Technology-related peso problems in stock returns

Although empirical evidence suggests the contrary, many asset pricing models assume stock returns to be symmetrically distributed. In this paper it is argued that the occurrence of negative jumps in a firm's future earnings and, consequently, in its stock price, is positively related to the level of network externalities in the firm's product market. If the ex post frequency of these negative jumps in a sample does not equal the ex ante assessed probability of occurrence, the sample is subject to a peso problem. The hypothesis is tested for by regressing the skewness coefficient of a firm’s realised stock return distribution on the firm’s R&D intensity, i.e. the ratio of the firm’s research and development expenditure to its net sales. The empirical results support the technology-related peso problem hypothesis. In samples subject to such a peso problem, the returns are biased up and the variance is biased down.

The Influence of World Factors on Finnish Stock Market Volatility

This paper investigates to what extent the volatility of Finnish stock portfolios is transmitted through the "world volatility". We operationalize the volatility processes of Finnish leverage, industry, and size portfolio returns by asymmetric GARCH specifications according to Glosten et al. (1993). We use daily return data for January, 2, 1987 to December 30, 1998. We find that the world shock significantly enters the domestic models, and that the impact has increased over time. This applies also for the variance ratios, and the correlations to the world. The larger the firm, the larger is the world impact. The conditional variance is higher during recessions. The asymmetry parameter is surprisingly non-significant, and the leverage hypothesis cannot be verified. The return generating process of the domestic portfolio returns does usually not include the world information set, thus indicating that the returns are generated by a segmented conditional asset pricing model.

An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions

This paper uses the Value-at-Risk approach to define the risk in both long and short trading positions. The investigation is done on some major market indices(Japanese, UK, German and US). The performance of models that takes into account skewness and fat-tails are compared to symmetric models in relation to both the specific model for estimating the variance, and the distribution of the variance estimate used as input in the VaR estimation. The results indicate that more flexible models not necessarily perform better in predicting the VaR forecast; the reason for this is most probably the complexity of these models. A general result is that different methods for estimating the variance are needed for different confidence levels of the VaR, and for the different indices. Also, different models are to be used for the left respectively the right tail of the distribution.

Short-Horizon Asymmetric Mean-Reversion and Overreactions: Evidence from the Nordic Stock Markets

This paper examines the asymmetric behavior of conditional mean and variance. Short-horizon mean-reversion behavior in mean is modeled with an asymmetric nonlinear autoregressive model, and the variance is modeled with an Exponential GARCH in Mean model. The results of the empirical investigation of the Nordic stock markets indicates that negative returns revert faster to positive returns when positive returns generally persist longer. Asymmetry in both mean and variance can be seen on all included markets and are fairly similar. Volatility rises following negative returns more than following positive returns which is an indication of overreactions. Negative returns lead to increased variance and positive returns leads even to decreased variance.

Intraday and Weekend Volatility Patterns- Implications for Option Pricing

This study examines the intraday and weekend volatility on the German DAX. The intraday volatility is partitioned into smaller intervals and compared to a whole day’s volatility. The estimated intraday variance is U-shaped and the weekend variance is estimated to 19 % of a normal trading day. The patterns in the intraday and weekend volatility are used to develop an extension to the Black and Scholes formula to form a new time basis. Calendar or trading days are commonly used for measuring time in option pricing. The Continuous Time using Discrete Approximations model (CTDA) developed in this study uses a measure of time with smaller intervals, approaching continuous time. The model presented accounts for the lapse of time during trading only. Arbitrage pricing suggests that the option price equals the expected cost of hedging volatility during the option’s remaining life. In this model, time is allowed to lapse as volatility occurs on an intraday basis. The measure of time is modified in CTDA to correct for the non-constant volatility and to account for the patterns in volatility.

Modified linear prediction method for directions of arrival estimation of narrow-band plane waves

A modified linear prediction (MLP) method is proposed in which the reference sensor is optimally located on the extended line of the array. The criterion of optimality is the minimization of the prediction error power, where the prediction error is defined as the difference between the reference sensor and the weighted array outputs. It is shown that the L2-norm of the least-squares array weights attains a minimum value for the optimum spacing of the reference sensor, subject to some soft constraint on signal-to-noise ratio (SNR). How this minimum norm property can be used for finding the optimum spacing of the reference sensor is described. The performance of the MLP method is studied and compared with that of the linear prediction (LP) method using resolution, detection bias, and variance as the performance measures. The study reveals that the MLP method performs much better than the LP technique.

