A credit card as a banking product has a dual nature both as a convenient loan and a payment tool. Credit card profitability prediction is a complex problem because of the variety of the card holders' behaviour patterns, a fluctuating balance, and different sources of interest and transactional income. The state of a credit card account depends on the type of card usage and payments delinquency, and can be defined as inactive, transactor, revolver, delinquent, and default. The proposed credit cards profit prediction model consists of four stages: i) utilisation rate and interest rate income prediction, ii) non-interest rate income prediction, iii) account state prediction with conditional transition probabilities, and iv) the aggregation of the partial models into total income estimation. This thesis describes an approach to credit card account-level profitability prediction based on multistate and multistage conditional probabilities models with different types of income and compares methods for the most accurate predictions. We use application, behavioural, card state, and macroeconomic characteristics as predictors. This thesis contains nine chapters: Introduction, Literature Review, six chapters giving descriptions of the data, methodologies and discussions of the results of the empirical investigation, and Conclusion. Introduction gives the key points and main aims of the current research and describes the general schema of the total income prediction model. Literature Review proposes a systematic analysis of academic work on loan profit modelling and highlights the gaps in the application of profit scoring to credit cards income prediction. Chapter 3 describes the data sample and gives the overview of characteristics. Chapter 4 is dedicated to the prediction of the credit limit utilisation and contains the comparative analysis of the predictive accuracy of different regression models. We apply five methods such as i) linear regression, ii) fractional regression, iii) beta-regression, iv) beta-transformation, and v) weighted logistic regression with data binary transformation for utilisation rate prediction for one- and two-stage models. Chapters 5 and 6 are dedicated to modelling the transition probabilities between credit card states. Chapter 5 describes the general model setups, model building methodology such as transition probability prediction with conditional binary logistic, ordinal, and multinomial regressions, the data sample description, the univariate analysis of predictors. Chapter 6 discusses regression estimation results for all types of regression and a comparative analysis of the models. Chapter 7 describes an approach to the non-interest rate income prediction and contains a comparative analysis of panel data regression techniques such as pooled and four random effect methods. We consider two sources of non-interest income generation: i) interchange fees and foreign exchange fees from transactions via pointof- sales (POS) and ii) ATM fees from cash withdrawals. We compare the predictive accuracy of a one-stage approach, which means the usage of a single linear model for the income amount estimation, and a two-stage approach, which means that the income amount conditional on the probability of POS and ATM transaction. Chapter 8 aggregates the results from the partial models into a single model for total income estimation. We assume that a credit card account does not have a single particular state and a single behavioural type in the future, but has a chance to move to any of possible states. The income prediction model is selected according to these states, and the transition probabilities are used as weights for the particular interest rate and non-interest rate income prediction models. Conclusion highlights the contributions of this research. We propose an innovative methodological approach for credit card income prediction as a system of models, which considers the estimation of the income from different sources and then aggregates the income estimations weighted by the states transition probabilities. The results of comparative analysis of regression methods for: i) utilization rate of credit limit and ii) non-interest income prediction, iii) the use of panel data with pooled and random effect for profit scoring, and iv) account level non-binary target transition probabilities estimation for credit cards can be used as benchmarks for further research and fill the gaps of empirical investigations in the literature. The estimation of the transition probability between states at the account level helps to avoid the memorylessness property of the Markov Chains approach. We have investigated the significance of predictors for models of this type. The proposed modelling approach can be applied for the development of business strategies such as credit limit management, customer segmentation by the profitability and behavioural type.

