J. Appl. Environ. Biol. Sci., 8(4)95-102, 2018 | ISSN: 2090-4274 |
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1,3Lecturer(Finance),DepartmentofManagementSciences,BachaKhanUniversity,Charsadda,Pakistan 2MBA(Scholar),DepartmentofManagementSciences,BachaKhanUniversity,Charsadda,Pakistan 4Lecturer(Finance),InstituteofBusinessStudiesandLeadership,AbdulWaliKhanUniversity,Mardan 5Lecturer(ManagementSciences),UniversityofHaripur
Received: November 9, 2017 Accepted: February 7, 2018
This research’swork done to examine the financialrisks(CreditRisk, LiquidityRisk) effectson companies’ stock returnslisted fromPakistanstock Exchange.Therearenarrownumber ofresearch studiespassedoutin thefieldof financialrisks.ThepurposeofthisstudyistospreadtheworkofMehriAkhaviBabi(2015)andMehriAkhaviBabi includingthelatestdata,appropriatemodels,includingpaneldata.Therearetwoindependentvariables(CreditRisk and Liquidity Risk) and one dependent variable (Stock Returns) and one control variable (Company Size). This paper includes 50 non-financial companies listed in PSX-100 index for the period of 2010 to 2015. This study demonstrates the relationship among credit risk, liquidity risk, size and stock returns of the company. The results showthatthatCreditrisk hassignificantbutnegativerelationship with stockreturnof company, Liquidityriskhas significantpositiverelationship withstockreturnofcompanyandSizehaspositiveandsignificantrelationshipwith stockreturnofcompany. KEY WORD: CreditRisk,LiquidityRisk,Size,StockReturns
Fortheprofit and wealth maximization, theinvestment decision-making isalmost certainlythe utmostvitalpartof the investment, which required to investors. Consequently, for the decision-making process, the collection of information is a necessary and important feature. This information’s are collected from many sources such as securitymarket,company’sannualreportsand news etc.Theutmost significantinformation source is the financial reporting,which deliver information for assisting decision-making process. Information is moreover measured as a planned tool in decision-making, and the superiority of decisions depend on the precision and suitability of the informationaccessiblethroughoutdecision-makingprocess.(Mirnejad,Valipour&Alame-Haeri,2013). Raei and Saeidi, (2010) investigate to study the financial risk management, financial engineering. They study the conceptof risk and returns thatrisk has vast importance in finance. All the investors wish to get greater return on their investment.Thetwo-foremostprincipleoftheinvestment-decisionisrisk&returnandthegreaterreturn,asper the lowest risk is a significant condition. Therefore, risk is a concept which claims that finance contributors ask about risk level of securities which they face in the market. Risk is a crucial condition for investment. Lastly, a certainshareshouldbepurchasedaftergeneralanalysisofthecircumstances.Thefinancialriskshavestraighteffect ontheearningsofbusinessesandcouldbeprimeoftheirdisappointment.
