Extracting Common Factors to Classify Companies Listed in the Stock Exchange of Thailand by Using an Accounting Based Model

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1 Extracting Common Factors to Classify Companis Listd in th Stock Exchang of Thailand by Using an Accounting Basd Modl Krisada Khruachal Faculty of Businss Administration, Siam Tchnology Collg, Thailand Abstract - Th objctiv of this study is to classify th company listd in th Stock Exchang of Thailand by applying th Principl Componnt Analysis (PCA) to ovrcom th multicollinarity problm in th purpos of xtracting th common factors usd in th Logistic rgrssion modl. Th data st ar gathrd from th companis annual financial statmnts rgistrd in th Stock Exchang of Thailand sinc 2002 to Th data st consists of 101 companis which thr ar only 29 distrssd companis that hav bn dfaultd on corporat bonds and thr ar 72 non-distrssd companis that hav not bn dfaultd on corporat bonds. Th logodds scor ar calculatd basd on th prdictd dfault probability gnratd from th Logistic rgrssion whos variabls ar intgratd with th 4 statistically significant common factors. Ths scors ar usd to classify th company s risk lvl. Th ovrall accuracy of th prdictd modl is 92.3% which w can group th companis dfault probability into 5 diffrnt catgoris as vry good, good, rathr good, rathr not good, and not good with a crdit scor blow 475, , , , and abov 570 rspctivly in ach of which th prcntags of companis containd in ach catgoris ar 58.42, 12.87, 4.95, 8.91, and rspctivly. Kywords - Principl Componnt Analysis, Financial Ratio, Extracting, Classifying I. INTRODUCTION Th xposur to crdit risk is considrd as a significant sourc of srious problms for both financial institutions and companis spcially whn conomic rcssion has bn discovrd. With th dvlopmnt of mthodologis usd in ordr to captur th volatility of th companis assts valu to th prospctiv losss, th vital protctiv stratgis to mitigat risk has bn promptly implmntd to minimiz th harmfulnss of company failur in th futur. Th gnral information to b usd as th valuatd risk factors is normally th company financial position which usually gathrd from thir financial statmnts. Dspit th important of company financial statmnts, thr ar many studis applid th financial ratios as th prdtrmind factors in ordr to valuat th company s dfault probability, this is widly known as th accounting-basd modl. Howvr, thr ar also som crucial limitations that th accounting-basd modl cannot fully captur th total variation of company s assts valu. In addition, th financial ratios usd in th accounting-basd modl ar intrnally rlatd with ach othr. Thrfor, it will caus a multicollinarity problm whn prforming th analysis of rgrssion. With ths issus, th valuations of th accounting-basd modl ar tratd as an infrior modl. In addition, th modl will also provid spurious rsults. 58

2 Krisada Khruachal In this study, w try to improv th prformanc of th accounting-basd modl in assssing th dfault probability by applying th Principal Componnt Analysis (PCA) to ovrcom th fundamntal problm of multicollinarity in th variabl slction procss. To customiz th gnral usrs, w will convrt th dfault probability calculatd from th accounting-basd modl modls to a crdit scor by applying th log-odds scoring procss. II. LITERATURE REVIEWS With th important of accounting information rgarding th masurmnt of company s markt xposur, [1] rviwd th rlationship btwn th accounting information and th markt risk xposur. Thy concludd that th accounting information gathring from th accounting statmnts formativly rlatd to th markt risk indicators. Thrfor, th us of accounting statmnts could stimat th xposur of unlistd scuritis as wll as rating company dfault probability. Th volution of crdit scoring modl obviously startd from th dvloping of [2] that applid th financial ratios calculatd from th accounting statmnts of both th bankruptcy companis and th normally opratd companis. Ths companis information wr gathrd from Moody s Industrial Manual btwn th yars of 1954 to Th avrag of ach financial ratio had bn compard btwn normal and bankruptcy firms by applying th univariat analysis. Ths sampls ar no diffrnc in th companis charactristic in trms of siz and industry. Th ovrall rsults rvald that th ratio analysis providd a grat contribution