When banks lend money to another party they face a risk that the borrower will not fulfill its obligation towards the bank. This risk is called credit risk and it’s the largest risk banks faces. According to the Basel accord banks need to have a certain amount of capital requirements to protect themselves towards future financial crisis. This amount is calculated for each loan with an attached risk-weighted asset, RWA. The main parameters in RWA is probability of default and loss given default. Banks are today allowed to use their own internal models to calculate these parameters. Thus hold capital with no gained interest is a great cost, banks seek to find tools to better predict probability of default to lower the capital requirement. Machine learning and supervised algorithms such as Logistic regression, Neural network, Decision tree and Random Forest can be used to decide credit risk. By training algorithms on historical data with known results the parameter probability of default (PD) can be determined with a higher certainty degree compared to traditional models, leading to a lower capital requirement. On the given data set in this article Logistic regression seems to be the algorithm with highest accuracy of classifying customer into right category. However, it classifies a lot of people as false positive meaning the model thinks a customer will honour its obligation but in fact the customer defaults. Doing this comes with a great cost for the banks. Through implementing a cost function to minimize this error, we found that the Neural network has the lowest false positive rate and will therefore be the model that is best suited for this specific classification task. / När banker lånar ut pengar till en annan part uppstår en risk i att låntagaren inte uppfyller sitt antagande mot banken. Denna risk kallas för kredit risk och är den största risken en bank står inför. Enligt Basel föreskrifterna måste en bank avsätta en viss summa kapital för varje lån de ger ut för att på så sätt skydda sig emot framtida finansiella kriser. Denna summa beräknas fram utifrån varje enskilt lån med tillhörande risk-vikt, RWA. De huvudsakliga parametrarna i RWA är sannolikheten att en kund ej kan betala tillbaka lånet samt summan som banken då förlorar. Idag kan banker använda sig av interna modeller för att estimera dessa parametrar. Då bundet kapital medför stora kostnader för banker, försöker de sträva efter att hitta bättre verktyg för att uppskatta sannolikheten att en kund fallerar för att på så sätt minska deras kapitalkrav. Därför har nu banker börjat titta på möjligheten att använda sig av maskininlärningsalgoritmer för att estimera dessa parametrar. Maskininlärningsalgoritmer såsom Logistisk regression, Neurala nätverk, Beslutsträd och Random forest, kan användas för att bestämma kreditrisk. Genom att träna algoritmer på historisk data med kända resultat kan parametern, chansen att en kund ej betalar tillbaka lånet (PD), bestämmas med en högre säkerhet än traditionella metoder. På den givna datan som denna uppsats bygger på visar det sig att Logistisk regression är den algoritm med högst träffsäkerhet att klassificera en kund till rätt kategori. Däremot klassifiserar denna algoritm många kunder som falsk positiv vilket betyder att den predikterar att många kunder kommer betala tillbaka sina lån men i själva verket inte betalar tillbaka lånet. Att göra detta medför en stor kostnad för bankerna. Genom att istället utvärdera modellerna med hjälp av att införa en kostnadsfunktion för att minska detta fel finner vi att Neurala nätverk har den lägsta falsk positiv ration och kommer därmed vara den model som är bäst lämpad att utföra just denna specifika klassifierings uppgift.

