Mali yapı analizlerinde çok boyutlu modeller
Multi-dimensional models in financial structural analyses
- Tez No: 66735
- Danışmanlar: DOÇ. DR. MEHMET BOLAK
- Tez Türü: Yüksek Lisans
- Konular: Mühendislik Bilimleri, İşletme, Engineering Sciences, Business Administration
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1997
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: İşletme Mühendisliği Ana Bilim Dalı
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 182
Özet
ÖZET Mali yapı analizlerinin doğuşu 1900'lü yılların başlarında gerçekleşmiştir. 1900'lü yıllardan itibaren bu alanda son derece hızlı bir gelişim süreci oluşmuştur. Ekonomik alanda faaliyet gösteren şirketlerin giderek büyümesi, bazı mali kontrol mekanizmalarının geliştirilmesini gerekli kılmıştır. Büyüyen ve gelişen şirketlerin yatırım alanlarının belirlenmesi, bu yatırımları gerçekleştirirken kullanılacak iç ve dış kaynakların temini ekonominin en önemli problemlerinden biri olagelmiştir. Şirketlerin ihtiyaç duydukları fonların temini için veya ellerinde bulundurdukları atıl fonların en iyi şekillerde değerlendirilebilmesi için mali yapılarının ortaya konması ve bir değerleme sürecinden geçirilmesi gerekmektedir. Bu değerleme şirket yöneticilerine doğru kararlan alabilme ve geleceğe yönelik planlama yapabilme imkanları sağlayabilecektir. Şirketlerin koşullar gereği ihtiyaç duyduğu dış kaynakların temininde önemli bir işleve sahip olan kredi kuruluşları açısından da mali analizlerinin vazgeçilmez unsurlar olduğunu söyleyebiliriz. Kredi verilecek şirketlerin doğru olarak belirlenmesi gerek kredi kuruluşları gerekse ekonominin geneli için büyük önem taşımaktadır. Gerçekçi bir mali analiz ile doğru şirketlere kredi verilmesi; kredi kuruluşunun riskini azaltacağı gibi ekonomideki kaynakların verimli kullanılmasını sağlayacaktır. Mali yapı analizlerinin yaygın olarak kullanıldığı diğer bir alan ise sermaye piyasalarıdır. Üretim kesiminin fon ihtiyaçlarının artması, sermaye piyasalarının gelişimini hızlandırmıştır. Ülkemizde de sermaye piyasalarının son dönemde göstermiş bulunduğu büyümenin ivmesi bunun en önemli kanıtıdır. Sermaye piyasalarında işlem yapacak olan yatırımcıların doğru yatırım kararlan alarak doğru seçimleri yapması, başardı olarak hazırlanacak mali analizler ile doğru orantılıdır. Mali yapı analizleri gerek mikro bazda işletmeler için gerekse makro bazda ülke ekonomileri için büyük önem arz etmektedir. Bu önem bu alanda çok fasa süre içerisinde oldukça hızlı ilerlemelerin kaydedilmesini sağlamıştır. Mali yapı analizleri kapsamında çok farklı yöntemlerin geliştirilmesi dikkat çekmektedir. Bu çalışma kapsamında mali yapı analizlerinin önemine değinilmiş ve bu konuda çeşitli araştırmacılar tarafından hazırlanmış çok boyutlu analizler tanıtılmıştır. Daha sonra ise cluster analizi ve dislcriminant analizleri konusunda teorik bilgiler verilmiştir. Çalışmanın son bölümü ise uygulamaya ayrılmış ve bu bölümde İstanbul Menkul Kıymetler Borsası' nda faaliyet gösteren seçilmiş şirketlere cluster analizi ve çok boyutlu analizler uygulanmıştır. VI
Özet (Çeviri)
SUMMARY MULTI-DIMENSIONAL MODELS IN FINANCIAL STRUCTURAL ANALYSES Financial structural analyses are those ones where opportunities in order assess a company's position, results of its business activity and its financial development process; to figure out its positive and negative aspects; to determine the company's development stage in future are obtained. Results of financial structural analyses have significant effects both within and outside the enterprise. The fields where such results have significant effects can be defined as follows: -Managers and All Types of Company's Policies Enterprises that aim at developing and increasing its success should check and take their financial position under control. Thanks to such control the companies will be able to determine their advantageous and disadvantageous aspects. Determining their advantageous and disadvantageous allows the company managers to benefit from lots of significant convenience. A subject requiring due emphasis in particular is to carry out the necessary changes in long-term planning of the enterprise on time. Financial structural analyses yield many benefits when they are performer in a correct an consistent form and within regular intervals. Thus the problems likely to occur in the following terms can be identified furthermore solutions for such problems can be figured out beforehand. In fact financial position analyses undertake such an assignment of warning for the enterprises. If the company is able to detect an existence of deterioration in company's position then it will be able to take necessary cautions and measures. -Investment Analyses It is known by many that the correlation between failure of an enterprise and movement of its stock prices is really high. Many researches carried out regarding this subject have revealed that such a correlation exists. Such researches carried out about this subject proved that markets are extremely sensitive against financial failure risks. When the companies whose stocks were traded in the stock market became unsuccessful financially decreases in their stock prices VUgained acceleration. II is revealed in the studies performed that the price-declining trends increases during the period one year prior to bankruptcy, a consequence of financial failure. The result obtained from these researches and studies suggesting that markets are likely sensitive to risks of bankruptcy is very important one, however, it is a fact that such result itself is not a sufficient indicator. Predicting bankruptcy possibilities, in particular, for foreign markets accurately will both allow to be protected against possible losses and to obtain large profit figures at high amounts through short sales. Using financial structural analyses in investment objectives is necessary not only for institutional and small-scaled