Copernican Journal of Finance & Accounting 2016, volume 5, issue 2 e-ISSN 2300-3065 p-ISSN 2300-1240 Baser, F., Gokten, S., Kucukkocaoglu, G. & Ture, H. (2016). Liquidity-profitability tradeoff existence in Turkey: an empirical investigation under structural equation modeling. Copernican Journal of Finance & Accounting, 5(2), 27–44. http://dx.doi.org/10.12775/CJFA.2016.013 Furkan Baser* Ankara University, Turkey Soner Gokten** Baskent University, Turkey Guray Kucukkocaoglu*** Baskent University, Turkey Hasan Ture**** Gazi University, Turkey liquidity-profitability tradeoff existence in turkey: an empirical investigation under structural equation modeling Keywords: liquidity-profitability tradeoff, structural equation modeling, working capital management. J E L Classification: G30, M10. Date of submission: January 24, 2017; date of acceptance: January 30, 2017. Contact information: [email protected], Department of Insurance and Actuarial Sciences, Ankara University, Ankara, Turkey. ** Contact information: correspondent author, [email protected], Department of Management, Baskent University, Baskent Universitesi, Baglica Kampusu Eskisehir Yolu 20. km, IIBF, Isletme Bolumu, 06810, Ankara, Turkey, phone: +9 (0312) 246 66 66 - (1113). *** Contact information: [email protected], Department of Management, Baskent University, Ankara, Turkey. **** Contact information: [email protected], Department of Econometrics, Gazi University, Ankara, Turkey. * 28 Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture Abstract: Firms in emerging markets could show a tendency to have high liquidity positions by ignoring the liquidity-profitability tradeoff in terms of working capital management due to gained experiences from stressed times. Accordingly, this study empirically examines the validity of liquidity-profitability tradeoff in Turkish market via structural equation modeling. The functions of liquidity and profitability as latent variables of the model are constituted from Piotroski’s criterias of liquidity/solvency, operating efficiency and profitability. The hypothesized model for the inexistence of the validity of liquidity-profitability tradeoff was verified and there is a moderate level of positive effect between liquidity and profitability in Turkey. The findings indicate that (1) current ratio or its variants as single-handed variables are inadequate to explain liquidity-profitability relation and (2) leverage seems to be the most important indicator as taken into account on working capital management decisions. Turkish firms apply prudent working capital management to overcome possible liquidity shocks. Introduction Liquidity and profitability tradeoff is a crucial issue discussed in the literature under the management of current assets and current liabilities to obtain optimum profitability. Thus, efficient liquidity management involves planning and controlling current assets and current liabilities to eliminate the risk of insolvency by not meeting the short-term obligations on time. Besides, liquidity is one of the most important control variable that accounts for firm profitability as well (Iatridis & Kadorinis, 2009). Solely, in the frame of working capital approach, cash management is a nonnegligible concept which directly affects the profitability of a firm especially in short term (Schneider, 1988; Johnson & Aggarwal, 1988; Unsworth, 2000; Raspanti, 2000). In this regard, working capital management is considered as a useful tool in managing of funds to meet current operations. However, instead of using working capital as a measure of liquidity, accounting literature advocate the use of current and quick ratios to make temporal or cross sectional comparisons. Nevertheless, the ultimate measure of the efficiency of liquidity planning and control is the effect it has on profit (Eljelly, 2004). According to Sanger (2001), working capital represents a safety cushion for providers of short-term funds of the company, and as such they view the availability of excessive levels of working capital and cash in a positive way. However, from an operating point of view, working capital has increasingly been looked at as a restraint on financial performance, as these assets do not contribute to profit. Argued vividly by Nicholas (1991), companies usually do not think about improving liquidity management before reaching to a crisis conditions or becoming on the verge of bankruptcy. Thus, any increase in cash or cash-similar liquidity- profitability tradeoff existence in turkey… 29 positions creates a tradeoff on profitability by lying behind passive funds to generate profit. In this sense, liquidity ratios as a measure of company’s ability to pay debt obligations and its margin of safety play an important role on evaluating the financial decisions of tradeoff between liquidity and profitability (Gitman, 1974; Richard & Laughlin, 1980; Hawawini et al., 1986; Kamath, 1989; Gentry et al., 1990; Boer, 1999; Eljelly, 2004). Liquidity ratios mostly represent the summarized indirect results of financial decisions related with the financial structure. From this point of view, as the market conditions restrict the capabilities of decision makers in terms of working capital management, they could not have the opportunity to determine the level of current assets according to liquidity-profitability tradeoff mechanism. The reality is that liquidity management focuses on profitability in good times but in troubled times systematic risk put pressure on profitability and firms need sufficient liquidity positions to survive (Summers & Wilson, 2000). In this sense, liquidity-profitability tradeoff issues may long be ignored on the formation of financial structure. That means liquidity-profitability tradeoff concept in financial management decisions could not be valid in some markets, especially for emerging ones, as prudent behaviors come from the past. This study concentrates on testing the existence of the validity of liquidityprofitability tradeoff in Turkish market, which has many financial experiences on troubled times under liquidity shocks. To get a clear picture, we first need to go back to 1980s where Turkey has first started to adopt the rules of free market economy, free competition, and a liberalized foreign trade practices by applying neo-liberal policies to integrate into international markets. Throughout the years Turkey has faced with several financial crises because of unsteady economic and political environment forces and became dependent to IMF and its policies with standby agreements. Structural reforms applied as part of standby agreements showed positive effects on Turkish economy especially after 2002. Inflation and interest rates have fallen significantly and the currency stabilization program has been achieved. Growth rate in 2004 was realized as 9.9 percent and interestingly, high growth rates were accompanied by a reduction in inflation rates which were reduced to single-digit figures in 2004 after almost 30 years. In addition, a global financial shock of 2007, as an