<p><strong>Datum: </strong>2009-06-02</p><p><strong>Nivå: </strong>Magisteruppsats i ekonomistyrning, 15 hp</p><p><strong>Författare</strong>: Charlotta Lind och Martin Sloberg</p><p><strong>Titel: </strong>Ditt företag kan inte förutse konkurs -kan Z-score?</p><p><strong>Handledare: </strong>Esbjörn Segelod</p><p><strong>Problem: </strong>Våra forskningsfrågor är:</p><ul><li>Går det att förutse konkurs tre, fyra respektive fem år innan</li></ul><p>          konkursbeslutet?</p><ul><li>Vilka av den senaste Z-scoremodellens fyra nyckeltal är viktigast vid</li></ul><p>           prognostisering av konkurs?</p><p><strong>Syfte: </strong>Att testa i vad mån Z-scoremodellen kan användas för att förutse konkurser</p><p>bland icke börsnoterade, icke tillverkande företag tre, fyra respektive fem år</p><p>innan konkurs; samt att undersöka vilka av denna modells inbördes nyckeltal</p><p>som är viktigast vid predicering av konkurser.</p><p><strong>Metod: </strong>Vi har genom kvantitativ metod analyserat årsredovisningar från 51 företag</p><p>som gått i konkurs 2008, dessa utgjorde vår huvudundersökningsgrupp och 29</p><p>slumpmässigt utvalda företag, vilka utgjorde vår kontrollgrupp. Analysen</p><p>skedde genom användandet av Altmans vidareutvecklade modell för att</p><p>förutspå konkurser från år 1995. Totalt analyserades på detta sätt 240</p><p>årsredovisningar.</p><p><strong>Slutsats: </strong>Modellens träffsäkerhet för de undersökta konkurs företagen var</p><p>2003 45,09 %</p><p>2004 47,05 %</p><p>2005 54,90 %</p><p>Vid hypotesprövning kunde vi endast för år 2005 påvisa samband för</p><p>företagsklassificeringsfrekvenser mellan konkursföretagen och</p><p>kontrollgruppen, detta gör att modellens prognostisering bör anses alltför</p><p>osäker tidigare än tre år innan konkurs. Mot bakgrund till de påvisade</p><p>träffsäkerheterna för åren och hypotesprövningarna anser vi att modellen</p><p>endast bör användas i kombination med andra analysformer .</p><p>Sammanfattningsvis är Z-scoremodellens prognostiseringsförmåga för svag att</p><p>självständigt förutse konkurser.</p><p><strong>Sökord: </strong>Konkurs, Z-score</p> / <p><strong>Date:</strong> 2009-06-02<strong> </strong></p><p><p><strong>Level:</strong> Master thesis in Management Accounting, 15 hp</p><p><strong>Authors: </strong>Charlotta Lind and Martin Sloberg</p><p><strong>Title: </strong>Your company cannot predict bankruptcy;- can Z-score?</p><p><strong>Tutor: </strong>Esbjörn Segerlod</p><p><strong>Our problem questions:</strong></p></p><ul><li>Is it possible to predict a bankruptcy three, four or five years before</li></ul><p>           the adjudication of bankruptcy?</p><ul><li>Which one of the four keyratios in the Z-scoremodel is the most</li></ul><p>          important when predicting a bankruptcy?</p><p><p><p><strong>Purpose: </strong></p><p>To test if the Z-score model can be used to predict bankruptcy for</p></p></p><p>private own companies three, four or five years before the</p><p>adjudication. To get knowledge which one of the key ratios is most</p><p>important when predicting a bankruptcy?</p><p><p><p><strong>Method:</strong></p>Through a quantitative study of Altman's Z-score model has 51</p></p><p>bankrupt companies, 29 control companies and 240 annual reports</p><p>been analyzed.</p><p><p><p><strong>Conclusion:</strong></p>The Z-score model's accuracy for the studied bankrupt companies</p></p><p>is:</p><p>2003 45,09 %</p><p>2004 47,05 %</p><p>2005 54,90 %</p><p>Only in 2005 could a relationship between the bankrupt companies</p><p>and the control companies be established through the Z-score model</p><p>tests. This makes the model too uncertain to be used earlier than</p><p>three years before the adjudication of bankruptcy. It is therefore our</p><p>opinion that the Z-score model is too weak to be used by itself but</p><p>should rather be used as a complement with other models to predict</p><p>bankruptcies.</p><p><p><p><strong>Keywords:</strong> Bankruptcy, Z-score model</p></p></p>