to xplain th company s failur 5-yar in advanc. Howvr, ach financial ratio was unqually abl to illustrat th company s failur. Thy found that th ratio of cash flow to total liabilitis prformd th bst in dscribing th company s failur. W obviously saw from many litraturs that th study of [3] has oftn bn usd to dvlop th classification modl which usually applid th tchniqus of multipl discriminant analysis. It is typically calld Z-Scor Modl that th Logistics rgrssion analysis was implmntd. This modl mainly usd th financial accounting ratios as a tool to classify th company dfault probability. This modl accuratly forcastd th company s failur 1 yar in advanc with 95% of total sampl. Howvr, th accuracy would di down to 83% whn th modl forcastd th company s failur 2 yar in advanc. Th framwork of [3] has oftn bn dvlopd in ordr to match with th gnral nvironmnt of company s failur and countris spcific. In Thailand, th mpirical study of [4] trid to xamin th modl of [5] whos modl usd to charactriz th companis failur in an mrging markt. In addition, th stimatd dfault probabilitis from th logistic rgrssion quation wr usd to calculat th log-odds crdit scor in ordr to classify th company s risk lvl. Th rsults rvald that thr wr only two variabls applying in th Altman s modl, whr thr wr th ratios of rtain arnings to total assts and th ratio of arnings bfor intrst and tax to total assts. Ths two variabls wr statistically significant at Th ovrall accuracy of th modl was 93.84% by classifying th companis into 5 groups with crdit scors as vry good, good, rathr good, rathr not good, and not good rspctivly. Unfortunatly, th study of [6] claimd that th financial ratios usd in th accountingbasd modl intrnally rlatd with ach othr which it will sriously caus a multicollinarity problm. Thrfor, th valuatd rsults from accounting-basd modl wr considrd as spurious rsults which it was tratd as an infrior modl. Thr ar many studis that proposd th mthod to solv th multicollinarity problm for xampl th study of [7] that dtctd th multicollinarity by applying th mthod of obsrving corrlation matrix, varianc influnc factor, and ign-valus of th corrlation matrix. Thir rsults found that th mthod of Principl Componnt Analysis (PCA) could b usd to amnd th multicollinarity problm. 59

3 III. RESEARCH OBJECTIVES Th intnts of this study ar to construct a classification modl and prscinc th company s dfault probability applying th xtnsion of logistic rgrssion analysis tchniqu proposd by [3]. In addition, w will mploy a larg amount of th financial accounting ratios that calculatd from th company s accounting statmnts. Ths ratios ar covrd th ratios masuring th company s liquidity, fficincy, profitability and lvrag. IV. CONCEPTUAL FRAMEWORK As w focus closly mor on rvamping th accounting-basd modl in assssing th dfault probability of th companis listd in th Stock Exchang of Thailand, w would gathr th accounting information from th company s accounting statmnts and calculat th financial ratios usd in th Logistic rgrssion modl. Extracting Common Factors to Classify Companis Listd in th Stock Exchang of Thailand by Using an Accounting Basd Modl In ordr to gt rid of th multicollinarity problm, th Principl Componnt Analysis (PCA) has bn usd to xtract th common componnts in th accounting-basd modl. Dpndnt Variabl: Th vnt whr th company has bn dfault ( y 1) on th corporat bond and th vnt whr th company normally oprats ( y 0). Indpndnt Variabls: Th financial ratios calculatd from th company s accounting statmnts which ach valu was idally assumd to captur th bhaviour of company s liquidity, fficincy, profitability and lvrag. V. DATA This mpirical study has bn conductd to covr th priod of January 2002 to Dcmbr 2016 which is ovr 14 yars of study. Th population of this study is th companis listd on th Stock Exchang of Thailand which usd to rais fund by issuing a corporat bond sinc January 2002 to Dcmbr Howvr, thr ar only 29 companis during this priod that hav bn dfault on corporat bonds. Thrfor, w would considr all th dfaultd companis in th modl construction procss for incrasing th prcision. Fig. 1 Th Concptual Framwork of Classifying th Companis Dfault Probability In ordr to construct th classification modl, th normally opratd companis hav bn randomly slctd from list of th Stock Exchang of Thailand postd on th wbsit by using a simpl random sampling. As rsults, th slctd sampl comprisd of 101 companis listd in th stock xchang of Thailand which particularly consists of 29 distrssd companis and 72 non-distrssd companis. Th monthly company s annual financial statmnts and thir ky financial ratios masuring th company s liquidity, fficincy, profitability and lvrag hav bn calculatd to b th indpndnt variabls for th prdictiv Z-Scor modl. Th data st has mainly downloadd from th Datastram program and th wbsit of th Scuritis and Exchang Commission, Thailand (SEC) which thy ar all publicly availabl. 60

