Quantitative market and sales forecast accuracy analysis

The main objective of this master’s thesis was to quantitatively study the reliability of market and sales forecasts of a certain company by measuring bias, precision and accuracy of these forecasts by comparing forecasts against actual values. Secondly, the differences of bias, precision and accuracy between markets were explained by various macroeconomic variables and market characteristics. Accuracy and precision of the forecasts seems to vary significantly depending on the market that is being forecasted, the variable that is being forecasted, the estimation period, the length of the estimated period, the forecast horizon and the granularity of the data. High inflation, low income level and high year-on-year market volatility seems to be related with higher annual market forecast uncertainty and high year-on-year sales volatility with higher sales forecast uncertainty. When quarterly market size is forecasted, correlation between macroeconomic variables and forecast errors reduces. Uncertainty of the sales forecasts cannot be explained with macroeconomic variables. Longer forecasts are more uncertain, shorter estimated period leads to higher uncertainty, and usually more recent market forecasts are less uncertain. Sales forecasts seem to be more uncertain than market forecasts, because they incorporate both market size and market share risks. When lead time is more than one year, forecast risk seems to grow as a function of root forecast horizon. When lead time is less than year, sequential error terms are typically correlated, and therefore forecast errors are trending or mean-reverting. The bias of forecasts seems to change in cycles, and therefore the future forecasts cannot be systematically adjusted with it. The MASE cannot be used to measure whether the forecast can anticipate year-on-year volatility. Instead, we constructed a new relative accuracy measure to cope with this particular situation.

Modelling mean above and below ground litter production based on yield tables

Selective papers of the workshop on "Development of models and forest soil surveys for monitoring of soil carbon", Koli, Finland, April 5-9 2006.

A comparison of electricity spot prices simulation using ARMA-GARCH and mean-reverting models

The aim of this work is to compare two families of mathematical models for their respective capability to capture the statistical properties of real electricity spot market time series. The first model family is ARMA-GARCH models and the second model family is mean-reverting Ornstein-Uhlenbeck models. These two models have been applied to two price series of Nordic Nord Pool spot market for electricity namely to the System prices and to the DenmarkW prices. The parameters of both models were calibrated from the real time series. After carrying out simulation with optimal models from both families we conclude that neither ARMA-GARCH models, nor conventional mean-reverting Ornstein-Uhlenbeck models, even when calibrated optimally with real electricity spot market price or return series, capture the statistical characteristics of the real series. But in the case of less spiky behavior (System prices), the mean-reverting Ornstein-Uhlenbeck model could be seen to partially succeeded in this task.

Stellar population synthesis: the effect of improved Asymptotic Giant Branch models and of interstellar dust on mass-to-light–color relations

Teoreettisen populaatiosynteesin avulla voidaan mallintaa tähtijoukkojen ja galaksien fotometrisiä ominaisuuksia yhdistämällä yksittäisten tähtien tuottama säteily, joka saadaan teoreettisista tähtien kehitysmalleista. Valitsemalla sopiva massajakauma syntyville tähdille voidaan muodostaa yksinkertainen tähtipopulaatio, joka koostuu saman ikäisistä ja kemialliselta koostumukseltaan yhtenäisistä tähdistä. Monimutkaisempia tähtipopulaatioita voidaan muodostaa konvoloimalla yksinkertaisten tähtipopulaatioiden luminositeetti jonkin valitun tähtienmuodostushistorian kanssa sekä yhdistämällä näin muodostettuja populaatioita. Tässä työssä tarkastellaan asymptoottisen jättiläishaaran (AGB) tähtien uusien, tarkentuneiden evoluutiomallien vaikutusta populaatiosynteesin tuloksiin niin yksinkertaisten tähtipopulaatioiden kuin galaksien mallinnukseen soveltuvien monimutkaisempien tähtipopulaatioiden kohdalla. Työn päätarkoitus on tuottaa uudistuneisiin malleihin perustuvat populaation massa-luminositeetti -suhteen ja värin väliset relaatiot (MLC-relaatiot). MLC-relaatioita voidaan käyttää populaation massan määrittämiseen sen fotometristen ominaisuuksien (väri, luminositeetti) perusteella. Lisäksi tutkitaan tähtienvälisen pölyn vaikutusta yksinkertaisen spiraaligalaksimallin MLC-relaatioihin. Työssä käytetyt tähtien kehitysmallit perustuvat julkaisuun Marigo et al. (Astronomy & Astrophysics 482, 2008). Havaitaan, että AGB-tähtien vaikutus populaation integroituun luminositeettiin on pieni näkyvillä aallonpituuksilla, mutta merkittävä lähi-infrapuna-alueella. Vaikutus MLC-relaatioihin on vastaavasti merkittävä tarkkailtaessa luminositeettia lähi-infrapunassa sekä käytettäessä värejä, joissa yhdistetään optisia ja lähi-infrapunan kaistoja. Todetaan, että MLC-relaatioiden käyttö lähi-infrapunassa edellyttää tarkentuneen AGB-vaiheen sisällyttämistä populaatiosynteesin malleihin. Tähtienvälisen pölyn vaikutus MLC-relaatioihin todetaan riippuvan käytetystä kaistasta ja väristä, mutta vaikutuksen havaitaan olevan suurin optisen ja lähi-infrapunan väriyhdistelmillä.