external factor, affected Turkey like all other countries. Right after the spread of US based financial crisis to all over the world, central banks started to install monetary policies to cultivate recovery and funds started to move to the emerging markets to ob- 30 Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture tain satisfactory returns based on an increase in global money supply. Turkish market appeals foreign investment with nearly 70 billion USD capital inflows per year between 2002 through 2013. By paying the last loan repayment in the amount of 422.1 million $ (the total amount of payment was 23.5 billion $ during 2002–2013) in 2013, Turkey initialized its position against IMF. Also, in year 2013, Turkey ranked as the sixth biggest economy in Europe and the sixteenth in the world. With regards to this historical background, we expect that Turkish firms could show a tendency to have high liquidity positions by ignoring the liquidity-profitability tradeoff in terms of working capital management. As they have become more prone to financial crises and learned from the past experiences, this paper selected year 2014 to test this alleging remarks as this year represent a boom phase in the Turkish economy. As the acceptance of general rules or conclusions are challenging in financial researches and they are based on a lot factors that are not directly observable (Titman & Wessels, 1988; Harris & Raviv, 1991), expecting the invalidity of the negative relationship between liquidity and profitability cannot come as a surprise when the conditions of emerging markets are compared with emerged ones. Financial structure decision-making is even more complicated when it is examined in developing countries where markets are characterized by controls and institutional constraints (Boateng, 2004). Therefore, most studies in the literature analyzing the financial structure topic in developed markets depict many institutional similarities and could be accepted as efficient. Accordingly, relevant studies for emerging markets depict many institutional differences as well (Schulman et al., 1996; Wiwattanakantang, 1999; Chen, 2004). Under these conditions, as an emerging market economy, it is not contrary to expect positive relation between liquidity and profitability for Turkish firms. From this point of view, this paper tests the validity of liquidity-profitability tradeoff for firms in Turkish market by applying Structural Equation Modeling (SEM). In this sense, the functions of liquidity and profitability are constituted by using Piotroski (2000) criterions1 and then SEM is applied. 1 Current ratio (CR), gross margin (MARGIN), leverage (LEV) and asset turnover (TURN) which are the criterions of liquidity/solvency and operating efficiency, are used as the determinants of liquidity function. Return on assets (ROA), cash flow from operations (CFO) and accruals (AC) which are the criterions of profitability, are used as the determinants of profitability function. Sample includes 187Istanbul). active firms listed and tradedthe on National Market of Istanbul S Exchange Exchange (BIST-Borsa (BIST-Borsa Istanbul). National National Market Market is is the largest largest market market of of BIST, BIST, where where Exchange (BIST-Borsa Istanbul). National Market is the largest market of BIST, where Exchange (BIST-Borsa Istanbul). the National Market is the largest market of BIST, where equities equities of of companies companies that that satisfy satisfy the listing listing requirements requirements (an (an average average market market capitaliza capitaliza equities of companies that satisfy the listing requirements (an average market capitaliza equities of companies that satisfy theoflisting requirements (an average market capitaliza of of at at least least 12 12 million million Turkish Turkish Liras Liras of its its free-float free-float for for the the relevant relevant period period and, and, aa free free ff of at least 12 million Turkish Liras of its free-float for the relevant period and, a free rate liquidity - profitability tradeoff existence in turkey … 31 and, ainclude of at least 12 million Turkish Liras of its free-float for the relevant period free ff rate of of at at least least %25) %25) of of National National Market Market are are traded. traded. Selected Selected sample sample does does not not include rate least of Market are Selected sample does not rate of of at at least %25) %25) of National National Market with are traded. traded. Selected sample does not include includn nancial service firms and the companies lack of data. 2014 annual accounting nancial service firms and the companies with lack of data. 2014 annual accounting n The structure of the paper is as follows. In the next section, the dataset and nancial service firms and the companies with lack of data. 2014 annual accounting nu nancial service firms and the companies with lack of data. 2014 annual accounting n bers to the determinants each firm annual functions areused described and the SEM is given in detailed. Then, statement bers are are used to calculate calculate themethodology determinantsoffor for each firm and and annual financial financial statement bers are used to the determinants for annual results discussed bersare aregiven usedand to calculate calculate therespectively. determinants for each each firm firm and andBIST annual financial financial statement statemen these these years years are are obtained obtained from from Public Public Disclosure Disclosure Platform Platform of of BIST (KAP). (KAP). these years are obtained from Public Disclosure Platform of BIST (KAP). these years are obtained from Public Disclosure Platform of BIST (KAP). Research methodology Functions Functions with with Determinants Determinants Functions with Functions with Determinants Determinantsliquidity and profitability is investigated via using latent v The The relationship relationship between between liquidity and profitability is investigated via using latent v Data and profitability is investigated via using latent v The relationship between liquidity The relationship between liquidity profitability is refer investigated via usingoflatent v ables. means functions of and profitability Sample includes 187 active firms listedand and on National Marketvariables of Istanbul Stock ables. That That means functions of liquidity liquidity andtraded profitability refer latent latent variables of struct struct ables. That means functions liquidity and latent variables of Sample includes 187 active firmsof listed and traded on Nationalrefer Market of Istanables. That means functions liquidity and profitability profitability refer latent variables ofinstruct struct equation modeling respectively. Determinants of functions are described Exchange (BIST-Borsa Istanbul).ofNational Market is these the largest market of BIST, where the equation modeling respectively. Determinants of these functions are described in deta deta bul equation Stock Exchange (BIST-Borsa Istanbul). National Market is the largest marmodeling respectively. Determinants of these functions are described in detai equation modeling respectively. Determinants of thesethe functions are described in deta this part of equities of companies satisfy listing requirements average market capitalization ket of BIST, where the that equities of the companies that satisfy (an listing requirethis part of the the paper. paper. this part of the paper. 