4 Krisada Khruachal VI. RESEARCH METHODOLOGY In ordr to xtract th common factors, lt th variabl x dnots th panl of financial ratios changs which Cov( x) xx ' dnots th covarianc matrix of th financial ratios changs. Th common factors xtractd from th panl of financial ratios can b calculatd from 1/2 x v F F whr; v dnotd th matrix whos columns ar th ignvctors of Cov( x ). 1/2 dnots th diagonal matrix whos lmnts ar th squar-roots of th ignvalus. dnots th vctors of principal componnt loadings, or factors loadings which can 1/2 also b illustratd as v. F dnots th vctor of principal componnts. Estimating th paramtrs to assss th dfault probability, th logistic rgrssion analysis has bn mployd incorporating with th common factors xtractd from th data st of company financial ratios. g x F F F ( ) n n Th numbr of common factors is basd on th first common factors that can xplain at last 90 prcntag of th total variation of th panl of all financial ratios. Th stimation of company s dfault probability can b calculatd as follow; P y 1 g( x) 1 g( x) g( x) To frindly customiz th gnral usrs, th log-odd scor has bn mployd to convrt th dfault probability to b a crdit scor. P y 1 g( x) Log odds Scor ln P y 0 g( x) Ranking th scor basd on th dfault probability, w can calculat as follow; Crdit Scor Log odds Scor Th company whos crdit scor is largly gratr than 500 is thortically considrd as a highst dfault probability. For thos company whos crdit scor largly lss than 500 is thortically considrd as a lowst dfault probability (Good Company). VII. EMPRIRICAL RESULTS A. Extracting th Common Factors from th Data St of Accounting Ratios Applying th principl componnt analysis to xtract th common factors from a data st of various typs of th financial ratios, w slctivly hav 10 common factors that can captur at last 90 prcnt of th total variation of a data st, which th prcntag of th first 10 th ignvalu that can xplain th variation of th data st ar sortd in dscnding ordr shown in th Tabl I, whr th prcntag of xplanation can b calculatd as follow; n Explaind D Di 100 i1 TABLE I THE PERCENTAGE EXPLAINED BY THE FIRST 10 TH COMMON FACTORS Common Factor Explaind (%) Common Factor Explaind (%) B. Estimating th Paramtrs Usd in th Logistic Rgrssion Modl Aftr w applid th first 10 th common factors and th dtrmind vnts in th logistic rgrssion modl to stimat th paramtrs, w found that only th first 4 61

5 common factors, which ar th 1 st, 2 nd, 3 rd, and 10 th, ar statistically significant at Thrfor, w slctivly applid only th first 4 common factors in th classification modl to classify th company s probability of dfault which can b illustratd as. gˆ( x) F 2.379F 4.703F 2.639F Extracting Common Factors to Classify Companis Listd in th Stock Exchang of Thailand by Using an Accounting Basd Modl TABLE II NUMBER OF COMPANY CLASSIFIED BY THE LOGISTICS REGRESSION MODEL BASED ON THE COMPANY STATUS Obsrvd Prdictd Company s Status* Company s Status Dfault Non-Dfault Dfault 22 3 Non-Dfault 2 38 Ovrall Prcntag 92.3 *cut off point at 0.5 Analysing th classification modl with 4 statistically significant common factors, w found that th Nglkrk R-Squar and th Cox & Snll R-Squar ar 90.7% and 66.8% rspctivly, which thy ar considrably high lvl of xplanation. Accordingly, w can imply that 66.8% of th total variation of th financial ratios data st can b xplaind by th Logistic rgrssion with 4 statistically significant common factors. In addition, th Chi-squar of Hosmr and Lmshow Tst, which it is usd to tst th suitability of th prdictd modl, showd th P-valu at This valu is considrably gratr than th statistical lvl of significant 0.05 which w can imply that th prdictd modl with th 4 statistically