Investment risks in Russia: A Finnish perspective

Purpose of this study is to analyze the effect of Russia's economic environment changes in the total return indexes of Finnish companies. The research data consisted of Finnish publicly listed companies, which have made physical investments to Russia, and operating in the area. The study used six different variables to model the Russian operating environment. The data consists of total return indexes of Finnish companies. From those we calculated the monthly mean interval between timeline of 1 January 2000 to 31 December 2009. Sample period is divided into two different parts. Variables impact on companies' total return indices is tested by regression analysis. By F-test we tested significance of model and squared coefficient correlation told us how much model explains from changes. Goodness of the β-coefficient is tested in the model by t-test. The research results shows that the Russian operating environment, or changes in which the active Finnish companies in total return indices. On partial sample periods results were not so significant.

Of milquetoasts and daredevils : personalities in female eiders

Traditionally biologists have often considered individual differences in behaviour or physiology as a nuisance when investigating a population of individuals. These differences have mostly been dismissed as measurement errors or as non-adaptive variation around an adaptive population mean. Recent research, however, challenges this view. While long acknowledged in human personality studies, the importance of individual variation has recently entered into ecological and evolutionary studies in the form of animal personality. The concept of animal personality focuses on consistent differences within and between individuals in behavioural and physiological traits across time and contexts and its ecological and evolutionary consequences. Nevertheless, a satisfactory explanation for the existence of personality is still lacking. Although there is a growing number of explanatory theoretical models, there is still a lack of empirical studies on wild populations showing how traditional life-history tradeoffs can explain the maintenance of variation in personality traits. In this thesis, I first investigate the validity of variation in allostatic load or baseline corticosterone (CORT) concentrations as a measure for differences in individual quality. The association between CORT and quality has recently been summarised under the “CORT-fitness hypothesis”, which states that a general negative relationship between baseline CORT and fitness exists. I then continue to apply the concept of animal personality to depict how the life-history trade-off between survival and fecundity is mediated in incubating female eiders (Somateria mollissima), thereby maintaining variation in behaviour and physiology. To this end, I investigated breeding female eiders from a wild population that breeds in the archipelago around Tvärminne Zoological Station, SW Finland. The field data used was collected from 2008 to 2012. The overall aim of the thesis was to show how differences in personality and stress responsiveness are linked to a life-history context. In the four chapters I examine how the life-history trade-off between survival and fecundity could be resolved depending on consistent individual differences in escape behaviour, stress physiology, individual quality and nest-site selection. First, I corroborated the validity of the “CORT-fitness hypothesis”, by showing that reproductive success is generally negatively correlated with serum and faecal baseline CORT levels. The association between individual quality and baseline CORT is, however, context dependent. Poor body condition was associated with elevated serum baseline CORT only in older breeders, while a larger reproductive investment (clutch mass) was associated with elevated serum baseline CORT among females breeding late in the season. Interestingly, good body condition was associated with elevated faecal baseline CORT levels in late breeders. High faecal baseline CORT levels were positively related to high baseline body temperature, and breeders in poor condition showed an elevated baseline body temperature, but only on open islands. The relationship between stress physiology and individual quality is modulated by breeding experience and breeding phenology. Consequently, the context dependency highlights that this relationship has to be interpreted cautiously. Additionally, I verified if stress responsiveness is related to risk-taking behaviour. Females who took fewer risks (longer flight initiation distance) showed a stronger stress response (measured as an increase in CORT concentration after capture and handling of the bird). However, this association was modulated by breeding experience and body condition, with young breeders and those in poor body condition showing the strongest relationship between risktaking and stress responsiveness. Shy females (longer flight initiation distance) also incubated their clutch for a shorter time. Additionally, I demonstrated that stress responsiveness and predation risk interact with maternal investment and reproductive success. Under high risk of predation, females that incubated a larger clutch showed a stronger stress response. Surprisingly, these females also exhibited higher reproductive success than females with a weaker stress response. Again, these context dependent results suggest that the relationship between stress responsiveness and risk-taking behaviour should not be studied in isolation from individual quality and that stress responsiveness may show adaptive plasticity when individuals are exposed to different predation regimes. Finally, female risk-taking behaviour and stress coping styles were also related to nest-site choice. Less stress responsive females more frequently occupied nests with greater coverage that were farther away from the shoreline. Females nesting in nests with medium cover and farther from the shoreline had higher reproductive success. These results suggest that different personality types are distributed non-randomly in space. In this thesis I was able to demonstrate that personalities and stress coping strategies are persistent individual characteristics, which express measurable effects on fitness. This suggests that those traits are exposed to natural selection and thereby can evolve. Furthermore, individual variation in personality and stress coping strategy is linked to the alternative ways in which animals resolve essential life-history trade-offs.