2 3 4 5 partaverage the paper. ments (an market capitalization of at least 12 the million Turkish Liras 3, LEV 4 period and TURN Liquidity is as function CR of atthis least 12ofmillion Turkish Liras of its of free-float for relevant and,5aby free floa MARGIN Liquidity is defined defined as the the function of CR22,, MARGIN 3 , LEV4 and TURN5 by 2, MARGIN 3, of 4 and %25) 5 by LEV TURN Liquidity is defined as the function of CR of its free-float for the relevant period and, a free float rate at least Liquidity is defined as the function of CR ,� ). MARGIN , LEV anddoes TURN by (1) fi �(CR TURN rate ofLiquidity at least %25) of National Market traded. Selected sample not include �� = �� MARGIN �� ,, LEV �� ,,are (1) Liquidity =are �(CR MARGIN LEV TURN � ). not include financial serof National Market traded. Selected sample does Liquidity (1) �(CR � = � MARGIN � ,,LEV � ,,TURN � ). ). Liquidity = �(CR MARGIN LEV TURN (1) � � � � � Total amount of the current assets is the fundamental accounting measurement fo nancial service firms companies ofannual data. 2014 annualnumaccounting num vice firms and the companies with lack of with data. 2014 accounting Total amount ofand thethe current assets is thelack fundamental accounting measurement fo Total amount of the current assets is the fundamental accounting measurement fo Total amount of the current assets is the fundamental accounting measurement fo bers are to the determinants for each each firm and annual annual financial position of financial structure. In sense, Current Ratio is bersquidity are used used to calculate calculate determinants for firm and statements o quidity position of the thethe financial structure. In this this sense, Currentfinancial Ratio (CR) (CR) is gener gener quidity position of the financial structure. In this sense, Current Ratio (CR) is gener statements of these years are obtained from Public Disclosure Platform of BIST quidity of theindicator financial structure. Inassessment this sense, Current Ratio (CR) is gener accepted as the liquidity in frame these years position are Publicfor Disclosure of BIST (KAP). accepted as obtained the main mainfrom indicator for liquidityPlatform assessment in the the frame of of working working cap cap (KAP). accepted main indicator for assessment in of working cap accepted as as the the main indicator for liquidity liquidity assessment in the the frame frame ofother working ca management: As is known, increase in CR means more liquidity. On the hand, management: As is known, increase in CR means more liquidity. On the other hand, C C management: As is known, increase in CR means more liquidity. On the other hand, CR management: As is known, increase in CR means more liquidity. On the other hand, C the indicator Functions with Determinants the summarized summarized indicator of of the the financial financial decisions decisions which which derive derive from from other other indicators indicators Functions with Determinants the indicator of financial decisions which derive from other indicators the summarized summarized indicator of the the financial decisions which derive from otherCR indicators affect the structure of terms For reason, or its The relationship between liquidity andin is investigated using latent affect the financial financial structure of firms firms inprofitability terms of of liquidity. liquidity. For this thisvia reason, CR or vari its vv Theaffect relationship between liquidity and profitability is investigated via using the financial structure of firms in terms of liquidity. For this reason, CR or its affect the financial structure ofsingle-handed firmsand in terms of liquidity. Forevaluate this reason, or its vv ants should not be thought determinants the of ables. That means functions of as liquidity profitability refer to latent variables ofCR structura ants should not bemeans thought as single-handed determinants to evaluate the level level of cur cur latent variables. That functions of liquidity and profitability refer latent ants should not be thought as single-handed determinants to evaluate the level of cur ants should not be thought as single-handed determinants to evaluate the level of assets. variables structural equation modeling respectively. of these in detailcur equation modeling respectively. Determinants of these Determinants functions are described in assets.of assets. functions are in detailthe in this part of the paper. MARGIN is for assets level thisassets. part of thedescribed paper. MARGIN is the the one one of of the major major determinants determinants for current current assets level in in the the fram fram 2 4 5 ,2MARGIN3,for LEV and4 TURN by: Liquidity is defined as the function of CR MARGIN is the one of the major determinants current assets level in the fram 3 5 MARGIN is the one of the major determinants for current assets level in the fram accounting practices: Increase in MARGIN causes an increase in cash or receivables andinTURN Liquidity is practices: defined as Increase the function of CR , MARGIN accounting in MARGIN causes an, LEV increase cash orbyreceivables accounting practices: Increase in MARGIN causes an increase in cash or receivables accounting=practices: Increase in of MARGIN causes an increase inaffect cash or receivables counts. means high MARGIN should (1) Liquidity �(CR counts. Which Which means high level level of� , TURN MARGIN should positively positively affect the the liquidity liquidity � � , MARGIN � , LEV � ).(1) counts. Which means high level of MARGIN should positively affect the liquidity counts. Which means high level of MARGIN should positively affect the liquidity o firm. Total firm. amount of the current assets is the fundamental accounting measurement for li Total amount of the current assets is the fundamental accounting measurefirm. firm.position of the financial structure. In this sense, Current Ratio (CR) is generally quidity ment for liquidity position of the financial structure. In this sense, Current Ra- accepted as the main indicator for liquidity assessment in the frame of working capita 2 2 CR ⁄ShortTermLiabilities CR = = CurrentAssets CurrentAssets⁄ ShortTermLiabilities 2 ⁄ShortTermLiabilities management: As is known, increase in CR means more liquidity. On the other hand, CR is 2 CR = CurrentAssets 23 3 CR ⁄ShortTermLiabilities MARGIN = (TotalSales − CostofSales)⁄TotalSales, we use ‘cost of goods sold’ for manufacturin = CurrentAssets MARGIN = (TotalSales − CostofSales)⁄TotalSales . , we use ‘cost of goods sold’ for manufacturin 3 ⁄TotalSales MARGIN =firms (TotalSales − CostofSales) , we use ‘cost of from goods sold’ sold’for for manufacturin 3summarized the3commercial indicator of the financial decisions which indicators tha and of services service MARGIN = (TotalSales TotalSales , we we use use derive ‘costofofgoods goodsother sold’ for manufacturin commercial firms and ‘cost ‘cost − ofCostofSales) services sold’ sold’⁄for for service firms. firms. manufacturing or commercial andsold’ ‘costfor of services sold’ for service firms. commercial firms and ‘cost offirms services service firms. 