Models of Dispersal and Diversification

Ecology and evolutionary biology is the study of life on this planet. One of the many methods applied to answering the great diversity of questions regarding the lives and characteristics of individual organisms, is the utilization of mathematical models. Such models are used in a wide variety of ways. Some help us to reason, functioning as aids to, or substitutes for, our own fallible logic, thus making argumentation and thinking clearer. Models which help our reasoning can lead to conceptual clarification; by expressing ideas in algebraic terms, the relationship between different concepts become clearer. Other mathematical models are used to better understand yet more complicated models, or to develop mathematical tools for their analysis. Though helping us to reason and being used as tools in the craftmanship of science, many models do not tell us much about the real biological phenomena we are, at least initially, interested in. The main reason for this is that any mathematical model is a simplification of the real world, reducing the complexity and variety of interactions and idiosynchracies of individual organisms. What such models can tell us, however, both is and has been very valuable throughout the history of ecology and evolution. Minimally, a model simplifying the complex world can tell us that in principle, the patterns produced in a model could also be produced in the real world. We can never know how different a simplified mathematical representation is from the real world, but the similarity models do strive for, gives us confidence that their results could apply. This thesis deals with a variety of different models, used for different purposes. One model deals with how one can measure and analyse invasions; the expanding phase of invasive species. Earlier analyses claims to have shown that such invasions can be a regulated phenomena, that higher invasion speeds at a given point in time will lead to a reduction in speed. Two simple mathematical models show that analysis on this particular measure of invasion speed need not be evidence of regulation. In the context of dispersal evolution, two models acting as proof-of-principle are presented. Parent-offspring conflict emerges when there are different evolutionary optima for adaptive behavior for parents and offspring. We show that the evolution of dispersal distances can entail such a conflict, and that under parental control of dispersal (as, for example, in higher plants) wider dispersal kernels are optimal. We also show that dispersal homeostasis can be optimal; in a setting where dispersal decisions (to leave or stay in a natal patch) are made, strategies that divide their seeds or eggs into fractions that disperse or not, as opposed to randomized for each seed, can prevail. We also present a model of the evolution of bet-hedging strategies; evolutionary adaptations that occur despite their fitness, on average, being lower than a competing strategy. Such strategies can win in the long run because they have a reduced variance in fitness coupled with a reduction in mean fitness, and fitness is of a multiplicative nature across generations, and therefore sensitive to variability. This model is used for conceptual clarification; by developing a population genetical model with uncertain fitness and expressing genotypic variance in fitness as a product between individual level variance and correlations between individuals of a genotype. We arrive at expressions that intuitively reflect two of the main categorizations of bet-hedging strategies; conservative vs diversifying and within- vs between-generation bet hedging. In addition, this model shows that these divisions in fact are false dichotomies.

Random matrices: Universality of ESDs and the circular law

Given an n x n complex matrix A, let mu(A)(x, y) := 1/n vertical bar{1 <= i <= n, Re lambda(i) <= x, Im lambda(i) <= y}vertical bar be the empirical spectral distribution (ESD) of its eigenvalues lambda(i) is an element of C, i = l, ... , n. We consider the limiting distribution (both in probability and in the almost sure convergence sense) of the normalized ESD mu(1/root n An) of a random matrix A(n) = (a(ij))(1 <= i, j <= n), where the random variables a(ij) - E(a(ij)) are i.i.d. copies of a fixed random variable x with unit variance. We prove a universality principle for such ensembles, namely, that the limit distribution in question is independent of the actual choice of x. In particular, in order to compute this distribution, one can assume that x is real or complex Gaussian. As a related result, we show how laws for this ESD follow from laws for the singular value distribution of 1/root n A(n) - zI for complex z. As a corollary, we establish the circular law conjecture (both almost surely and in probability), which asserts that mu(1/root n An) converges to the uniform measure on the unit disc when the a(ij) have zero mean.