Harry Markowitz,(1958) bring a solution, was CAPM. They investigate the stock returns and risks relationship. Black (1972), Sharp and Linter (1964) used a model to calculate risk-free rate and risk premium. They scale the stockssensitivitybyBeta factor, when financialcrisescover all over theworld in 1980’sand1990’s.Thenew risk managementtechniquesarosetocontrolalltypeofrisksand logicallyoneriskmanageanotherone.Theriskisvery appropriateforfinancialandnon-financialorganizationare;(market,interestrate,liquidity,credit,foreignexchange and solvency risks). Risk recognition is an action of risk management which evaluate the risk and explanation of risk. In thisresearch report, theyexamineon three types of risk that mostlyfaced such as creditrisk, liquidityrisk andsolvencyrisk. TherationalityoftherelationshipbetweenearningsandreturnswasfirstpresentedbyBallandBrownin1968inan article titled as “An empirical evaluation of accounting income numbers” and their null hypothesis stated that
*Corresponding Author: Muhammad Nisar Khan, Lecturer (Finance), Department of Management Sciences, Bacha Khan University,Charsadda,Pakistan.Email:nisarmgnt@bkuc.edu.pk
accounting income numbers were not beneficial for stock exchange investors. Therefore, their research hypothesis appealed that thesenumberswere suitable for investors.The findingsof their studyresulted in therejection of the null hypothesis and it showed that a general review of the stock prices, after the distribution of income reports verifiedthatthe informationcontainedin the annualincome number,wasbeneficialand thedirectionofchangesin reportedaccountingincome,hadpositivecorrelationwiththechangesinstockpricesincomparisonto theprevious year. They also concluded that the information presented in capital market was beneficial on condition that it suggested investors’ reactions to bring up changes in stock prices or in the volume of stock exchanges (Ball & Brown,1968). Shabahang,(2003)believesthatthe mainpatternofearningsandreturnsisahypothesisbasedonwhich thecapital marketachievesefficiencyin comparison totherelatedinformationwhich isavailabletothepublic.Healsoclaims that thehypothesisofefficient market refers to thereaction rateof thesecuritiesofcapital marketcompared to the distribution of new information. Therefore, the definition of the efficiency of market consists of the fact that the capital market reflects the available information thoroughly and the market prices show immediate reaction to the newinformation;thatis,thenewinformationhasimmediateeffectonthesecuritiesprice. Therearebasicprinciplesininvestment which statedthat thecapitallosesthrough risk and pursuedtowardearning and returns. Theresult shows that the investorswho take risk and impede the investment in business, that is risky andunsafetheirreturn.Everyinvestmentisinvolvinginrisk. TeimouriandAbzari,Samadi,(2008)claimedthatriskandfearoflossinallbusiness.Buthighandlowlevelofrisk dependoninvestment.Thus,investorimagineenoughearningsbasedoninvestedcapital. RaeiandSaeidi,(2010)reportedthattheearningsdirectlyaffectedbyfinancial-riskofthecompaniesandwhatthey arelending fromthe financialinstitution.Therefore,seeingthatvitalroleofrisksininvestment,andthisstudywas an attempt to inspect that two types of risks, liquidity and credit risks can affect the relationship of return and earning. Unsystematic-risk factors(creditrisk and liquidityrisk) are the most vitalcomponent frompastseveral years. The earlier researchesexhibit that,itseffectcompanies’ stockreturn.Theproblemofthisstudywas that theworkdone onunsystematic-riskfactorsweretoomuchlowinthecontextofPakistanandtherewerenobutlittleworkhasbeen done to identify the accurate effect of unsystematic-risk factors on companies’ stock return. Different researchers workedoneffectoffinancial-risk factors(systematicrisk,unsystematicrisks) onstockreturnbuttheyusedmostof systematic-riskfactorsorbothsystematicandunsystematicriskfactorsmixedinresearches.So,thisstudyusedonly onesideoffinancial-risk factors,wasunsystematicrisks:includingcreditriskandliquidityrisk.Thisresearchmain objectives, to determine the effect of financial risks such as Liquidity and credit risks on stock returns. To investigatetheCreditriskandLiquidityriskeffectonstockreturns.
HyoungGooKangandChoongOhKang,(2009)investigatedtheCreditrisk’seffectonstockreturn.Theycollected thedatafromKoreaCompositeStockPriceIndex(KOSPI)coveringperiod from1995 to2007.CrossingtheAsian FinancialCrisisin1997-1999,Dot-comBustin2002andCreditCardCrisisin2002-2003inKorea.Theyconcepted asystematicrisk factorsin relation to credit risk bymeans ofthecreditblowoutsof individual firmsresulted from theMerton(1974)model.ThecreditfactorcapturesasystematicriskfromKoreanSM. Empirical tests and the Korean stock market show the credit risk factor exhibits meaningfully positive premiums evenaftercontrollingbyFamaandFrenchthreefactor. NasrinMoradiandMohammad Mohebbi,(2015)researchedontherelationshipbetweentheliquidityriskandstock return.Samplesize,6oilcompaniesweretaken.Thatwereactivein2011to2013 inTehranstockexchange.Fama and French model was used to investigate the relationship among dependent and independent variable. Statistical analysesweredonebasedonmulti-choiceregressionanddatawasmonthlyandpanel.Theresultsshowthatthesize ofcompanydoesn’t significant effectonoil companiesstockreturn, asresult frominvestorpoint ofview butbook valuetomarketvalue,marketriskpremiumandliquidityriskhassignificanteffectonstockreturnofoilcompanies, Tehranstockexchangethatrepresentstheimportanceofthesevariablesinstudiedcompaniesstockreturn. SadiaIqbal,(2015)investigated inherstudythatROEandCCRhaveasignificant&negativeaffectwhiletheROA andCurrentRatiohavepositive&significantresultonliquidity. ROA and Current Ratio havepositive affect on liquidityto theupward but ROE and CAR havenegative affecton liquiditytothedownward. If the ROE and CAR Rises the risk of liquidity will decrease. If the ROA & Current Ratio increases the risk of Liquiditywillincrease.
