The Persistence of Finnish Equity Fund Performance

Tutkimuksen tavoitteena on selvittää, esiintyykö suomeen sijoittavilla osakerahastoilla menestyksen pysyvyyttä. Tutkimusaineisto koostuu kaikista suomalaisista osakerahastoista, jotka toimivat ajanjaksolla 15.1.1998-13.1.2005. Aineisto on vapaa selviytymisvinoumasta. Suorituskyvyn mittareina käytetään CAPM-alfaa sekä kolmi- ja nelifaktori-alfaa. Empiirisessä osassa osakerahastojen menestyksen pysyvyyttä testataan Spearmanin järjestyskorrelaatiotestillä. Evidenssi menestyksen pysyvyydestä jäi vähäiseksi, vaikkakin sitä esiintyi satunnaisesti kaikilla menestysmittareilla joillakin ranking- ja sijoitusperiodin yhdistelmillä. CAPM-alfalla tarkasteltuna tilastollisesti merkitsevää menestyksen pysyvyyttä esiintyi selvästi useammin kuin muilla menestysmittareilla. Tulokset tukevat viimeaikaisia kansainvälisiä tutkimuksia, joiden mukaan menestyksen pysyvyys riippuu usein mittaustavasta. Menestysmittareina käytettyjen regressiomallien merkitsevyystestit osoittavat multifaktorimallien selittävän osakerahastojen tuottoja CAPM:a paremmin. Lisätyt muuttujat parantavat merkittävästi CAPM:n selitysvoimaa.

Koulusaavutusaineiston analyysi asetelmaperusteisilla ja kaksitasoisilla logit-regressiomalleilla

Summary: The analysis of educational data with design-based and two-level logistic regression models

Painokoneen suorituskykyanalyysi tuotannon tehokkuuden arvioimiseksi ja hinnoittelupäätösten tueksi

Työn tavoite on analysoida kirjapainon offsetrotaatiopainokoneen painoyksikön yksi, eli pienen linjan, ja painoyksiköiden kaksi ja kolme muodostaman painokoneen, eli ison linjan, suorituskykyä vuosien 1996-1997 ja vuosien 2002-2006 tuotantotietojen perusteella. Analyysit on tehty erikseen molemmille linjoille vuosien 1996-1997 ja vuosien 2002-2006 osalta, koska nettoajonopeudet ovat laskeneet molemmilla painolinjoilla huomattavasti vuosista 1996 ja 1997. Suorituskykyanalyysien perusteella ei löytynyt mitään teknistä tai töiden ominaisuuksista johtuvaa syytä ajonopeuksien huomattavaan laskuun. Työssä on tutkittu painotyön ominaisuuksien perusteella määräytyvän tuotantotavan, painopaperin ja painosmäärän vaikutusta ajonopeuteen ja sitä kautta toteutuneeseen ajohintaan. Suorituskykyanalyysien pohjalta on muodostettu molemmille linjoille erityyppisten tuotteiden sisäiseen hinnoitteluun sopivat regressiomallit, joilla voidaan parhaiten estimoida erilaisten tuotteiden ajohintoja. Työssä on tarkasteltu lyhyesti myös painokoneen kuntoonlaitto- ja häiriöaikojen sekä hukkamäärien kehitystä, koska ajonopeus pelkästään ei anna oikeaa kuvaa koko tuotannon tehokkuudesta. Kokonaistehokkuuden parantaminen on korkeiden ajonopeuksien lisäksi edellytys kirjapainon kilpailukyvyn säilyttämiseksi.

Combining Advanced Forecasting Methods with System Dynamics - the Case of Finnish Seaports

Seaports play an important part in the wellbeing of a nation. Many nations are highly dependent on foreign trade and most trade is done using sea vessels. This study is part of a larger research project, where a simulation model is required in order to create further analyses on Finnish macro logistical networks. The objective of this study is to create a system dynamic simulation model, which gives an accurate forecast for the development of demand of Finnish seaports up to 2030. The emphasis on this study is to show how it is possible to create a detailed harbor demand System Dynamic model with the help of statistical methods. The used forecasting methods were ARIMA (autoregressive integrated moving average) and regression models. The created simulation model gives a forecast with confidence intervals and allows studying different scenarios. The building process was found to be a useful one and the built model can be expanded to be more detailed. Required capacity for other parts of the Finnish logistical system could easily be included in the model.