Molecular conformation of alamethicin in dimethylsulfoxide solution A two-dimensional n.m.r. study

The solution conformation of alamethicin, a 20-residue antibiotic peptide, has been investigated using two-dimensional n.m.r. spectroscopy. Complete proton resonance assignments of this peptide have been carried out using COSY, SUPERCOSY, RELAY COSY and NOESY two-dimensional spectroscopies. Observation of a large number of nuclear Overhauser effects between sequential backbone amide protons, between backbone amide protons and CβH protons of preceding residues and extensive intramolecular hydrogen bonding patterns of NH protons has established that this polypeptide is in a largely helical conformation. This result is in conformity with earlier reported solid state X-ray results and a recent n.m.r. study in methanol solution (Esposito et al. (1987) Biochemistry26, 1043-1050) but is at variance with an earlier study which favored an extended conformation for the C-terminal half of alamethicin (Bannerjee et al.

Microfoundations of HRM effects: Individual and Collective Attitudes and Performance

Previous research on Human Resource Management (HRM) has focused extensively on the potential relationships between the use of HRM practices and organizational performance. Extant research in HRM has been based on the underlying assumption that HRM practices can enhance organizational performance through their impact on positive employee attitudes and performance, that is, employee reactions to HRM. At the current state of research however, it remains unclear how employees come to perceive and react to HRM practices and to what extent employees in organizations, units and teams react to such practices in similar or widely different ways. In fact, recent HRM studies indicate that employee reactions to HRM may be far less homogeneous than assumed. This raises the question of whether or not the linkage between HRM and organizational outcomes can be explained by employee reactions in terms of attitudes and performance, if these reactions are largely idiosyncratic. Accordingly, this thesis aims to shed light on the processes that shape individuals’ reactions to HRM practices and how these processes may influence the variance or sharedness in such reactions among employees in organizations, units and teams. By theoretically developing and empirically examining the effects of employee perceptions of HRM practices from the perspective of ‘HRM as signaling’ and psychological contract theory, the main contributions of this thesis focus on the following research questions: i) How employee perceptions of the HRM practices relate to individual and collective employee attitudes and performance. ii) How employee perceptions of HRM practices relates to variance in employee attitudes and performance. iii) How collective employee performance mediates the relationship between employee perceptions of HRM practices and organizational performance. Regarding the first research questions the findings indicate that individuals do respond positively to HRM practices by adjusting their felt obligations towards the employer. This finding is in line with the idea of HRM as a signaling device where each HRM practice, implicitly or explicitly, sends signals to employees about promised rewards (inducements) and behaviors (obligations) expected in return. The relationship was also confirmed at the group level of analysis. What is more, variance was found to play an important role in that employee groups with more similar perceptions about the HRM system displayed a stronger relationship between HRM and employee obligations. Concerning the second question the findings were somewhat contradictory in that a strong HRM system was found negatively related to variance in employee performance but not employee obligations. Regarding the third question, the findings confirmed linkages between the HRM system and organizational performance at the group level and the HRM system and employee performance at the individual level. Also, the entire chain of links from the HRM system through variance in employee performance, and further through the level of employee performance to organizational performance was significant.