Comprehensive digital preservation repositories: gaps, and what do we mean by “repository” anyway?

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Simulation of the Interaction Mean Free Path between Neutrons and TRISO Particles

The interaction mean free path between neutrons and TRISO particles is simulated using scripts written in MATLAB to solve the increasing error present with an increase in the packing factor in the reactor physics code Serpent. Their movement is tracked both in an unbounded and in a bounded space. Their track is calculated, depending on the program, linearly directly using the position vectors of the neutrons and the surface equations of all the fuel particles; by dividing the space in multiple subspaces, each of which contain a fraction of the total number of particles, and choosing the particles from those subspaces through which the neutron passes through; or by choosing the particles that lie within an infinite cylinder formed on the movement axis of the neutron. The estimate from the current analytical model, based on an exponential distribution, for the mean free path, utilized by Serpent, is used as a reference result. The results from the implicit model in Serpent imply a too long mean free path with high packing factors. The received results support this observation by producing, with a packing factor of 17 %, approximately 2.46 % shorter mean free path compared to the reference model. This is supported by the packing factor experienced by the neutron, the simulation of which resulted in a 17.29 % packing factor. It was also observed that the neutrons leaving from the surfaces of the fuel particles, in contrast to those starting inside the moderator, do not follow the exponential distribution. The current model, as it is, is thus not valid in the determination of the free path lengths of the neutrons.

Characteristic Approach to Predicting Analysts’ Forecast Errors in the Finnish Market

Extensive literature shows that analysts’ forecasts and recommendations are often biased. Thus, it is important for the financial market to be able to recognize this bias to be able to correctly valuate public companies. This thesis uses characteristic approach, which was introduced by So (2013, pp. 615-640), to forecast analysts’ forecast errors and tests if predictable forecast error is fully incorporated into share prices. Data is collected of listed Finnish companies. Thesis’ timeframe spans over ten years from 2004 to 2013 consisting of 788 firm-years. Although there is earlier evidence that the characteristic approach is able to predict analysts’ forecast errors, no support for this is found in the Finnish market. This thesis contributes to the current knowledge by showing that the characteristic approach does not work universally as such but requires development to work especially in the smaller markets.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Stochastic particle models: mean reversion and burgers dynamics. An application to commodity markets

The aim of this study is to propose a stochastic model for commodity markets linked with the Burgers equation from fluid dynamics. We construct a stochastic particles method for commodity markets, in which particles represent market participants. A discontinuity in the model is included through an interacting kernel equal to the Heaviside function and its link with the Burgers equation is given. The Burgers equation and the connection of this model with stochastic differential equations are also studied. Further, based on the law of large numbers, we prove the convergence, for large N, of a system of stochastic differential equations describing the evolution of the prices of N traders to a deterministic partial differential equation of Burgers type. Numerical experiments highlight the success of the new proposal in modeling some commodity markets, and this is confirmed by the ability of the model to reproduce price spikes when their effects occur in a sufficiently long period of time.