Novel Regression Methods For Spectral Data

Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i

The effect of dynamic capabilities on operational-level innovation – Empirical study in magazine publishing industry

This master’s thesis aims to examine the relationship between dynamic capabilities and operational-level innovations. In addition, measures for the concept of dynamic capabilities are developed. The study was executed in the magazine publishing industry which is considered favourable for examining dynamic capabilities, since the sector is characterized by rapid change. As a basis for the study and the measure development, a literary review was conducted. Data for the empirical section was gathered by a survey targeted to chief-editors of Finnish consumer magazines. The relationship between dynamic capabilities and innovation was examined by multiple linear regression. The results indicate that dynamic capabilities have effect on the emergence of radical innovations. Environmental dynamism’s effect on radical innovations was not detected. Also, dynamic capabilities’ effect on innovation was not greater in turbulent operating environment.

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.