J. Appl. Environ. Biol. Sci.,8(4)95-102,2018
NasirAkram,(2014)theyputAsk-bid-spreadforvariableproxiestoinvestigatetheriskofliquidity.Informationhas beengatheredfromtencompaniesregisteredonKSEPakistanfrom2005-2012. Fortheinformationinvestigation,whattheycollectusetwo phaseregressions.Andamongtheliquidityandreturns theresultsshowanegativeimplication. MehriAkhavi Babi, (2015)theyinvestigated the financial risk,earnings per share and stock returns (TSE Iran). 65 companies were selected, 2008 to 2013.Thelinear and multiple regressions were used to test the hypotheses. The consequencesshow thattheEPS hasapositive effect&significant effectonreturn.Furthermore, theconsequences show that the solvency & credit risks were inverse & significant effect on EPS & stock returns. But the liquidity relationwasinsignificant. Florian Steiger, (2010) Theyexamined the prospect ofapplying derivative risk payments to describereturn. There are several kinds of risk appear in the market because of fast developing derivatives market by trading, such as interestrate,creditandmanymore. TrilochanTripathyandEshanAhluwalia,(2015)Explainedthattheuncertaintyandexpectationareveryinteresting thingsin themarket event tobuild it. TheyExamine therelationship among liquidityand equityreturnin financial system and daylong effectof liquidity& EquityReturn in the DayDuring Government budgetnotice. Theyused theOLS&ARDLModels.Theyrevealed therouteandmagnitudeofrelationshipamongvaries liquidityproxies& daily stock return in Indian stock market. The study shows that the returns have significant active relation with liquidityscales.Morethattheeffectofliquidityonreturnisrelativeprominentinthedateofbudgetspeechthanthe date of post budget notice. The study reveals that the absolute spread test as a liquidity test, plays a vital role in rulingadaylongequilibriummotionofdailystockreturnsinIndianmarket. SirineChekililandNadiaAbaoub,(2013)Thisstudypublishedtoshowthepresenceoftheliquiditypremiumpaid. Data hasbeen collected fromTunisian stock Exchange and Twentylisted securitieshasbeen taken as samplesize. The period of the sample size is twenty-four mounts from January 2003 to December 2004. The Martinez Nieto, RubioandTapia2005modelhasbeenusedtoexaminetherelationshipamongliquiditypremiumandstockreturns. wedecided that theBid-ask spread is ascale ofliquidityin the Tunisian marketbut therotating ratio is a scaleof liquidity.TherecentscaleofAmihud(2002),isaworthlesstooltoscaletheTunisianmarketandliquiditypremium isn’tdistributethemonthofJanuary. ChengFanFahandAnnuarNasir,(2011)Thisstudyfindtheeffectoffinancial, marketandpriceriskson theERC (Earning Response Coefficients) for Commercial Banks in china. They use the collective abnormal returns (dependent) and the unexpected earning (independent) variables. It showsthat: i) Have asolid relation ofReturns-to-Earningswithbanks;ii)TheliquidityriskhasinformationcontentintheReturns-to-Earningsrelation. IsaacMwaurah, WillyMuturi and AnthonyWaititu,(2017) Thisstudyinvestigatesthe inspiration of financial risk on stock returns. Annual data of 9 banks listed from 2006 to 2015 has been used. Stock returns (dependent) and credit,market,liquiditypluscapitalrisks(independent)andbanksize(controlandmoderator)variablesweretaken. Theyassumedamultivariateleastsquareregressionmodelingandabsorbedtwo-dimensionregression.i) Individual impact of financial risk on Stock Returns. ii) collective multivariate impact of financial Risk on Stock Returns. Individualregressionofcredit, market,liquiditypluscapital risksshowastatisticalsignificantpositiverelationship