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中華民國第十任總統選舉結果於民國八十九年三月十八日揭曉，這場眾所矚目的選舉終告落幕，然而對選舉研究工作者而言卻是新的開始。選舉預測居選戰中重要的一環，也是研究選舉的學者關心的問題，更提供了一個驗證選民投票行為理論的絕佳機會，近來國內相關論述已有相當成果。但由於它在投票結束，便有答案，其挑戰程度不言而喻。因此，如何結合理論、方法及事實三者為一體的努力，對選舉預測更是別具意義。 本篇研究之範圍，是以公元2000年總統大選為例，對選舉預測工作做更深層的探討，且檢驗邏輯斯預測模型（Logistic Regression Model）及模糊統計（Fuzzy Statistics）分析在本次總統選舉的預測力，考量本次總統選舉中各項可能影響選情的因素，進一步建構選舉預測模式，然而兩種預測模式的初步預測結果並不佳，經過棄保效應的可能性調整後，預測誤差已大幅降低，其中模糊統計（Fuzzy Statistics）分析預測結果經棄保效應調整後，與實際開票結果相當接近，因此與邏輯斯預測模型相較，模糊統計分析的應用對未表態選民投票意向的預測力較佳。一套完整的選舉預測模型研究，應包含問卷設計、抽樣訪問、資料處理、加權除錯、模型設計與預測評估等整套研究流程，然而在本次總統大選中，由於三強激戰，影響選情因素相當複雜，最後此兩種選舉預測模式皆無法獲致精確的預測結果。因此，我們期待選舉預測模型的建構，能突破主客觀環境的侷限，進一步達到「準」與「穩」的要求。 / With the successful staging of the 2000 presidential elections in Taiwan, scholars have been presented with a new opportunity to test their theories. Electoral predictions are an important field within the study of elections and have been among the most keenly studied questions over the past few years. Unlike many other research topics, there is an absolute standard for election predictions: the election results. Thus, combining theory, methodology, and facts to obtain a meaningful result is no simple task. This thesis attempts to predict the 2000 presidential election using both a logistic regression model and a fuzzy statistics model. After constructing models which includes all kinds of different variables that might influence the electoral outcome, we find that neither the logistic regression model nor the fuzzy statistics model is particularly accurate. However, after accounting for the effects of strategic voting, model error decreases dramatically. In particular, after including provisions for strategic voting, the fuzzy statistics model is improved to the point that its predictions are extremely close to the actual outcome. Thus, we show that the fuzzy statistics model is superior to the logistic regression model in analyzing the vote choices of undecided voters. Research on electoral predictions should include such aspects as questionnaire design, sampling, interviewing, data processing, weighting, data cleaning, model design, and evaluation of the prediction. However, because this election featured a particularly intense three way race, the factors affecting the electoral outcome were both numerous and intertwined in complex ways. Unfortunately, it is impossible to evaluate our electoral predictions of the two models precisely. We hope that in the future, election prediction models will be able to break through these environmental limitations and achieve more accurate and stable predictions.

規模效應是資本資產定價模型所無法解釋的報酬異常現象中，最常被討論的一個。本文首先將探討台灣股市是否具有規模效應情形，若有，再進一步檢視其型態為何。接下來，本文試圖了解是否公司發生財務危機的機率高低會與規模溢酬有所關連，亦即，小公司因為較容易發生財務危機事件，因此平均而言，較大公司有更高的報酬率。本研究將採用Shumway(2001)的羅吉斯迴歸模型來估算公司發生財務危機事件之機率，並且比較不同變數之預測能力如何。 經由實證結果，發現1986年至2009年的台灣股市具有規模效應情形，此結果與之前幾位研究者之研究結果相符。而在財務危機事件機率的部份，亦可看出發生財務危機機率較高的投資組合享有較高的報酬率，此情形在小市值規模的公司身上尤其明顯。從以上發現，我們可以推論財務危機風險確實為構成規模效應的因素之一。 / Size effect is one of wildly-discussed pricing anomalies that cannot be explained by capital assets pricing model, we would like to exam whether it exists in Taiwan stock markets and how its pattern is. Furthermore, we assume the higher financial distress risk a company has, the higher expected return it will earn. That is, there is positive correlation between financial distress risk and return. Following the logistic model developed by Shumway(2001), we explore the list of variables which have greater explanatory power in prediction. Through empirical data with stocks listed and ever listed on Taiwan Stock Exchange and GreTai Securities Market, we find size effect does exist. The result is consistent with previous study. We also see firms with higher distress risk tend to have higher returns, this condition is especially obvious in small companies. So we can infer that having higher distress risk is one of the reasons why small companies can earn higher returns, they are consistent with our conjecture.