significant common factors suitably classify th dfault probability for companis listd in th Stock Exchang of Thailand. According to th modl s suitability rsults tstd abov, w can calculat th company s dfault probability as th following quation; P y 1 gˆ ( x) 1 gˆ ( x) gˆ ( x) Following th procdurs in ranking th company basd on thir dfault probability, w can obtain th company s crdit scor from ths quations; P y 1 gˆ ( x) Log ˆ odds Scor ln P y 0 gˆ ( x) Crdit ˆ Scor Log ˆ odds Scor Tru positiv rat (rcall) = 0.88 Tru ngativ rat = 0.95 Fals positiv rat = 0.12 Fals ngativ rat = 0.05 Analyzing th modl accuracy, w found that th ovrall accuracy of th prdictd modl is 92.3% (60/65). Morovr, th obsrvd 25 companis that usd to dfault on corporat bond can b corrctivly classifid by th prdictiv modl with 88% (22/25) of accuracy (22 companis). On th othr hands, th obsrvd 40 companis that normally oblig on corporat bond can b corrctivly classifid by th prdictiv modl with 95% (38/40) of accuracy (38 companis). TABLE III THE PERCENTAGE AND NUMBER OF COMPANY LISTED IN THE STOCK EXCHANGE OF THAILAND CLASSIFIED BY THE CREDIT SCORE Scor No. of Critria Rang Company % > 570 Not good Rathr not good Rathr good Good < 475 Vry good Total 101 To rat th company basd on th crdit scoring procss, w can group th companis into 5 diffrnt catgoris which ar dfind th crdit scors as vry good, good, rathr good, rathr not good, and not good with crdit scor blow 475, , , , and abov 570 rspctivly in ach of which th prcntags of companis containd in ach catgoris ar 58.42, 12.87, 4.95, 8.91, and rspctivly. 62

6 Krisada Khruachal VIII. DISCUSSION AND CONCLUSION This study xamins th implication of th Logistic rgrssion modl whos variabls ar applying th bnfit of th Principl Componnt Analysis (PCA) in an xtracting th common factors from a larg data st of th financial ratios. W found from th mpirical rsults that thr ar only 4 statistically significant common factors that can xplain at last 90 prcnt of th total variation of th data st which comprisd of both dfaultd and non-dfaultd companis listd in th Stock Exchang of Thailand. Applying ths 4 statistically significant common factors and th dtrmind vnts to stimat th company s crdit scor via th logistic rgrssion modl, th ovrall accuracy of th prdictd modl is 92.3% which w found that th total obsrvd 25 companis, who usd to dfault on corporat bond, can b corrctivly classifid by th prdictiv modl with 88% of accuracy (22 companis). Morovr, th obsrvd 40 companis that normally oblig on corporat bond can b corrctivly classifid by th prdictiv modl with 95% of accuracy (38 companis). By applying th crdit scoring procss calculatd by th log-odds scor, w can group th companis dfault probability into 5 diffrnt catgoris as vry good, good, rathr good, rathr not good, and not good with a crdit scor blow 475, , , , and abov 570 rspctivly in ach of which th prcntags of companis containd in ach catgoris ar 58.42, 12.87, 4.95, 8.91, and rspctivly. With ths constructiv rsults, th xtracting mthod which is th principl componnt analysis intuitivly provids a grat contribution to a classification modl which is th Logistic rgrssion modl in classifying th company s dfault probability for th companis listd in th Stock Exchang of Thailand. REFERENCES (Arrangd in th ordr of citation in th sam fashion as th cas of Footnots.) [1] Watts, R.L. and Zimmrman, J.L. (1986). Positiv Accounting Thory. Nw Jrsy: Prntic-Hall. [2] Bavr, W.H. (1966). Financial Ratio as Prdictor of Failur. Journal of Accounting Rsarch, Vol. 4(3), pp [3] Altman, E. (1968). Financial Ratios, Discriminant Analysis and th Prdiction of Corporat Bankruptcy. Journal of Financ, Vol. 23(4), pp [4] Krisada, K., Vichit, L., and Jirawan, J. (2001). Classification of Companis Listd in Stock Exchang of Thailand by Using Logistic Rgrssion Analysis. Burapha Journal of Businss Managmnt, Vol. 5(2), pp [5] Altman, E., Hartzll, J., and Pck, M. (1995). A Scoring Systm for Emrging Markt Corporat Bonds: Saloman Brothrs High Yild Rsarch. Nw York. [6] Shumway, T. (2001). Forcasting bankruptcy mor accuratly: A simpl hazard modl. Journal of Businss, 74, pp [7] Alibuhtto and Piris (2015). Principl Componnt Rgrssion for solving Multicollinarity Problm. Confrnc Procding on th 5 th Intrnational Symposium 2015, SEUSL. 63