Datum: 2009-06-02 Nivå: Magisteruppsats i ekonomistyrning, 15 hp Författare: Charlotta Lind och Martin Sloberg Titel: Ditt företag kan inte förutse konkurs -kan Z-score? Handledare: Esbjörn Segelod Problem: Våra forskningsfrågor är: Går det att förutse konkurs tre, fyra respektive fem år innan           konkursbeslutet? Vilka av den senaste Z-scoremodellens fyra nyckeltal är viktigast vid            prognostisering av konkurs? Syfte: Att testa i vad mån Z-scoremodellen kan användas för att förutse konkurser bland icke börsnoterade, icke tillverkande företag tre, fyra respektive fem år innan konkurs; samt att undersöka vilka av denna modells inbördes nyckeltal som är viktigast vid predicering av konkurser. Metod: Vi har genom kvantitativ metod analyserat årsredovisningar från 51 företag som gått i konkurs 2008, dessa utgjorde vår huvudundersökningsgrupp och 29 slumpmässigt utvalda företag, vilka utgjorde vår kontrollgrupp. Analysen skedde genom användandet av Altmans vidareutvecklade modell för att förutspå konkurser från år 1995. Totalt analyserades på detta sätt 240 årsredovisningar. Slutsats: Modellens träffsäkerhet för de undersökta konkurs företagen var 2003 45,09 % 2004 47,05 % 2005 54,90 % Vid hypotesprövning kunde vi endast för år 2005 påvisa samband för företagsklassificeringsfrekvenser mellan konkursföretagen och kontrollgruppen, detta gör att modellens prognostisering bör anses alltför osäker tidigare än tre år innan konkurs. Mot bakgrund till de påvisade träffsäkerheterna för åren och hypotesprövningarna anser vi att modellen endast bör användas i kombination med andra analysformer . Sammanfattningsvis är Z-scoremodellens prognostiseringsförmåga för svag att självständigt förutse konkurser. Sökord: Konkurs, Z-score / Date: 2009-06-02 Level: Master thesis in Management Accounting, 15 hp Authors: Charlotta Lind and Martin Sloberg Title: Your company cannot predict bankruptcy;- can Z-score? Tutor: Esbjörn Segerlod Our problem questions: Is it possible to predict a bankruptcy three, four or five years before            the adjudication of bankruptcy? Which one of the four keyratios in the Z-scoremodel is the most           important when predicting a bankruptcy? Purpose: To test if the Z-score model can be used to predict bankruptcy for private own companies three, four or five years before the adjudication. To get knowledge which one of the key ratios is most important when predicting a bankruptcy? Method: Through a quantitative study of Altman's Z-score model has 51 bankrupt companies, 29 control companies and 240 annual reports been analyzed. Conclusion: The Z-score model's accuracy for the studied bankrupt companies is: 2003 45,09 % 2004 47,05 % 2005 54,90 % Only in 2005 could a relationship between the bankrupt companies and the control companies be established through the Z-score model tests. This makes the model too uncertain to be used earlier than three years before the adjudication of bankruptcy. It is therefore our opinion that the Z-score model is too weak to be used by itself but should rather be used as a complement with other models to predict bankruptcies. Keywords: Bankruptcy, Z-score model

In this thesis presents the results obtained in the treatment of the topic The Creation of an Internal Control System in the select company. The Internal Control System is examined from the perspective of the COSO model which evaluates the quality of the internal control at various levels in the company. On the survey of the disertation are valorized risk areas of the company. There are also proposed individuals suggestions for the solutions of the risk areas including the draft internal regulation. The company was also investigated using Altman's Z-Score model that evaluated its financial health.

Holocene climate likely influenced prehistoric hunter-gatherer subsistence and mobility as changing climate patterns affected food resources. Of interest here is whether climate-driven resource variability influenced peoples in the central Rocky Mountains. This study employed the z-score model to predict how foragers coped with resource variability. The exercise enabled exploration of the relationship between climate, resources, and foraging strategies at High Rise Village (48FR5891), an alpine residential site in Wyoming's Wind River Range occupied between 2800-250 cal B.P. The test was applied to occupations dating to the Medieval Warm Period (1150-550 cal B.P.) and the Little Ice Age (550-100 cal B.P.). Using regional characterizations of temporal variability for these climate periods, a z-score model was employed to develop predictions of how foragers coped with resource variability and predictability during both periods. The model predicted foraging decisions at High Rise Village that managed the risk of caloric shortfall during the slow-changing Medieval Warm Period and the highly variable Little Ice Age. Predictions for each period were tested against corresponding archaeological expectations for subsistence remains, mobility and technology requirements, and the frequency of site use. Further, this study employed a dendroclimatological study to locally characterize the climate periods and test model assumptions of their contrasting patterns of variability. The dendroclimatological study corroborates model assumptions and finds that the Medieval Warm Period was a period of multidecadal climatic variability and resource predictability while the Little Ice Age was characterized by short-term variability and resource unpredictability. Poor preservation of subsistence remains hampered the archaeological study. However, as expected, lithic and chronometric data indicate the site was used residentially and relatively frequently during the Medieval Warm Period, and that use decreased during the Little Ice Age. Medieval use of the site appears to be by Uinta Phase (1800-900 cal B.P.) foragers from the adjacent lowlands, and likely related to regional population pressure, as well as resource accessibility and predictability at High Rise Village. A dramatic decrease in site use predates the Little Ice Age and is likely related to regional population decrease and not LIA conditions at High Rise Village.