withStockReturns.Collectivemultiple(GLS)regressionoffinancialriskwithacontrolvariablespecifiedfinancial risk is negatively -significant on Stock Returns and bank size had a positive significant effect on stock returns. Moderatingeffectofbanksizeontheinfluenceoffinancialriskonstockreturnswasfoundpositivelysignificant. Shaun A.Bond and Qingqing Chang, (2013) theyfind the effectof innovations in liquidityon stock-return. Study find a positive low liquidity shock for business which have positive cash flow and expected-return news. The correlationamong liquidityproxiesandstockreturns, rise fromtheassociationofliquidityproxieswiththe3stock return components. Regression of returns on liquidity proxies may minimize or maximize the importance of liquidity with stock-return variance. At the end, liquidity proxies tend to explain stock returns better in negative marketliquidityshocks. Mahdi Salehi, Ghodratallah Talebnia and Behzad Ghorbani, (2011) Current study investigate the relationship between stock returns and liquidity ability in companies, listed in Tehran Stock Exchange. Monthly data for the years2002-2009hasbeenused.Thestudyresultsindicatethatthereisanegativecorrelationbetweenstockreturns andliquidity.Theoutcomesofcurrentstudysupportnegativerelationshippresumptionbetweenstockreturnsandits liquidityability. Waqas Bin Khidmat and Mobeen Ur Rehman (2014) Ten listed chemicalcompaniesofPakistan has been selected and 9 years data ofthese companies from (2001-2009) has been used. Solvency ratio has negative and significant impactonthe(ROA)and(ROE).Itsshowthat the(DTE)ratiogoesupthen firmperformancegoesdown.Itisalso concluded thattheliquidityhas highpositiveeffectoverReturnonAssetsofsector.Stakeholdersalso interested in solvencyratiosof companies.Suppliers check thesolvencyposition of the companiesbefore delivering the goods.
Theinvestors areinterested in solvencyposition to know howmuch thecompanyis risky. Liquidity,solvencyand profitabilityarecloselyrelatedbecause,ifoneofthemincreasestheotheronedecreases.
Thecurrentresearchbasedonthefollowinghypotheses: H1:Thereisasignificanteffectofcreditriskonstockreturns. H1:Thereisasignificanteffectofliquidityriskonstockreturns.
A conceptual framework busy in the study discusses the basis that influence of financial risk on stock returns. The dependent variable in the study includes company’s stock returns while independent variables credit riskandliquidityrisk.Thestudyinvolvedacontrol/moderatorvariableofcompany“size”.
LogofAssets
Doubtfuldebtsto Currentdebts
Independent Variables Control Variable Dependent Variable
InthisstudycreditriskwasmeasuredusingtheratioofDoubtfulDebtstoCurrentDebts.Thismeasureconformsto followingempiricalstudyof(MehriAkhaviBabi,2015).
Saleh (2014) defined liquidity risk as the inadequacy of the liability side of the company that restraints demand deposit and possibly triggers system fragility and company runs. It is the uncertainty that arise when a security cannotbeliquidated in amarketto averta financialloss.Thisstudyadopted funding liquidityriskasameasureby theratioofDebtstoTotalassets(MehriAkhaviBabi,2015).
Berger andBrouwman (2011)determinedthatcompanysizecan beusedas acontrolvariablemeasured as alogof asset base. Theydescribed that companysize ispositivelyrelated to probabilityof survival. This explains that the effectofriskandreturnsincompanyisdeterminedbythestateoftheeconomy.Thisobservationwassupportedby Shariat and Khosvari (2008) who observed that firm size is negatively related to stock returns during periods of financialdifficulties.
