total predictable variance remains the same and the rotated canonical correlations will be allocated more evenly across the canonical variates using these methods. More importantly, the examination of the nature of the canonical variates generally will be simplified.
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