Purpose: To investigate if Altman´s Z´-score model, which calculates financial distress, can be applied on companies established in Sweden and if the financial crisis in 2008 made previously healthy companies go bankrupt. Methodology: Quantitative studies with a positivistic foundation. Empirical data will be collected in order to examine if there is generalizability among the studied objects. Conclusions will be made by comparing the empirical data with the theoretical foundation. Financial distress in firms will be measured. Theoretical perspectives: Altman´s Z´-score model, designed to predict financial distress in private firms. Empirical foundation: A selection of 93 private firms that have gone bankrupt in the years 2008, 2009 or 2010. The firms selected all have a turnover that exceeds 20 million SEK. The years examined will be 2005 to 2009. Conclusion: As this study is carried out, the conclusion is that Altman´s Z´-score model cannot be applied on companies established in Sweden.

財務報表是投資大眾據以了解企業財務體質的主要來源，然而安隆事件的發生，造成投資人依賴財務報表的信心幾近崩潰。近期國內博達科技公司在財報中有帳列現金63億元情況下，因無法償還即將到期的29.8億公司債，而無預警的向法院聲請重整，爆發財務危機事件，似乎又是一樁企業以虛飾誇大之財務報表，誤導投資人，致使無數投資人損失慘重之案例。究竟財務報表能夠表達的企業營運情況是什麼？我們到底可不可以利用財務報表，即使是經過美化的報表，看出企業有行為不軌的蛛絲馬跡？ 本研究是在傳統財務比率分析方法失效時，打算從另一個角度，尋找企業違約前之徵兆。利用選擇權理論法模型，以及Z-Score模型來檢視博達公司的信用風險，試著以信用風險模型探索其信用危機發生前之警訊。最重要的是，為使一般投資人皆可利用此信用風險模型作為信用風險管理的參考，故所有資料來源均為集中市場公開資訊，不論是股價、各種財務報表及公告資訊，均是利用臺灣證券交易所網站（www.tse.com.tw）中取得資訊。 本研究運用兩種理論模型實證結果，選擇權理論法模型並無出現特別警訊，反而是Z-Score模型結果令人滿意，不論是Altman區別函數，或是替代之「本土型」區別函數計算結果，均在博達公司財務危機事件發生一年前就以區別分數顯示其有財務危機之警訊。甚至針對博達公司倍受質疑的業績灌水、營收虛增問題，調整銷貨收入，並重新代入Z-Score模型後，Z值之預警效果更加提前反映及顯著。

信用評等機構對於企業與市場投資者而言有著重要且無可取代的功能，其所提供之信用評等資訊應當是許多市場投資者所仰賴的重要決策依據，但近年來，卻有許多外界聲浪質疑信評機構評等之準確性，本論文之研究目的即是希望從錨定效應此一行為偏誤之觀點切入，探討國內信評機構在對企業評等時，是否會受到錨定效應影響，導致評等調整不正確或是評等落後其他財務指標等現象發生。 研究結果顯示，國內信評機構對受評企業之過往財務資訊存在錨定現象，但不至於大幅影響整體違約風險之準確性，且信評機構對受評企業財務之惡化較為敏感。另一方面，本研究也發現，信評機構對於非上市櫃公司、金融業以及初次評等等級在「twAA」以上企業之評等，存在較為明顯之錨定現象。 / Credit Rating Agencies (CRAs) play a major role in the financial market. Credit rating purport to provide investors with valuable information they need to make decisions about investing, but the accuracy of the rating itself has been called into question by many investors in recent years. The purpose of this study is to examine the anchoring effect on CRAs while the rating is being given. The results indicate that domestic CRAs tend to be anchored on the past financial information of the issuers. But the impacts are very slightly. Besides this, CRAs seem relatively sensitive to the financial deterioration. Moreover, the anchoring effect are much more significant when the debt issuers are private firms, financial institutions or the companies with greater or equal to twAA initial credit rating.