Globally, there is a growing demand for food away from home as a result of higher incomes, changes in consumption patterns, changes in household composition, and the time pressures created by dual-working families. The foodservice industry has become highly competitive as the number of foodservice outlets has increased to meet the demand. In order to succeed in such a competitive industry, restaurant operators need to understand the factors (and their relative importance) that influence restaurant patrons’ decision when selecting a restaurant. The demand for ethnic foods has also increased, in New Zealand and worldwide, due to the influences of ethnic diversity, overseas food and cultural experiences, and media exposure. Despite the importance of restaurant choice criteria and a growth in popularity of ethnic foods, published research on consumers’ restaurant selection behaviour that focuses on the ethnic segment is relatively limited. Furthermore, there are no published empirical studies on ethnic restaurant choice behaviour in New Zealand. This research aims to fill these gaps in the literature by empirically identifying the factors that influence a decision to dine at an upscale ethnic restaurant, their relative importance, as well as their relationships with dining occasion and consumer characteristics. Focus group discussions and the literature review helped identify a set of restaurant choice factors. A mail survey was used to collect the data. Factor analysis was used to refine the restaurant choice factors, and logistic regression analysis identified the five significant factors that influence consumers’ decision. These are: Dining Experience, Social Status, Service Quality, Food Quality, and Value for Money, listed in order of their importance. The results of t-tests and ANOVA suggested that consumers perceived the restaurant choice factors differently based on their demographic characteristics. The results of this study contribute to the marketing theory by providing an empirical framework of consumer selection behaviour in New Zealand upscale ethnic dining establishments. The study will also assist marketing practitioners and operators of ethnic restaurants to develop their strategies and offer the attributes that attract and retain customers.

<p>The use of marketing research panels are a more and more frequently used source of information for studies within many different branches. The purpose of this report is to investigate the demographic composition of panels and compare it with the population of Sweden, a possible change in behaviour of respondents, and if the source of recruitment is the cause of possible differences in study results. The study was commissioned by Norstats Linkoping office. Sources for the data material include Norstat’s recruitment process and their two main panels with different recruitment sources. To enable a deeper investigation of behaviour we also constructed a survey that was sent to 2,714 members of Norstat’s internet panels.</p><p>The statistical analysis includes contingency table analysis, multiple logistic regression, and Poisson regression. The results show that the demographic composition does not fully cover all the aspects of the Swedish population and some groups are less represented than others. The behaviour tends to differ between panel members that have responded to three or less surveys compared to members that have responded to twenty or more surveys. Source of recruitment does not seem to affect the results of studies, but it has some effect on the demographic composition of marketing research panels.</p> / <p>Användandet av paneler som källa vid undersökningar har den senaste tiden blivit en allt vanligare företeelse. Denna rapport har för avsikt att undersöka panelers demografiska sammansättning och överensstämmande med Sveriges befolkning, eventuell ändring av svarsbeteende samt huruvida rekryteringskällan ger upphov till kvalitetsskillnader hos medlemmar i en panel. Företaget Norstat har med sitt kontor i Linköping figurerat som uppdragsgivare till arbetet. Datamaterialet till studien har uppkommit från Norstats rekryteringsprocess samt från företagets två huvudpaneler med olika rekryteringskällor. För att djupare undersöka svarsbeteende konstruerade vi även en enkätundersökning som skickades ut till 2 714 medlemmar i Norstats internetpaneler.</p><p>Den statiska analysen innefattar χ2-test, multipel logistisk regression samt Poissonregression. Resultaten påvisade att den demografiska sammansättningen i panelen inte fullt ut speglade Sveriges befolkning samt att vissa grupper undertäcks i högre utsträckning än andra. Svarsbeteendet hos medlemmar i paneler har en tendens att ändras från det att medlemmen har svarat på en till tre undersökningar, till det att den har svarat på tjugo undersökningar eller fler. Rekryteringskällan till en panel verkar inte ge upphov till några större skillnader i svarsresultat, men däremot finns vissa skillnader i demografisk sammansättning.</p>