4 ⁄ LEV LongTermLiabilities Equities firms and ‘cost of services service firms. 44commercial affect the= financial structure of firmssold’ in for terms of liquidity. For this reason, CR or its vari ⁄ LEV = LongTermLiabilities Equities . 4 4 LEV = LongTermLiabilities⁄Equities 55 ⁄ . TotalSales LEV == ⁄TotalAssets TURN =LongTermLiabilities TotalSales TotalAssets ants55 TURN should not be thought as⁄Equities single-handed determinants to evaluate the level of curren 5 TURN = TotalSales⁄TotalAssets TURN = TotalSales⁄TotalAssets assets. MARGIN is the one of the major determinants for current assets level in the frame o 32 Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture tio (CR) is generally accepted as the main indicator for liquidity assessment in the frame of working capital management: As is known, increase in CR means more liquidity. On the other hand, CR is the summarized indicator of the financial decisions which derive from other indicators that affect the financial structure of firms in terms of liquidity. For this reason, CR or its variants should not be thought as single-handed determinants to evaluate the level of current assets. MARGIN is the one of the major determinants for current assets level in the frame of accounting practices: Increase in MARGIN causes an increase in cash or receivables accounts. Which means high level of MARGIN should positively affect the liquidity of a firm. In the literature, the relation between leverage (LEV) and size (Total Assets) is discussed frequently. International evidence suggests that leverage is positively related to size (Rajan & Zingales, 1995; Schulman et al., 1996; Wiwattanakantang, 1999; Booth et al., 2001; Boateng, 2004; Padron et al., 2005; Gaud et al., 2005; Sayılgan et.al., 2006). Several reasons are depicted on the positive relation between leverage and size, such as cheaper access to outside financing, high level of collateral and etc. (Strebulaev, 2007). In this sense, firms listed and traded on National Market of Istanbul Stock Exchange have more ability for long term debt financing due to their sizes. In general manner, long term financing especially for current assets increases liquidity in short term. Therefore, it is expected that there is a positive relation between LEV and liquidity as well. Turnover (TURN) is the indicator of firm sales generated relative to the value of its assets in terms of cash conversion cycles. Therefore, turnover connects with the operating efficiency of a firm. Any decrease in operational efficiency make firms depend on more current assets for sustainability. In order to make a decision on adding TURN as an indicator into liquidity function, a correlation analysis was executed and the correlation coefficient between CR and TURN for the data set was found as -0.207 which is statistically significant at 1% (see Table 1). Accordingly, this study states the expectation of negative relation between the TURN and liquidity. cussed cussed frequently. frequently. International International evidence evidence suggests suggests that that leverage leverage is is positively positively related related to to current assets for sustainability. In order to make a decision on adding TURN as an indica (Rajan & Zingales, 1995; Schulman et al., 1996; Wiwattanakantang, 1999; Booth (Rajan & Zingales, 1995; Schulman et al., 1996; Wiwattanakantang, 1999; Booth et et tor 2001; into liquidity function, a correlation analysis was executed and the correlation coeffi 2001; Boateng, Boateng, 2004; 2004; Padron Padron et et al., al., 2005; 2005; Gaud Gaud et et al., al., 2005; 2005; Sayılgan Sayılgan et.al., et.al., 2006). 2006). Sev Sev cient between CR and TURN for the data set was found as -0.207 which is statistically reasons liquidity-are profitability tradeoff existence inrelation turkey… between leverage and size, 33 such depicted on the positive as chea reasons are depicted on the positive relation between leverage and size, such as chea significant at outside 1% (seefinancing, Table 1). Accordingly, this study states the expectation of negativ access high ofMARGIN, collateral and etc. access to to Table outside financing, matrix high level level collateral etc. (Strebulaev, (Strebulaev, 2007). 2007). In In 1. Correlation for CR,of LEV,and TURN relation between the TURN and liquidity. sense, listed on of Exchange sense, firms firms CR listed and and traded traded on National National Market Market of Istanbul Istanbul Stock Stock Exchange have have m m MARGIN LEV TURN ability for long term debt financing due to their sizes. In general manner, long term fina ability for long term debt financing due to their sizes. In general manner, long term fina Sig.1. Correlation Corr. Coef. Sig. Corr. Coef. Sig. Corr. Coef. TURN Sig. Corr. Coef.Table matrix forliquidity CR, MARGIN, LEV, ing for in term. it (r) (p) (r) (p) (p) ing especially especially for(p)current current (r)assets assets increases increases liquidity in short short (r) term. Therefore, Therefore, it is is expe expe CR MARGIN LEV TURN relation CR that – that there there 1is is aa positive positive relation between between LEV LEV and and liquidity liquidity as as well. well. Corr. Co- Sig. Corr. Co- Sig. MARGIN 0.213** 1 Turnover (TURN) is1 0.213** ef. (r) 0.003 (p) Corr. Sig. Corr. Sig. generated relative value ef. indicator (r)– (p)of Coef. (r) (p) Coef.to Turnover (TURN) is the the indicator of firm firm sales sales generated relative to(r)the the(p) value oo 1 CRassets –0.080 cash cycles. LEV 0.278 0.187* 0.010 – turnover assets in in terms terms of of cash conversion conversion cycles. 1Therefore, Therefore, turnover connects connects with with the the opera opera MARGIN 0.003 efficiency of Any decrease TURN –0.207** 0.005 0.278 –0.230** 0.002in -0.080 0.187* LEV efficiency of aa firm. firm. Any decrease in - operational efficiency depend –0.033 0.010 10.654 - 1 make – operational efficiency make firms firms depend on on m m -0.207** 0.005 -0.230** 0.002 -0.033 0.654 1 TURN current assets for sustainability. In order to make a decision on adding TURN as an ind Correlation is at at thethe 0.050.05 level (2-tailed). current assets for sustainability. In order to make a decision on adding TURN as an ind * *Correlation issignificant significant level (2-tailed). tor into function, aa 0.01 correlation analysis Correlation is at at thethe 0.01 levellevel (2-tailed). ****Correlation is significant significant (2-tailed). tor into liquidity liquidity function, correlation analysis was was executed executed and and the the correlation correlation coe coe byCR authors. TURN S Source: o ucient r c edeveloped :between developed authors. cient between CRbyand and TURN for for the the data data set set was was found found as as -0.207 -0.207 which which is is statistic statistic significant significant at at 1% 1% (see (see Table Table 1). 