The gradually changing behavior of the population, towards urbanization, ledto an increased shortage of available housing. This development has resultedin a serious issue in Sweden, where too few firms are providing solutions formulti-family houses in wood. Potential firms that could fill this increasingdemand are those in the single-family house industry. Yet, these firms mightface considerable problems with productivity, predominately derived fromincreasing production costs and inadequate production development.Developing these firms are associated with long-term investments, whichis investigated by evaluating the industry structure for sellers, highlightingthe financial and market situation within their industry. These factors aregrowing in importance due to the current market concentration, where morefirms are required to focus on product development driven by the demand toprefabricate wooden elements, volumes or modules in an industrialized way.This thesis studies Swedish firms producing wooden single-familyhouses, with the aim to investigate their possibilities to enter the woodenmulti-family house industry in Sweden.Investigations will be conducted by applying Altman’s Z’ value, riskposition model, the Herfindahl-Hirschman index, the Herfindahl-Hirschmannumber equivalent, productivity ratio model for profitability and finally amodel measuring market Concentration Ratio.Results show that the industry tends towards perfect competition with toomany firms involved, i.e. firms mainly have to compete by prices. Further,firms are grouped into three zones; risk, grey or safe zone. The levels withinthese zone show a reduction of firms in the red zone over time. Related to thecurrent risks, many firms have promising positions to invest in productdevelopment towards wooden multi-family houses, in addition to theircurrent products, even though firm productivity has declined during thestudied time frame. The results that the investigated firms have goodpossibilities gaining a competitive advantage by diversifying into thegrowing wooden multi-family house industry.

[pt] Os estudos de modelos de previsão de falência tiveram seu início há quase 90 anos, sempre com o intuito de ser uma ferramenta de gestão útil para analistas e gestores das empresas. Embora as primeiras pesquisas sejam antigas, o assunto continua atual. Diversos setores da economia passaram, ou passam, por crises ao longo do tempo e não foi diferente para a indústria de aviação. Nesse contexto, o presente trabalho usou dados históricos de indicadores financeiros das empresas aéreas americanas de um período de três décadas para elaborar quatro modelos de previsão de falência e comparar suas performances preditivas com o Modelo Z-Score. Todas as elaborações foram calibragens do Modelo Z-Score, usando técnicas de simulação e estatística. Duas usaram Análise Discriminante Múltipla (MDA) e duas utilizaram Bootstrap junto com MDA. Um par de cada método utilizou as variáveis originais do Modelo Z-Score e o outro par apresentou sugestão de novo conjunto de variáveis. Os resultados mostraram que o modelo de previsão mais preciso, com 75,0 porcento de acerto na amostra In-Sample e 79,2 porcento na Out-of-Sample, utilizou o conjunto original de variáveis e as técnicas Bootstrap e MDA. / [en] Studies of bankruptcy prediction models started almost 90 years ago, with the intention of being a useful management tool for analysts and managers. Although the first researches are ancient, the subject remains current. Several sectors of the economy have experienced, or are experiencing, crises over time and the aviation industry is no exception. In this context, the present work used historical data of financial indicators of American airlines over a period of three decades to develop four models of bankruptcy forecast and compared their predictive performances with the Z-Score Model. All proposed models were calibrations of the Z-Score model, using simulation and statistical techniques. Two models were generated using Discriminant Analyzes Multiple (MDA) and two using Bootstrap along with MDA. A pair of each method used the original variables of the model s Z-Score and the other pair presented a novel set of variables. Results showed that the most accurate forecasting model, with 75.0 percent accuracy in-sample and 79.2 percent out-of-sample, used the original variables of the model s Z-Score and the Bootstrap e MDA techniques.

This thesis surveys the method of extending Cox proportional hazard models (1972) and the general class of semiparametric model (2004) in the upgrades or downgrades of credit ratings by S&P. The two kinds of models can be used to modify the relationship of covariates to a recurrent event data of upgrades or downgrades. The benchmark credit-scoring model with a quintet of financial ratios which is inspired by the Z-Score model is employed. These financial ratios include measures of short-term liquidity, leverage, sales efficiency, historical profitability and productivity. The evidences of empirical results show that the financial ratios of historical profitability, leverage, and sales efficiency are significant factors on the rating transitions of upgrades. For the downgrades data setting, the financial ratios of short-term liquidity, productivity, and leverage are significant factors in the extending Cox models, whereas only the historical profitability is significant in the general class of semiparametric model. The empirical analysis of S&P credit ratings provide evidence supporting that the transitions of credit ratings are related to some determined financial ratios under these new econometrics methods.