<p>Small firms often have inadequate access to the capital necessary for sucessful management. The Swedish Government introduced in the mid-1990s allowance rules that facilitate retention of profit for sole proprietorships and partnership firms. The tax credits arising from the allowances give certain benefits as a source of financing compared to traditional forms of credits. Among the more essential benefits are that the payment for some parts of the tax credit can be put on hold almost indefinitely, or alternatively never be paid. The firms are free to use these means, and the responsibility of future payment of the postponed tax debt stays with the individual firms. The comprehensive purpose of the dissertation may be stated as to increase the understanding of small Swedish firms, especially sole proprietorships, utilizing possibilities for allowances for income smoothing and internal financing. At the beginning the dissertation describes case studies, comprising a smaller selection of microfirms. With a starting-point from the accounted and reported income-tax returns, alternative calculations are made where additional positive tax and finance effects appear possible to obtain. One purpose of these studies is to increase the insight regarding the possibilities of income smoothing and internal financing that arise from utilizing these allowances. </p><p>These studies also illuminate, to what extent and in what way they are being used in reality. Another objective of these studies is to give a more substantive insight into the technics behind the different allowances, appropriation to positive or negative interest rate allocation appropriation or dissolving of tax allocation reserve appropriation or dissolving of “expansion fund” Theories regarding the creation of resources, through building of capital, and theories on financial planning and strategy are studied. The purpose is to find support for the choice of theoretical grounded underlying independent variables that can be used in cross-sectional studies to explain the use of the possibilities of appropriations. Theories of finance that are of greatest interest, in the operationalisation of these variables, are theories that discuss the choices of different financing alternatives for small firms. The “pecking order theory”, describes the firm’s order of priority when choices of finance alternatives are made. The concept of “financial bootstrapping” expands the frame for different forms of financing choices that especially very small firms have at their disposal.</p><p>The last part of the theoretical frame deals with the phenomenon of “income smoothing,” which can be translated as leveling out profits/losses. A number of financial and non-financial variables are supported by and operationalised from these financial theories e.g., return on sales, capital turnover, quick ratio and debt-to-equity ratio, respectively age, gender and line of business. Cross-sectional studies are implemented for the taxation years of 1996 and 1999, on databases that have been extracted from Statistics Sweden. The group of 87,276 sole proprietorships included in the study were required to complete tax returns and pay taxes for the business activity according to the supporting schedule, N2, information from the sole proprietorships’ income statement and balance sheet in an accounting statement that comes with the income tax return form. The possibilities of allowances are considered as dependent variables. The intention of the cross-sectional studies is to survey and describe the utilization of possible allowances, with the support of the financial and non-financial independent variables. The connection of these variables to the decision of sole proprietorships to appropriate to the tax allocation reserve is also summarized in a logistic regression model. A number of theoretically based propositions are made for the purpose of observing how the variables are connected to the chances that sole proprietorships actually appropriate to this form of allowance. Appropriation to the tax allocation reserve stands out as the most practiced form of allowance. The studies also clarify that utilization varies among different forms of allowances, but that not all firms that have the prerequisites to utilize the possibilities really do so to the full. A further utilization of the different possibilities of allowances is often conceivable. For the sole proprietorships that are not utilizing these possibilities, the allowances should be considered eligible as a contribution to internal financing and to increase access to capital.</p>

Small firms often have inadequate access to the capital necessary for sucessful management. The Swedish Government introduced in the mid-1990s allowance rules that facilitate retention of profit for sole proprietorships and partnership firms. The tax credits arising from the allowances give certain benefits as a source of financing compared to traditional forms of credits. Among the more essential benefits are that the payment for some parts of the tax credit can be put on hold almost indefinitely, or alternatively never be paid. The firms are free to use these means, and the responsibility of future payment of the postponed tax debt stays with the individual firms. The comprehensive purpose of the dissertation may be stated as to increase the understanding of small Swedish firms, especially sole proprietorships, utilizing possibilities for allowances for income smoothing and internal financing. At the beginning