investors but also for existing or future shareholders or the ones providing long-term or short-term funds to the enterprise. Another utilization area where financial structural analyses are used widely rating studies. The rapid development process experienced in capital markets during the recent period have increased the need to make those enterprises activating in such markets subject to rating procedures. In other countries there are many rating institutions making business. As it is mentioned before such rating institutions perform assessments on the country basis and furthermore they evaluate enterprises that operate in such capital markets. In USA; Japan and European countries many rating institutions operate under this aim. It is really a shortcoming for us that there is no such institution operating within our country. Confidence which is the most significant component in capital markets will increase as soon as such institutions begin to operate in Turkey. Thus both investors and companies will obtain many advantages. -Loan Analyses Financial institutions providing loan to a enterprise and other enterprises having commercial relations with such enterprise should have necessary information about the enterprise to whom they are creditors. The information about the financial position of the enterprise and its reserves for efFecting payments can be only obtained through financial structural analyses. The relation between fund suppliers and fund demanders has a significant place within economic activities. Bank institutions, in particular, have a significant function for establishing such relations therefore they should analyze demands for credits in a very sound manner. When any bank makes wrong assumptions and evaluations regarding credit claims this will lead to important losses for both the bank and state economy. If any bank assesses any company that is on the verge of bankruptcy due to its financially unsuccessful position as one without any risk and supply it with loan or misjudges a hugely successful enterprise about its financial position and refuse to provide it with loan this will very likely be a cause for huge losses. Thus institutions supplying loans and credits should use financial structural analyses in order to avoid such wrong decisions. -Auditing MilAs it is known financial structural analyses are realized based on the financial statements of the companies. Therefore it is very important that such statements used in financial structural analyses should reflect the actual figures. It is the duty and task of an auditor to discover whether such statements on which financial analyses depend on, reflect the actual position or not. We can classify the auditing in two; namely, internal auditing and external auditing. Many sectors get benefit from the reports prepared by the external auditors. Enterprise's partners, managers, investors who invest in company's stocks or debenture bonds and credit institutions that either provided or will provide loans to enterprises are mainly among those who benefit from the said reports. Therefore auditors has significant liabilities and responsibilities in auditing. In order to master such responsibilities auditor should observe discernment between financially successful and financially unsuccessful companies very well. Financial structural analyses require in order to carry out such discernment. The facts that there is a rapid increase for the need to the information revealed as a consequence of financial analyses; financial analyses techniques processing such data develop day by day and financial analyzing models that have been developed proved that they are largely reliable for the predictions towards future actions will lead in keeping the development process observed in this field to gain acceleration. In order to obtain reliable results from financial structural analyses some elements should be provided. Likely errors may result in unrecoverable losses while, on the other hand, a successful and sound financial structural analyses may yield extremely important benefits to the persons or institutions that have realized such analyses. Therefore it should be kept in mind that financial structural analyses require very serious and circumspect studies from the initial stage to the last phase. We can list the characteristics requiring for any financial structural analyses as follows: -Preparation of financial statements in sound manners and securing that information taken as a basis for the analyses reflect the actual figures. -Securing that persons who will perform financial analyses should have sufficient experience and knowledge. -It is essential that the ones carrying out such analyses should be very aware of legal frames concerning the company's business operations. -It is important that the sector where company makes business should be known and investigated well. -It is important to be well informed about economic characteristics of the period through which financial structural analyses are realized. -It is important to be aware of the policies applied by the companies subject to financial analyses. -Experience of the experts performing financial structural analyses. IXIn text section of the thesis study currently being written information is provided about definition of financial structural analyses and its components and models with multi-variables used in financial structural analyses are described. The last section of thesis study is provided for practices. In practice section a different approach is taken to financial structural analyses with cluster analysis, discriminant analysis, multi-regression analysis and logit model analysis. Results obtained from the practice studies can be grouped into two. The first one concerns the results of cluster analysis. 