1). Accordingly, Accordingly, this this study study states states the the expectation expectation of of nega nega Profitability as realized measurement of Profitability as the the realized and measurement ofgained gainedbenefit benefitfrom fromallallbusibusiness perfor relation between the liquidity. 6 7 between the TURN TURN andfunction liquidity. , CFO and AC by: nessrelation performance is defined as the of ROA 6 7 mance is defined as the function of ROA , CFO and AC by .(2) ��ROA�Correlation , CFO� , AC� �matrix Profitability� =Table . (2) Table 1. 1. Correlation matrix for for CR, CR, MARGIN, MARGIN, LEV, LEV, TURN TURN CR MARGIN LEV TURN CR(ROE) and returnMARGIN LEV Return on equity on assets (ROA) are the most usual in-TURN ⁄ ROA = NetIncome TotalAssets Corr. Co- the Sig. Corr. CoSig.firm in Corr. Sig. While Corr. dicators used to measure of the general terms. Corr. Co- Sig.profitability Corr. CoSig. Corr. Sig. Corr. 7 ef. (r) � − ROA (p) ef. (r) (p) Coef. (r) (p) Coef. (r) �CFO ⁄ AC = TotalAssets (p) ef. (r) (p)profit from Coef.the (r) invested (p) Coef. (r) ROE is a measureef. of(r) firm’s efficiency to generate capi1 CR 1 CR tal, ROA is generally used to compare1 companies 0.213** 0.003 - by taking the all kinds of inMARGIN 0.213** 0.003 1 MARGIN vestments into account. In this sense, because of the availability of-- significant -0.080 0.278 0.187* 0.010 1 LEV -0.080 0.278 0.187* 0.010 1 LEV -0.207** 0.005 -0.230** 0.002 -0.033 1 TURN differences the equity of sample0.002 firms and-0.033 the main0.654 concentra-0.207** 0.005values-0.230** 0.654 1 TURN between * Correlation is significant at the 0.05 level (2-tailed). * Correlation at the 0.05 level (2-tailed). tion of this paperisissignificant on the validity of liquidity-profitability tradeoff, ROA is pre** as Correlation is significant at the 0.01 level (2-tailed). ferred determinant of profitability function. Also, total investing amount of ** Correlation is significant at the 0.01 level (2-tailed). Source: developed byofauthors. assets is the identifier the total capacity of firm and the amount of assets repSource: developed by authors. 6 Sig. Sig. (p) (p) - resents the firm size. In the literature, there is a generalization on the existence of positive relation between size and profitabilityof that derives from from different Profitability as the realized measurement gained benefit all business per Profitability as the realized measurement of gained benefit from ways; such as abilities of firms to generate discounts from suppliers, gettingall fa- business per 6 7 mance is as function of AC vorable credit terms and conditions, their and receivables mance is defined defined as the the function success of ROA ROA6in,, CFO CFO and AC7 by by collection and � etc. (Eljelly, 2004). Therefore, is� ,the indicator to clarify the Profitability ��ROAROA AC�summarized .. (2) � = � , CFO Profitability (2) � = ��ROA � , CFO� , AC� � profitability of a firm relative to its size. 6 66 ROA = NetIncome⁄TotalAssets ROA = NetIncome⁄TotalAssets . = �CFO⁄TotalAssets� − ROA AC AC = �CFO⁄TotalAssets� − ROA . 77 7 34 Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture On the other side, ROA is calculated by accounting numbers based on accruals. Therefore, taking only ROA as an indicator to evaluate the profitability of a firm is inadequate. In terms of complete disclosure, cash flow from operations (CFO) should be taken into account (Baumol, 1952; Miller and Orr, 1966). Therefore, CFO is added into analysis as another determinant of profitability function and it is expected that increase in CFO means increase in profitability. Non-debt tax shield includes methods generally derived from accounting techniques to create tax-shield advantages like debt financing. Another alternative advantage comes from the depreciation as a means of reducing corporate taxes (Rubio & Sogorb-Mira, 2012). Thus, in terms of cash generation, tax deductions under depreciation expenses are the substitutes of tax benefits from debt financing (DeAngelo & Masulis, 1980). In this case, it could be clearly expected that firms with high level of fixed assets gain more benefit from nondebt tax shield advantages derives from depreciation (Titman & Wessels, 1988; Rajan & Zingales, 1995; MacKay & Phillips, 2005; Faulkender & Petersen, 2006; Wald & Long, 2007; Kale & Shahrur, 2007) and the spread between CFO and net income should be higher for the firms that have bigger amount of tangible assets. Validity of this expectation causes smaller accounting assessment of profitability in terms of ROA due to high level of total assets for such firms (Table 2). The correlation coefficient between accruals (AC) and ROA for the Turkish firms is –0.416 and statistically significant at 1% which supports our expectation about non-debt tax shield effect on profitability measurement derives by ROA calculations. Accordingly, this study states the expectation of negative relation between the AC and profitability. Table 2. Correlation matrix for ROA, CFO, AC ROA CFO Sig. (p) Corr. Coef. (r) Corr. Coef. (r) ROA 1 CFO 0.096 0.192 1 AC –0.416* 0.000 0.050 Sig. (p) AC Corr. Coef. (r) Sig. (p) 1 – – * Correlation is significant at the 0.01 level (2-tailed). S o u r c e : developed by authors. – 0.495 35 liquidity- profitability tradeoff existence in turkey… Structural Equation Modelling Structural equation modeling (SEM) is used to model causal relationship between latent variables and to disclose linear relationships between independent and dependent variables. (MacCallum & Austin, 2000; Schumacker & Lomax, 2004; Garcia et al., 2013). SEM refers not to a single statistical technique but to a family of related procedures such as causal modeling and covariance structure analysis. (Kline, 2011). In social sciences, these causal models draw attention because of their ability to describe structural theory bearing on some phenomenon (Koç et al., 2016). The specification of the structural model can be presented with graphical presentation, system of simultaneous equations or matrix expression. By graphical representation, causal relationship between observed variables and latent variables is introduced visually. Based on the theoretical model developed in Figure 1, we formulated the research hypothesis as follow: H1: The liquidity of firm has a direct positive effect on profitability (Means, invalidity of liquidity-profitability tradeoff in Turkish market). Figure 1. Model development ߜଵ ߜଶ ߜଷ ߜସ CR MARGIN LEV TURN ߣଵ ߣଶ ߣଷ ߣସ Liquidity ߦଵ S o u r c e : developed by authors. ߛଵ Profitability ߟଵ ߣଵ ߣଶ ߣଷ ROA ߝଵ CFO ߝଶ AC ߝଷ Assessing model’s fit in SEM is the most controversial subject. The overall fit of the observed data to hypothesized model must be assessed before interpreting individual parameters (Jöreskog et al., 1999). Fit indices are used to control whether the covariance