the dissertation describes case studies, comprising a smaller selection of microfirms. With a starting-point from the accounted and reported income-tax returns, alternative calculations are made where additional positive tax and finance effects appear possible to obtain. One purpose of these studies is to increase the insight regarding the possibilities of income smoothing and internal financing that arise from utilizing these allowances. These studies also illuminate, to what extent and in what way they are being used in reality. Another objective of these studies is to give a more substantive insight into the technics behind the different allowances, appropriation to positive or negative interest rate allocation appropriation or dissolving of tax allocation reserve appropriation or dissolving of “expansion fund” Theories regarding the creation of resources, through building of capital, and theories on financial planning and strategy are studied. The purpose is to find support for the choice of theoretical grounded underlying independent variables that can be used in cross-sectional studies to explain the use of the possibilities of appropriations. Theories of finance that are of greatest interest, in the operationalisation of these variables, are theories that discuss the choices of different financing alternatives for small firms. The “pecking order theory”, describes the firm’s order of priority when choices of finance alternatives are made. The concept of “financial bootstrapping” expands the frame for different forms of financing choices that especially very small firms have at their disposal. The last part of the theoretical frame deals with the phenomenon of “income smoothing,” which can be translated as leveling out profits/losses. A number of financial and non-financial variables are supported by and operationalised from these financial theories e.g., return on sales, capital turnover, quick ratio and debt-to-equity ratio, respectively age, gender and line of business. Cross-sectional studies are implemented for the taxation years of 1996 and 1999, on databases that have been extracted from Statistics Sweden. The group of 87,276 sole proprietorships included in the study were required to complete tax returns and pay taxes for the business activity according to the supporting schedule, N2, information from the sole proprietorships’ income statement and balance sheet in an accounting statement that comes with the income tax return form. The possibilities of allowances are considered as dependent variables. The intention of the cross-sectional studies is to survey and describe the utilization of possible allowances, with the support of the financial and non-financial independent variables. The connection of these variables to the decision of sole proprietorships to appropriate to the tax allocation reserve is also summarized in a logistic regression model. A number of theoretically based propositions are made for the purpose of observing how the variables are connected to the chances that sole proprietorships actually appropriate to this form of allowance. Appropriation to the tax allocation reserve stands out as the most practiced form of allowance. The studies also clarify that utilization varies among different forms of allowances, but that not all firms that have the prerequisites to utilize the possibilities really do so to the full. A further utilization of the different possibilities of allowances is often conceivable. For the sole proprietorships that are not utilizing these possibilities, the allowances should be considered eligible as a contribution to internal financing and to increase access to capital.

Basal Temperature of Snow (BTS) measurements were used as the primary inputs to a high resolution (30 x 30 m grid cells) empirical-statistical regional permafrost probability model for the southern and central Yukon, and northernmost British Columbia (59° - 65°N). Data from seven individual study areas distributed across the region were combined using a blended distance decay technique, with an eighth area used for validation. The model predictions are reasonably consistent with previous permafrost maps for the area with some notable differences and a much higher level of detail. The modelling gives an overall permafrost probability of 52%. North of 62°N, permafrost becomes more extensive in the lowland areas whereas farther south permafrost is typically common only above treeline. Significant differences exist between the mountain environments of the Yukon and the Swiss Alps where the BTS method originated and as a result different modelling approaches had to be developed. This work therefore: (1) develops additional explanatory variables for permafrost probability modelling, the most notable of which is equivalent elevation, (2) confirms the use of ground truthing as a requirement for empirical-statistical modelling in the Yukon and (3) uses a combination of models for the region in order to spatially predict between study areas. The results of this thesis will be of use to linear infrastructure route-planning, geohazard assessment and climate change adaptation strategies. Future work employing the model will allow the effects of scenario-based climate warming to be examined.