Stockreturnisthechangeincapitalorwealthduetoaninvestment.Thechangescouldoccurduetocashflowssuch asearnings,dividendsor interestorduetonegativeorpositivechangesin prices(Mehri,2015).Todeterminestock returns the study employed formula applied by Purnamasari et al. (2012) and Predescu and Stancu (2011) in calculatingthestockreturns:
J. Appl. Environ. Biol. Sci.,8(4)95-102,2018
Introduction
This portion of the research includes the type of research, the sample used in this research and also the different sourcesfromwhichthedataiscollected.Theresearchmethodologyalsodiscussedinthisportion.Thischapteralso includesvariablesoftheresearch.
The study being based on secondary data therefore this study is quantitative in nature and as we are testing a hypothesis therefore a deductive approach being used. As according to Wilson (2010)“A deductive approach is concerned with developing a hypothesis (or hypotheses) based on existing theory, and then designing a research strategytotestthehypothesis.
Population and Sample size
Thepopulation forthe studycomprisesofallthenon-financialcompanieslistedatPSE.Weselected about50 non-financial companies randomly from the said population for the study. Moreover, we selected those non-financial firmswhosedataforthestudyperiod(2010to2015)wereavailable.
Thisstudybasedonthesecondarydatafortheincludedvariablesanddatacollectedfromthefollowingwebsites: 1.OfficialwebsiteoftheStateBankofPakistan(Balancesheetanalysis) 2.Opendoorsforall.com 3.AnnualReportsoftheselectednon-financialfirms
Thedatacollected fromcompanies’annualreports.TheindexpricecollectedfromthePakistanstockexchange.The closing prices of the stock return’s taken and calculated by log of today by previous returns. The log returns calculatedbytheformula.
RT=ln(P1/Po)
RT=representsthereturn
P1=representstheclosingpriceonthegivenday
Po=representstheclosingpriceonthedaypreviousP1
Toexaminethecreditandliquidityriskseffectonstockreturns.coveringperiodof6yearsfrom2010to2015.Panel dataused.Thestockreturnofthecompaniescalculatedasfollows
RT=ln(P1/Po) For the annually returns the Rt signify the annual returns, P1 show the closing price on the given year and P0showingtheclosingpriceonthepreviousyeartoP1.
Furthermore,thisstudyanalyzedtoestimatethecreditriskandliquidityrisk.Afterthesecalculations,weregressed creditriskandliquidityriskwithstockreturnofselectedcompanies.
RT=α+β1(CR)+β2(LR)+εt Therearethreedifferenttestmodelsofpaneldata. Common,fixedandrandomeffectmodelsused. To select among common and fixed effect model, “F value” test used. If its value is greater than two we will use fixedeffectmodelotherwisecommoneffectmodelwillused.
Variables
Credit risk This study assessed the ratios for credit risk byDoubtful Debts to Current Debts of the company. (Mehri Akhavi Babi,2015).
Liquidity risk
Thisstudy,measuredtheratiosforliquidityriskbydebttototalassetsofthecompany.(MehriAkhaviBabi,2015).
Company Size Thisstudyassessedtheratiosforcompanysizebylogoftotalassetsofthecompany.(IsaacMwaurah,WillyMuturi andAnthonyWaititu,2017)
Thestockreturnofthecompaniescalculatedasfollows RT=ln(P1/Po)
Thepaneldatasetused inthisstudywhich isacombination oftimeseriesand crosssectiondata.Dataset coversatimeperiod of2010-2015.Weused multipleregressionanalysis.Tousemultipleregression firstof allwe usedappropriatemodelamongthecommoneffectregressionmodelandfixedeffectregressionmodelFstatistictest hasusedtoselectthebestmodelamongthecommon effectregressionmodeland fixed effectregressionmodel.To selectamongfixedeffectandrandomeffectmodel,“Houseman”testwilluse.ifitsresultcomessignificantrandom effectmodelwilluseotherwisefixedeffectmodelwillbeused. First to select model among common effect model and fixed effect model F-value calculated by the following formula.