Tilastollinen tutkimus ohjelmiston laatuun vaikuttavista tekijöistä

Tämä työ on tehty osana MASTO-tutkimushanketta, jonka tarkoituksena on kehittää ohjelmistotestauksen adaptiivinen referenssimalli. Työ toteutettiin tilastollisena tutkimuksena käyttäen survey-menetelmää. Tutkimuksessa haastateltiin 31 organisaatioyksikköä eri puolelta suomea, jotka tekevät keskikriittisiä sovelluksia. Tutkimuksen hypoteeseina oli laadun riippuvuus ohjelmistokehitysmenetelmästä, asiakkaan osallistumisesta, standardin toteutumisesta, asiakassuhteesta, liiketoimintasuuntautuneisuudesta, kriittisyydestä, luottamuksesta ja testauksen tasosta. Hypoteeseista etsittiin korrelaatiota laadun kanssa tekemällä korrelaatio ja regressioanalyysi. Lisäksi tutkimuksessa kartoitettiin minkälaisia ohjelmistokehitykseen liittyviä käytäntöjä, menetelmiä ja työkaluja organisaatioyksiköissä käytettiin, ongelmia ja parannusehdotuksia liittyen ohjelmistotestaukseen, merkittävimpiä tapoja asiakkaan vaikuttamiseksi ohjelmiston laatuun sekä suurimpia hyötyjä ja haittoja ohjelmistokehityksen tai testauksen ulkoistamisessa. Tutkimuksessa havaittiin, että laatu korreloi positiivisesti ja tilastollisesti merkitsevästi testauksen tason, standardin toteutumisen, asiakasosallistumisen suunnitteluvaiheessa sekä asiakasosallistumisen ohjaukseen kanssa, luottamuksen ja yhden asiakassuhteeseen liittyvän osakysymyksen kanssa. Regressioanalyysin perusteella muodostettiin regressioyhtälö, jossa laadun todettiin positiivisesti riippuvan standardin toteutumisesta, asiakasosallistumisesta suunnitteluvaiheessa sekä luottamuksesta.

Capital Structure of Finnish SMEs and Financial Constraints

This thesis studies capital structure of Finnish small and medium sized enterprises. The specific object of the study is to test whether financial constraints have an effect on capital structure. In addition influences of several other factors were studied. Capital structure determinants are formulated based on three capital structure theories. The tradeoff theory and the agency theory concentrate on the search of optimal capital structure. The pecking order theory concerns favouring on financing source over another. The data of this study consists of financial statement data and results of corporate questionnaire. Regression analysis was used to find out the effects of several determinants. Regression models were formed based on the presented theories. Short and long term debt ratios were considered separately. The metrics of financially constrained firms was included in all models. It was found that financial constrains have a negative and significant effect to short term debt ratios. The effect was negative also to long term debt ratio but not statistically significant. Other considerable factors that influenced debt ratios were fixed assets, age, profitability, single owner and sufficiency of internal financing.

Commodity Price Driven Risk Management from Viewpoint of High Grade Steel Alloys

The study of price risk management concerning high grade steel alloys and their components was conducted. This study was focused in metal commodities, of which nickel, chrome and molybdenum were in a central role. Also possible hedging instruments and strategies for referred metals were studied. In the literature part main themes are price formation of Ni, Cr and Mo, the functioning of metal exchanges and main hedging instruments for metal commodities. This section also covers how micro and macro variables may affect metal prices from the viewpoint of short as well as longer time period. The experimental part consists of three sections. In the first part, multiple regression model with seven explanatory variables was constructed to describe price behavior of nickel. Results were compared after this with information created with comparable simple regression model. Additionally, long time mean price reversion of nickel was studied. In the second part, theoretical price of CF8M alloy was studied by using nickel, ferro-chrome and ferro-molybdenum as explanatory variables. In the last section, cross hedging possibilities for illiquid FeCr -metal was studied with five LME futures. Also this section covers new information concerning possible forthcoming molybdenum future contracts as well. The results of this study confirm, that linear regression models which are based on the assumption of market rationality, are not able to reliably describe price development of metals at issue. Models fulfilling assumptions for linear regression may though include useful information of statistical significant variables which have effect on metal prices. According to the experimental part, short futures were found to incorporate the most accurate information concerning the price movements in the future. However, not even 3M futures were able to predict turning point in the market before the faced slump. Cross hedging seemed to be very doubtful risk management strategy for illiquid metals, because correlations coefficients were found to be very sensitive for the chosen time span.

Analysis of patterns in mining time series using Qlucore

Raw measurement data does not always immediately convey useful information, but applying mathematical statistical analysis tools into measurement data can improve the situation. Data analysis can offer benefits like acquiring meaningful insight from the dataset, basing critical decisions on the findings, and ruling out human bias through proper statistical treatment. In this thesis we analyze data from an industrial mineral processing plant with the aim of studying the possibility of forecasting the quality of the final product, given by one variable, with a model based on the other variables. For the study mathematical tools like Qlucore Omics Explorer (QOE) and Sparse Bayesian regression (SB) are used. Later on, linear regression is used to build a model based on a subset of variables that seem to have most significant weights in the SB model. The results obtained from QOE show that the variable representing the desired final product does not correlate with other variables. For SB and linear regression, the results show that both SB and linear regression models built on 1-day averaged data seriously underestimate the variance of true data, whereas the two models built on 1-month averaged data are reliable and able to explain a larger proportion of variability in the available data, making them suitable for prediction purposes. However, it is concluded that no single model can fit well the whole available dataset and therefore, it is proposed for future work to make piecewise non linear regression models if the same available dataset is used, or the plant to provide another dataset that should be collected in a more systematic fashion than the present data for further analysis.

Accounting Beta Measuring Systematic Risk: Empirical Evidence from the Finnish Markets

The main purpose of this study is to examine whether accounting-based variables can be used to measure systematic risk of a company using Finnish data. When the fundamental sources of systematic risk are known, companies are able to manage these risks and increase company value. Accounting beta was formed based on OLS regression models. Theoretical background for the study was based on the findings of studies according to which business risk, financial risk, operating risk and growth risk can be theoretically regarded as determinants of the systematic risk. The results reveal that accounting variables describe systematic risk of a company. The accounting beta is found to be particularly sensitive to the changes in the risk components. The investigation is confidential until 15.10.2012.

Venture capital investment on SME

This thesis studies venture capital investment on small and medium-sized enterprises (SMEs). The specific objective of the study is to test whether venture capitalists have a positive effect on SMEs. In addition effect of several other factors is studied in financial crisis. Used determinants are formulated based on three capital structure theories. The pecking order theory concerns favoring on financing source over another. The agency theory and the tradeoff theory concentrate on the search of optimal capital structure. The data of this study consist of financial statement data and results of corporate questionnaire. Regression analysis was used to find out the effects of several determinants. Regression models were formed based on the presented theories. SMEs with and without venture capitalists were considered separately. It was found that venture capitalists have a positive effect on SMEs. Although some results between SMEs with and without venture capitalists were mixed.

Determinants of cash holdings in Finnish industrial sector: measuring the impact of financial crisis 2007- 2010

This thesis studies cash and short term investments to net assets ratio of Finnish industrial companies during financial crisis, and how different firm specific and macro economical variables affect cash and short term investments. The data consists of quarter level interim reports. Regression analysis was used to find out the effects of different variables. Regression models were formed based on previous studies on cash holdings. It was found that firms studied held more cash during financial crisis than before it. Cash and short-term investments acted as substitute of net working capital. Leverage had a positive and significant relationship to cash and short term investment ratio. It was also found out that firms have a target cash and short term investments ratio.

Fractures in older people - incidence, predictors and consequences

In older populations, fractures are common and the consequences of fractures may be serious both for an individual and for society. However, information is scarce about the incidence, predictors and consequences of fractures in population-based unselected cohorts including both men and women and a long follow-up. The objective of this study was to analyse the incidence and predictors of fractures as well as functional decline and excess mortality due to fractures, among 482 men and 695 women aged 65 or older in the municipality of Lieto, Finland from 1991 until 2002. In analyses, Poisson’s, Cox proportional Hazards and Cumulative Logistic regression models were used for the control of several confounding variables. During the 12-year follow-up with a total of 10 040 person-years (PY), 307 (26%) persons sustained altogether 425 fractures of which 77% were sustained by women. The total incidence of fractures was 53.4 per 1000 PY (95% confidence intervals [95% CI]: 47.9 - 59.5) in women and 24.9 per 1000 PY (95% CI: 20.4 - 30.4) in men. The incidence rates of fractures at any sites and hip fractures were associated with increasing age. No significant changes in the ageadjusted incidence rates of fractures were found in either gender during the 12-year follow-up. The predictors of fractures varied by gender. In multivariate analyses, reduced handgrip strength and body mass index (BMI) lower than 30 in women and a large number of depressive symptoms in men were independent predictors of fractures. A compression fracture in one or more thoracic or upper lumbar vertebras on chest radiography at baseline was associated with subsequent fractures in both genders. Lower body fractures independently predicted both short- (0-2 years) and long-term (up to 8 years) functional decline in mobility and activities of daily living (ADL) performance during the 8-year follow-up. Upper body fractures predicted decline in ADL performance during longterm follow-up. In the 12-year follow-up, hip fractures in men (Hazard Ratio [HR] 8.1, 95% CI: 4.4-14.9) and in women (HR 3.0, 95% CI: 1.9-4.9), and fractures at the proximal humerus in men (HR 5.4, 95% CI: 1.6-17.7) were independently associated with excess mortality. In addition, leisure time inactivity in physical exercise predicted independently both functional decline and excess mortality. Fractures are common among older people posing serious individual consequences. Further studies about the effectiveness of preventing falls and fractures as well as improving care and rehabilitation after fractures are needed.