matrix derived from the proposed theoretical model is different from the covariance matrix derived from the sample (Shook et al., 2004). A statistically insignificant difference reveals that the errors are insig- observedobserved data to hypothesized model must be must assessed before interpreting individual pa rameters (Jöreskog et al., Fit indices are used to the covariance ma data to 1999). hypothesized model be control assessed before interpreting indiv Assessing model’s fit in SEM is observed data to hypothesized model must be most assessed before whether interpreting individual paAssessing model’s fit in SEM is the controversial subject. The overall fit Assessing model’s fit in SEM is the most controversial subject. The overall fit of the rameters (Jöreskog et al., 1999). Fit indices are used to control whether the covariance ma rameters et al.,Fit 1999). Fitare indices are used towhether control whether the covari trix derived from (Jöreskog the proposed theoretical model isto different from thehypothesized covariance matrix observed data to mode rameters (Jöreskog etto al., 1999). indices used control the covariance maobserved data hypothesized model must be assessed before interpreting individu observed data totrix hypothesized model must be assessed before interpreting individual patrix derived from the proposed theoretical model is different from the covariance matrix derived the proposed theoretical isinsignificant different from covarian derived fromfrom the sample (Shook et al., 2004). A statistically difference reveal rameters (Jöreskog et al.,the1999). Fit i trix derived the from proposed theoretical model is model different from the covariance matrix rameters (Jöreskog et al., 1999). Fit indices are used to control whether the covarian 36 Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture rameters (Jöreskog et al., 1999). Fit indices are used to control whether the covariance maderived from the sample (Shook et al., 2004). A statistically insignificant difference reveal that the errors are insignificant and the model is supported. Various fit indices have derived the(Shook sampleet(Shook et al., A statistically insignificant differenc trix derived from the proposed theo derivedtrix from the from sample al., 2004). A 2004). statistically insignificant reveals derived from the proposed theoretical model is different fromdifference thematrix covariance trix derived from the proposed theoretical model is different from the covariance that the errors are insignificant and the model is supported. Various fit indices hav that theare errors are and theiscompeting model supported. Various fit have indi emerged to compare the ofinsignificant proposed model or Various baseline models. nificant and the model is fit supported. Various fitwith indices haveisemerged comderived from theto sample (Shook et al that the errors insignificant and the model supported. fit indices derived from the sample (Shook et al., 2004). A statistically insignificant difference derivedpare fromthe thefit sample (Shook et al., 2004). A statistically insignificant difference reveals emerged to compare the fit of proposed model with competing or baseline models. of proposed model with competing or baseline models. compare fit oftwo proposed model with competing or models. baseline In thisemerged atomodel latentwith variables which were liquidity and models profita that the errors are insignificant an emerged tostudy, compare theare fitcontaining of the proposed model competing or baseline that the errors insignificant and the model is supported. Various fit indice In this study, a model containing two latent variables which were liquidity that thebility errors are insignificant and the model is supported. Various fit indices have In this study, a model containing two latent variables which were liquidity and profita was considered. While the profitability of firms is an endogenous variable, liquidity In this study, containing a model containing two latent variables which were liquidity an emerged towere compare the fit ofprofitapropos this study, model twothe latent variables which liquidity and andInprofitability considered. While profitability of firms is an endogemerged toawas compare thethe fitmodel of proposed model with competing or baseline models. emergedbility to compare the fit of proposed with competing or baseline models. was considered. 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While the first pro of firms is an exogenous variable. Generally, SEM consists of two parts wherein the bility was considered. While theofprofitability of firmspart is an endogenous variable, liq and the second part concerns the measurement model validation. Based on the the bility was While the profitability firms is ansecond endogenous variable, liquidity partconsidered. involves the structural model testing and the concerns measuremen model validation. Based on the proposed model, the structural part can be written asthe mea part involves the structural model testing and the second part concerns of firms is an exogenous variable. G part involves the structural model testing and the as: second part concerns the measurement proposed model, the structural part can beGenerally, written of firms is an exogenous variable. SEM consists of two parts wherein th of firmsmodel is an validation. exogenous variable. Generally, SEM consists of two parts wherein the first Based on the proposed model, the structural part can be written as model on the proposed model, structural part can beasmodel writtente ߛ ߞଵଵBased onBased (3) ߟଵଵ ൌ ଵ ߦଵ ଵ validation. partthe involves thebe structural ଵ model validation. the proposed model, the structural part can written involves the structural testing andpart theconcerns second part part involves theߛଵstructural model testingmodel and the second the concerns measurement ൌ ߦߟଵ ൌߞଵߛ (3) (3) the(3)measu ߟଵ part where ߟଵଵߛ is an endogenous of firm), ߞଵଵ is Based an(3)exogenous (pre ଵ ߞ ଵ ߦଵ ߞଵ latent variable (profitability model validation. on the propo ߦ ߟଵ ൌ ଵ ଵ validation. ଵ model Based on the proposed model, the structural part can be written as model validation. Based on the proposed model, the structural part can be written as where ߟଵwhere is an ߟendogenous latent variable (profitability of firm),ofߞଵfirm), is an ߞexogenous (pre is an endogenous latent variable (profitability is an exogen dictor) latent variable (liquidity of firm), ߛ regression coefficient relating endogenou ଵ ଵ ൌ ߛ ߦ ߞ ߟ ଵ where ߟଵ ߟis is an an ߛ endogenous latentvariable variable(profitability (profitabilityofofଵfirm), firm), exogenous ଵ ଵߞଵisis ଵan where endogenous latent an exog(3) (preଵ ߦଵ ߞଵ(liquidity of firm), ߛ regression coefficient ߛଵ ߦଵ latent ߞଵଵ ൌ variable (3) relating endogenou ߟଵ ൌdictor) ଵ variables to exogenous variables, and ߞ is an error term. The critical parameter of en the dictor) latent variable (liquidity of firm), ߛ regression coefficient relating enous latent(liquidity variable (liquidity coefficient ଵ of ଵ regression where ߟଵ is an endogenous latent va ଵ dictor)(predictor) latentߟvariable oflatent firm), ߛଵ firm), regression coefficient relating endogenous where is an endogenous variable (profitability of firm), ߞ is an exogenou ଵ ଵ where ߟ endogenous latent variable (profitability of firm), ߞ is an exogenous (prerelating variables to exogenous variables, and is an error term. variables to exogenous variables, and ߞ is an error term. The critical parameter of th ଵ is an endogenous ଵ ଵ and to an error term. Theparameter critical paramet model invariables equation is ߛexogenous because itvariables, quantifies theߞerror hypothetical relationship between profita ଵ variables, ଵ is dictor) latent variable (liquidity of ଵ variables toparameter exogenous and ߞof an term. The critical of the ଵ is dictor) latent variable (liquidity firm), ߛ regression coefficient relating endog The critical of the model in equation is because it quantifies the ଵ dictor) model latent variable (liquidity of firm), ߛଵ regression coefficient relationship relating endogenous in equation is ߛ because it quantifies the hypothetical between profita ଵ in equation is ߛଵ itbecause it quantifies the hypothetical relationship betwee bility and liquidity ofߛfirms. variables to exogenous variables, an hypothetical relationship between profitability and liquidity of firms. quantifies the hypothetical relationship between profitamodel in model equation isexogenous ଵ because variables to variables, and ߞ is an error term. The critical parameter ଵ variables to exogenous variables, and ߞ is an error term. The critical parameter of the bility and liquidity of firms. ଵ The observed variables are linked to latent variables by way of measurement equation bility andvariables liquidity of firms. Theand observed are linked to latent variables by in way of measuremodel equation is ߛଵ because it qu bility liquidity of firms. model in equation is ߛ because it latent quantifies therelationship hypothetical relationship between p ଵ because it quantifies the hypothetical between profitamodel ment in equation is ߛ equations for the exogenous and endogenous variables. Equations of The observed variables are linked to variables by way of measurement equation Theଵ observed variables are linked to latentbility variables bymeasurement wayvariable ofenmeasurement forThe the observed exogenous and endogenous variables. Equations of endogenous are defined and liquidity of firms. variables are linked to latent variables by way of equations dogenous variable are defined as: and liquidity of firms. bility and forliquidity thebility exogenous and endogenous variables.variables. Equations of endogenous variable variable are defined for of thefirms. exogenous and endogenous Equations of endogenous ar as: observed variablesare aredefined linked for the exogenous and endogenous variables. Equations ofThe endogenous variable The observed variables are linked to latent variables by way of measurement equ The observed variables are linked to latent variables by way of measurement equations as: as:ߣଵ ߟଵ ߝଵ (4) ൌ (4)endogenous v for the exogenous and as: for the andvariables. endogenous variables. Equations ofvariable endogenous variable are d exogenous for the exogenous and endogenous Equations of endogenous are ߟ ߝ (4)defined ൌ ߣ ଵߟ ଵ ൌߝߣ ଵ (5) ߟ ߝ (4) ൌ ߣ (5) ଵ ଵ ଵ ଵ ଶ ଶ as: ଵ ଶ ଶ as:ൌ ߣଵ ߟଵ ߝଵ (4) as: ൌൌߣߣ (5) ଶ ߟଵ ߟଵ ߝଶ (5) ߝߝଷଷߝߣଶଶ(6) (6) ൌ ߣଵ ߟଵ ߝ(5) ൌ ൌ ߣଷଷଶߟߟଵଵଵൌ ଵ ଶ (4) ߣଵ ߟଵ ߝଵ ߝ ൌ ߣଵ ߟൌ (4) (6) ଵ ߣଷ ߟ ଵଵ ߝଷ (6) ൌߝexogenous ߣଷ ߟଵ ߝଷ variable are defined as: and equations of ൌ ߣଶ ߟଵ ߝ(6) ଶ ൌ ߣ ଷ ߟ ߝ variable are defined as: ଷ ߟଵ of ൌ ߣ (5) and equations exogenous ଶ variable are defined as: ଶ ଵ and ൌ ߣଶequations ߟଵ ߝଶ of exogenous (5) and equations of exogenous variable areas: defined as: ൌ ߣ ߟ ߝ andequations ofߣexogenous variable are defined ଷ ଷ ଵ ߟ ߝ (6) ൌ ଷ ଷ ଵ (6) ൌ ߣଷ ߟଵ ߝଷ and equations of exogenous variable and equations(7) of exogenous variable are defined as: and equations ofߣexogenous ൌ (7) ଵ ߜଵ ଵ variable are defined as: ଵ ߦଵ ଵ ൌ ൌ ߣߣଵଵߦߦଵଵ ߜߜଵଵ (7) (7) ൌ ߣଶߦଵ ߜଶ (8) (8) ൌ ൌ ߣߣଶଶߦߦଵଵ ߜߜଶଶ (8) (8) ൌ ߣଷߦଵ ߜଷ (9) (9) ൌ ൌ ߣߣଷଷߦߦଵଵ ߜߜଷଷ (9) (9) ൌ ߣସସߦଵଵ ߜସସ (10) (10) ൌ ൌ ߣߣସସߦߦଵଵ ߜߜସସ (10) (10) where ߣ, ߣ are factor loadings, and ߝ , ߜ are error terms. where are factorloadings, loadings, and and are errorterms. terms. where where ߣߣ,, ߣߣ are are factor factor loadings, and ߝߝ,, ߜߜ are are error error terms. The data was analyzed and interpreted within the scope of the research in line with the The The data data was was analyzed analyzed and and interpreted interpreted within within the the scope scope of of the the research research in in line line with with the the specified purposes by utilizing descriptive statistics and several statistical analyses. SEM specified specified purposes purposes by by utilizing utilizing descriptive descriptive statistics statistics and and several several statistical statistical analyses. analyses. SEM SEM and other statistical analyses were performed using IBM AMOS (Analysis of Momen and and other other statistical statistical analyses analyses were were performed performed using using IBM IBM AMOS AMOS (Analysis (Analysis of of Moment Momen Structures) and IBM SPSS (The Statistical Package for Social Sciences). Statistical signifiStructures) Structures) and and IBM IBM SPSS SPSS (The (The Statistical Statistical Package Package for for Social Social Sciences). Sciences). Statistical Statistical signifisignifi cance value is set as p < 0.05. 37 liquidity- profitability tradeoff existence in turkey… The data was analyzed and interpreted within the scope of the research in line with the specified purposes by utilizing descriptive statistics and several statistical analyses. SEM and other statistical analyses were performed using IBM AMOS (Analysis of Moment Structures) and IBM SPSS (The Statistical Package for Social Sciences). Statistical significance value is set as p < 0.05. Empirical results In order to test the validity of liquidity-profitability tradeoff in Turkish market, a structural equation model was employed, in which an exogenous latent factor (liquidity) and an endogenous latent factor (profitability) were considered. The scale for each factor was set by fixing the factor loading to one of its indicator variables and the maximum likelihood method was used to estimate the parameters of the model. The model that satisfies both goodness of fit measures and theoretical expectations was selected. The key fit statistics of the structural model summarized in Table 3 shows a value of χ2 / df = 3.269, CFI of 0.760, GFI of 0.943, AGFI of 0.907, NFI of 0.705, and RMSEA of 0.079. The statistic of χ2 / df is within the acceptable limit (Schumacker & Lomax, 2004). GFI and AGFI are all above 0.90, suggesting a good fit between the structural model and the data (Jöreskog et al., 1999; Byrne, 2010). RMSEA is below the suggested threshold value of 0.08 (Brwone & Cudeck, 1993). Therefore, the hypothesized model for the inexistence of the validity of liquidity-profitability tradeoff was verified by SEM, so consistence of the model to the data was acceptable. Table 3. Goodness of fit indices Fit Indices Model Value Recommended Value χ2 / df 3.269 1 to 5 The Comparative Fit Index (CFI) 0.760 0 (no fit) – 1 (perfect fit) Goodness of Fit Index (GFI) 0.943 0 (no fit) – 1 (perfect fit) Adjusted Goodness of Fit Index (AGFI) 0.907 0 (no fit) – 1 (perfect fit) The Normed Fit Index (NFI) 0.705 0 (no fit) – 1 (perfect fit) Root Mean Sq. Error of Approx. (RMSEA) 0.073 <0.05 (very good) – 0.1 (threshold) S o u r c e : developed by authors. 