F={(R2FE--R2CE)/N-1}/{(1--R2FE)/NT-N-K} Where, R2FE =fixedeffectmodelR2
R2
CE =commoneffectmodelR2 N=Numberofusedcrosssections T=Numberofusedtimeperiod K=Numberofusedindependentvariables BycalculatingtheF-valuewith thehelp ofaboveformula,thevalueis5.17,whichisgreater than 2.Thus,thenull hypothesisrejected andalternativehypothesisacceptedthat isfixedeffectmodelused.Nowweused Housman test forusingbestmodelbetweenfixedeffectmodelandrandomeffectmodel. TheresultofHousmantest,asgivenbelow.
Housman Test Summary
Chi-Sq. Statistic | Chi-Sq. d.f | Prob. | ||
---|---|---|---|---|
8.979559 | 5 | 0.1099 |
Dependent Variable = Returns | |||
Independent Variables | Coefficients | t-value | p-value |
Credit risk | -0.001542 | -2.938608 | 0.0036 |
Liquidity risk | 0.00000181 | 0.197803 | 0.0434 |
Size | 0.000482 | 0.948745 | 0.0237 |
R Square | 0.193144 | ||
F-value | 1.137050 | ||
Prob (F-statistic) | 0.258114 |
FromtheaboveresultitisclearthattheP-valueis0.1099whichgreaterthan0.05sotheresultisnotsignificantand weusedfixedeffectmodelfortheanalysis.Theresultsofthefixedeffectmodel,asgivenbelow.
Theabovetablerepresentstheexplanatorypowerofmodelusedwhichare,F-value1.137050,P-value0.258114and R square 19.3144.The coefficient of Credit risk is negative and its value is -0.001542, t-value is -2.938608and Probabilityvalueis0.0036.ThisitshowsthatCreditriskhassignificantbutnegativerelationship with stockreturn of company, it may also have interpreted as unit increase in credit risk brings -0.001542units decrease in stock returnoffirm,remainingotherthingsconstant. The Liquidity risk coefficient is positive and its value is 0.00000181, t-value is 0.197803and Probability value is 0.0434. This result shows that Liquidityrisk has significant positive relationship with stock return of company, it mayalsohaveinterpretedasunitincreaseinsizebrings0.00000181unitsincreaseinstockreturnoffirm,remaining otherthingsconstant.
J. Appl. Environ. Biol. Sci.,8(4)95-102,2018
Ifwe look at the coefficient of Sizewhich is 0.000482which is positive and t-value is 0.948745havingprobability value 0.0237, if we look at these values this shows that Size has positive and significant relationship with stock return of company, we can also interpret these results that one-unit increase in size will bring 0.00000633 units increaseinstockreturnoffirmkeepingotherthingsconstant.
This study conducted on financial risks (Credit risk, Liquidityrisk) on stock return of non-financial firm listed in Pakistan stock exchange. In this paper, we used panel data analysis to measure the relationship between financial risks and stock returns, listed non-financial companies for six-year period. We used two independent variables (credit risk, Liquidity risk) to measure their effect on stock return. The results exhibit that credit risk negatively correlated with stock return of company; though, this relationship is significant. This result is consistent to Mehri akhavi Babi, (2015). Liquidity risk positively correlated with stock return of company but, the relationship is significant.ThisresultisinconsistenttoMehriakhaviBabi,(2015). andSizepositivelycorrelatedwithstockreturn ofcompanybut,therelationshipissignificant.
Thisstudyanalyzedrelationshipbetweenfinancialrisksandstockreturn.itsonlytworiskscreditriskandLiquidity risk. However, the other major risk factors like market risk, capital risk and interest risk are factors of systematic risksandthisresearchstudyconductedbyonlyunsystematicriskfactors.
However,thelimitationofthestudymustbeincludedinthisthisresearch.Myanalysisisbasedonsomelimitation. Thelimitationsaregivenbelow. Thefirstweconsideronlytwofinancialrisks,creditriskandliquidityrisk. Second refer to the fact that the research is only based on Pakistan which is a developing country. In previous literaturessome researchers studythese relationshipsbased on developed countries. So, their results were different fromthisstudy. This study is conducted in a limited span of time and to check the relationship. After studying the previous researches on correlation of financial risks on stock return especially in my selected sample there was little work being available in which these risks were studied together. Therefore, it could be a new topic for furthermore researchtoanalyzecorrelationinthesekindsofrisks.
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