Software for design of experiments and response modelling of cake ltration applications

Filtration is a widely used unit operation in chemical engineering. The huge variation in the properties of materials to be ltered makes the study of ltration a challenging task. One of the objectives of this thesis was to show that conventional ltration theories are di cult to use when the system to be modelled contains all of the stages and features that are present in a complete solid/liquid separation process. Furthermore, most of the ltration theories require experimental work to be performed in order to obtain critical parameters required by the theoretical models. Creating a good overall understanding of how the variables a ect the nal product in ltration is somewhat impossible on a purely theoretical basis. The complexity of solid/liquid separation processes require experimental work and when tests are needed, it is advisable to use experimental design techniques so that the goals can be achieved. The statistical design of experiments provides the necessary tools for recognising the e ects of variables. It also helps to perform experimental work more economically. Design of experiments is a prerequisite for creating empirical models that can describe how the measured response is related to the changes in the values of the variable. A software package was developed that provides a ltration practitioner with experimental designs and calculates the parameters for linear regression models, along with the graphical representation of the responses. The developed software consists of two software modules. These modules are LTDoE and LTRead. The LTDoE module is used to create experimental designs for di erent lter types. The lter types considered in the software are automatic vertical pressure lter, double-sided vertical pressure lter, horizontal membrane lter press, vacuum belt lter and ceramic capillary action disc lter. It is also possible to create experimental designs for those cases where the variables are totally user de ned, say for a customized ltration cycle or di erent piece of equipment. The LTRead-module is used to read the experimental data gathered from the experiments, to analyse the data and to create models for each of the measured responses. Introducing the structure of the software more in detail and showing some of the practical applications is the main part of this thesis. This approach to the study of cake ltration processes, as presented in this thesis, has been shown to have good practical value when making ltration tests.

Software for design of experiments and response modelling of cake filtration applications

Filtration is a widely used unit operation in chemical engineering. The huge variation in the properties of materials to be ltered makes the study of ltration a challenging task. One of the objectives of this thesis was to show that conventional ltration theories are di cult to use when the system to be modelled contains all of the stages and features that are present in a complete solid/liquid separation process. Furthermore, most of the ltration theories require experimental work to be performed in order to obtain critical parameters required by the theoretical models. Creating a good overall understanding of how the variables a ect the nal product in ltration is somewhat impossible on a purely theoretical basis. The complexity of solid/liquid separation processes require experimental work and when tests are needed, it is advisable to use experimental design techniques so that the goals can be achieved. The statistical design of experiments provides the necessary tools for recognising the e ects of variables. It also helps to perform experimental work more economically. Design of experiments is a prerequisite for creating empirical models that can describe how the measured response is related to the changes in the values of the variable. A software package was developed that provides a ltration practitioner with experimental designs and calculates the parameters for linear regression models, along with the graphical representation of the responses. The developed software consists of two software modules. These modules are LTDoE and LTRead. The LTDoE module is used to create experimental designs for di erent lter types. The lter types considered in the software are automatic vertical pressure lter, double-sided vertical pressure lter, horizontal membrane lter press, vacuum belt lter and ceramic capillary action disc lter. It is also possible to create experimental designs for those cases where the variables are totally user de ned, say for a customized ltration cycle or di erent piece of equipment. The LTRead-module is used to read the experimental data gathered from the experiments, to analyse the data and to create models for each of the measured responses. Introducing the structure of the software more in detail and showing some of the practical applications is the main part of this thesis. This approach to the study of cake ltration processes, as presented in this thesis, has been shown to have good practical value when making ltration tests.

Comparison of model-based above ground biomass predictions from LiDAR

In order to reduce greenhouse emissions from forest degradation and deforestation the international programme REDD (Reducing Emissions from Deforestation and forest Degradation) was established in 2005 by the United Nations Framework Convention on Climate Change (UNFCCC). This programme is aimed to financially reward to developing countries for any emissions reductions. Under this programm the project of setting up the payment system in Nepal was established. This project is aimed to engage local communities in forest monitoring. The major objective of this thesis is to compare and verify data obtained from di erect sources - remotely sensed data, namely LiDAR and field sample measurements made by two groups of researchers using two regression models - Sparse Bayesian Regression and Bayesian Regression with Orthogonal Variables.