38 Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture CR ߜଵ ߣ ROA ߝଵ ߣଵ Figure 2 presentsଵdetails regarding the parameter estimates for the modߣଶ MARGIN coefficient estimatesߛfor the hypothesized el.ߜଶStandardized model with correߣଶ ଵ Profitability Liquidity ߝଶ CFO ߣଷ presented in Table 4. According to the statistical sponding t-value are signifiߟଵ ߦଵ ߣଷ ߜଷ LEVparameter cance of the estimates from SEM, the hypothesis which expresses ߣସ ߝଷ AC supported. a positive relationship between liquidity and profitability was TURN ߜସ From standardized coefficient estimate, it is concluded that liquidity-profitability tradeoff is not valid in Turkish market. Figure 2. Structural model with standardized path coefficients ߜଵ ߜଶ ߜଷ ߜସ CR 0.19 0.97 0.24 MARGIN 0.95 LEV Liquidity 0.44 Profitability 0.08 ROA ߝଵ CFO ߝଶ AC ߝଷ -0.40 -0.24 TURN S o u r c e : developed by authors. Table 4. Standardized coefficient estimates of SEM Path Standardized Coefficient Estimate t – Value p 0.435 2.350 0.019 –0.237 –1.969 0.049 MARGIN ← Liquidity 0.235 1.963 0.050 CR ← Liquidity 0.190 LEV ← Liquidity 0.951 ROA ← Profitability 0.973 CFO ← Profitability 0.085 1.117 0.264 AC ← Profitability –0.399 –2.555 0.011 Profitability ← Liquidity TURN ← Liquidity S o u r c e : developed by authors. – 1.937 – – 0.053 – liquidity- profitability tradeoff existence in turkey… Discussion: a detailed look on determinants 39 Inexistence of the validity of liquidity-profitability tradeoff in Turkish market is not surprising when the results of the determinants used in functions are analyzed. In other words, a clear understanding of this invalidity needs a detailed look on some determinants as well. Firstly, all results are consistent with our expectation in terms of the directions of the effects under the comments that mentioned in Section 2.2. CR, MARGIN and LEV have positive effect on liquidity, while TURN is the only determinant that has negative effect. On the other side, profitability is affected positively by ROA and CFO, while AC has negative affect on profitability. However, the results create need for making a discussion to explain this invalidity of liquidity-profitability tradeoff in Turkish market. In this sense, remarkable information can be obtained when concentrated on the findings of liquidity function. There are meaningful differences between the effect sizes of determinants. While CR, MARGIN and TURN has relatively low effect size (standardized coefficients for CR, MARGIN and TURN are 0.19, 0.24, –0.24, respectively), LEV has significantly high effect size (standardized coefficient for LEV is 0.95) on liquidity. This differentiation of LEV enables us to reveal two main inferences: (1) The inadequacy of CR or its variants to analyze the liquidity-profitability tradeoff and (2) the reality of applying prudent working capital management (P-WCM) by managers in Turkish market as an emerging one. In the literature, generally, the researches on liquidity-profitability tradeoff are constructed on separate relationships between CR or its variants and profitability (Eljelly, 2004). In this paper, a more comprehensive analysis is applied by employing SEM to disclose the effects of all determinants on liquidity all together. As seen from our findings, CR has not much explanatory power on the liquidity in the frame of financial structure formation. The fundamental reason of that is CR or its variants are the indirect summarized results of other direct financial decisions that taken by managers strategically. The word of strategically means that the preferences of managers in financing of current assets. High level positive effect of LEV on liquidity indicates that managers of Turkish firms prefer long term liabilities rather than current ones to finance current assets. In the other words, they apply P-WCM to overcome possible liquidity shocks (Uremandu, 2012; Modi, 2012; Akoto et al., 2013; Zakaria & Amin, 2013). This fact is coherent with our point of view, which asserts that 40 Furkan Baser, Soner Gokten, Guray Kucukkocaoglu, Hasan Ture managers behave prudent in financial decisions in Turkey because of their bad experiences come from troubled times. On the profitability side the result indicates a moderate level of positive effect between liquidity and profitability which is the other discussion issue that needs to be explained in addition to the invalidity of liquidity-profitability tradeoff. Firstly, the significant effect of ROA on profitability, (standardized coefficient for ROA is 0.97), verifies our choice on using it as a determinant instead of ROE. Since ROA includes the all short and long term financing alternatives especially for current assets, it completely reflects the outcome of applying P-WCM in terms of profitability. As discussed in Kling et al. (2014), cash holdings increase the ability of firms to cover possible operating loses emerged especially by liquidity shocks and to reach current liabilities in better conditions as an alternative of financing current assets, for example suppliers are more willing to provide trade credit to firms with higher liquidity positions. Also, as discussed in Jung and Kim (2008) study, stockpiling of liquid assets provides incentives for firms to increase their leverage because cash holdings decrease potential financial distress costs and increase target debt-equity ratios. In this sense, firms in Turkey decrease financial risks on cash conversion cycles by applying P-WCM and increase operating efficiency by gaining ability and flexibility on managing current liabilities. Conclusion In this paper, the existence of the validity of liquidity-profitability tradeoff is analyzed for Turkish market which has many financial experiences on troubled times that caused liquidity shocks. Our main expectation is that Turkish firms could show a tendency to have high liquidity position by ignoring the liquidityprofitability tradeoff in terms of working capital management due to gained experiences come from bad times. 2014 is the best fitted year to test this alleging remark as this year represents the best economic conditions that Turkey has faced. The data of 187 firms listed and traded on National Market of Istanbul Stock Exchange (BIST-Borsa Istanbul) are used. Structural equation modelling is applied to provide a more comprehensive analysis and the functions of liquidity and profitability are constituted by using Piotroski’s criterions of liquidity/solvency, operating efficiency and profitability to generate structural equation model of the study. 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