53 companies whose stock are currently being negotiated in Istanbul Stock Exchange and have sufficient representing power in trading volume are involved in practice studies. During the conduct of cluster analysis financial ratios which were calculated beforehand are used. In calculation of financial ratios balance sheet and income statements. The aim of cluster analysis is to be able to classify the companies subject to analysis by certain criteria because discriminant analysis, multiple-regression analysis and logit model analysis considered to be applied in the second section of the study require to classify 53 companies. As it is known here bankrupt companies are not included in the description of unsuccessful companies as we did in our studies we put forward as examples in text part. As per Ward's method yielding the best classification as a result of various cluster analysis methods applied to 53 units subject to analysis, cosine similarity solution was selected. According to this solution the categories in which the companies are classified were identified. Following the cluster analysis 53 companies were divided into two separate groups. After this stage of the study it required to identify these two different groups. It is essential that we have to define the characteristics of categories called by us as Group 1 and Group 2. Therefore among the statistical“t”test was applied and common characteristics of categories were tried to be identified. As a consequence of such analysis each ratio was arranged in order of their significance and general characteristics of categories were tried to be put forward. After financial ratios were arranged in order of their significance by“t”test it was identified that the factors determining the differences between the categories are cash ratios, indeptedness ratios and profitability ratios. As a result of these analyses carried out it was figured out that the companies in group 1 are in better conditions when compared to the ones in group 2 regarding their profitability position, liquidity position and indeptedness position. Following these studies companies in group 1 are identified as (+) groups with respect to their financial performance and the ones in group 2 (-) ones. It was discovered that certain companies within the same category have certain different characteristics than the other ones. Since such findings are related to some disadvantageous points involved in cluster analyses mentioned in text part there was no change or modification upon classification solution.After classification studies were completed multi-dimensional modeling analyses were started to be applied in the second section of practice studies. In this section of multi dimensional models discriminant analysis, multiple regression analysis and logit model analysis were used. Aim applying in such analyses is to determine the method which will yield the best result. A certain sampling were selected from 53 companies that are subject to analysis in the first stage of this analysis, the remaining ones were decided to be used as test objects. Therefore 13 companies which were randomly selected from 53 companies were held out of test and 40 companies were included in the analysis. In the first stage of the study where discriminant analysis was applied in the first round canonical discriminant function was obtained through stepwise variable selection. Preliminary possibilities for each group was taken as 50%. The following equation was observed as a result of discriminant analysis: Z= -1.6354224+5. 124301*X8+4.7050416*Xn-13.8082939*X20+3.8918704*X27- 6.8886140*X2»+2.7540924*X* This equation classifies 40 companies included in practice group with an accuracy by 97.5%. As to for 13 companies excluded from practice group it was found out that they were classified with an accuracy by 92.3% in discriminant analysis. These results prove that discriminant analysis which was carried out here yield extremely accurate results. The following equation was observed as a result of multiple-regression analysis: Z= -0.3 14536+1.045560*X*+1.405788*Xw+O.961077*Xıı- 2.817916*X2o+0.79423*XJ7+0.562039*X36 The accurate classification ratio of 40 companies handled was found to be 97.5% in multiple-regression equation, same percentage as the one in discriminant analysis. Prediction success of multiple-regression equation for 13 companies which identified as test group was found to be 92.3%. For 13 companies which were excluded from practice groups it was found that prediction success for multiple-regression analysis and discriminant analysis were exactly the same. As a result of these findings it was determined that multiple-regression model yield very successful results over the examples subject to analysis. The following equation was observed as a result of the logit model analysis: Z=-0.8090-4.0984*X2-34.6581*X20+9.7814*X36 XIThe accurate classification ratio of 40 companies subject to analysis according to logit equation was found to be 90%. For 13 companies to be determined as test group the success of equation was 84.6%. It is obvious that logit model yields successful results in the handled sampling. However, prediction success ratio in logit model was found to be lower in both 13 companies excluded from practice group and 40 companies included within test when compared to discriminant analysis and multiple-regression analysis. In the last stage of practice study another 13 companies among 53 companies which were taken into practice were excluded from study group and the same analyses were conducted upon 40 companies formed newly. Thus practice were held subject to test for the second time. Criteria for eliminating 13 companies was determined to be putting much emphasis on the companies classified as (-) in practice studies. As a result of the analyses performed the following equations were observed: Discriminant Function: Z= 0.43 16523+0.901 8855*X2+1 1.1 57973 1*X^1. 46377792*X27- 2.7343532*XM+0.0245427*X
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