Determinants of Cognitive Impairment in Old Age and Their Genetic Architecture

Cognitive health is of central importance for independent and balanced old age, while memory disorders represent the leading cause of intensive and long-term care among the Finnish elderly. The aims of this study were to analyse the effect of height, body mass index, weight change, metabolic conditions and coffee drinking in midlife on cognitive performance in old age among a sample of 2606 Finnish twins aged 65 years or older who had participated in a telephone interview to assess their cognitive status. Since coffee drinking associates with several metabolic conditions and Finns are known to be the greatest consumers of coffee in the world, the heritability and stability of coffee drinking was analysed in the whole Older Finnish Twin Cohort (n=10716). In order to investigate the association between height and cognitive performance in a population with more supportive childhood living conditions, a total of 2161 Danish twins were included in this study. A greater height was found to clearly associate with better cognitive performance in Finnish subjects, but less so among the Danish sample, which may reflect the childhood environmental differences between these cohorts. In the Finnish subjects, there was greater variance in cognitive performance among shorter subjects, and environmental factors were found to play a greater role in their cognitive performance, whereas the cognitive performance of taller participants was mainly explained by genetic factors. Midlife metabolic variables that were found to be significantly associated with a poorer cognitive performance in old age included a higher body mass index and three metabolic conditions: cardiovascular disease, hypertension and, most significantly of all, diabetes. Moreover, both weight gain and loss, even to a lesser degree than suggested previously, were found to be associated with poorer cognition. Furthermore, evidence of a causal relationship between midlife cardiovascular disease and cognitive performance in old age was demonstrated among discordant twin pairs. Conversely, no effect of coffee drinking in midlife on cognitive performance in old age was observed, although coffee drinking was demonstrated to be stable in the study population. The heritability of coffee drinking was found to differ across sexes and age groups, being 51% in men and 52% in women in the whole study population. This study supports the contention that cognitive performance in old age reflects the effects of multiple genetic and environmental exposures, including their complex interactions during the life-span. The demonstrated associations and evidence of a causal pathway between potentially preventable exposures and poorer cognitive performance highlight the importance of preventive medicine.

Voltage and Temperature Aware Statistical Leakage Analysis Framework Using Artificial Neural Networks

Artificial neural networks (ANNs) have shown great promise in modeling circuit parameters for computer aided design applications. Leakage currents, which depend on process parameters, supply voltage and temperature can be modeled accurately with ANNs. However, the complex nature of the ANN model, with the standard sigmoidal activation functions, does not allow analytical expressions for its mean and variance. We propose the use of a new activation function that allows us to derive an analytical expression for the mean and a semi-analytical expression for the variance of the ANN-based leakage model. To the best of our knowledge this is the first result in this direction. Our neural network model also includes the voltage and temperature as input parameters, thereby enabling voltage and temperature aware statistical leakage analysis (SLA). All existing SLA frameworks are closely tied to the exponential polynomial leakage model and hence fail to work with sophisticated ANN models. In this paper, we also set up an SLA framework that can efficiently work with these ANN models. Results show that the cumulative distribution function of leakage current of ISCAS'85 circuits can be predicted accurately with the error in mean and standard deviation, compared to Monte Carlo-based simulations, being less than 1% and 2% respectively across a range of voltage and temperature values.

Kiinnostusta vai ahdistusta? : Opettajaksi opiskelevien akateemiset tunteet, motivaatio ja opiskelun ongelmat suhteessa hyvinvointiin ja menestykseen aktivoivalla luentokurssilla

Previous studies indicate that positive learning experiences are related to academic achievement as well as to well-being. On the other hand, emotional and motivational problems in studying may pose a risk for both academic achievement and well-being. Thus, emotions and motivation have an increasing role in explaining university students learning and studying. The relations between emotions, motivation, study success and well-being have been less frequently studied. The aim of this study was to investigate what kind of academic emotions, motivational factors and problems in studying students experienced five days before an exam of an activating lecture course, and the relations among these factors as well as their relation to self-study time and study success. Furthermore, the effect of all these factors on well-being, flow experience and academic achievement was examined. The term academic emotion was defined as emotion experienced in academic settings and related to studying. In the present study the theoretical background to motivational factors was based on thinking strategies and attributions, flow experience and task value. Problems in studying were measured in terms of exhaustion, anxiety, stress, lack of interest, lack of self-regulation and procrastination. The data were collected in December 2009 in an activating educational psychology lecture course by using a questionnaire. The participants (n=107) were class and kindergarten teacher students from the University of Helsinki. Most of them were first year students. The course grades were also gathered. Correlations and stepwise regression analysis were carried out to find out the factors that were related to or explained study success. The clusters that presented students´ problems in studying as well as thinking strategies and attributions, were found through hierarchical cluster analysis. K-means cluster analysis was used to form the final groups. One-way analysis of variance, Kruskal-Wallis test and crosstabs were conducted to see whether the students in different clusters varied in terms of study success, academic emotions, task value, flow, and background variables. The results indicated that academic emotions measured five days before the exam explained about 30 % of the variance of the course grade; exhaustion and interest positively, and anxiety negatively. In addition, interest as well as the self-study time best explained study success on the course. The participants were classified into three clusters according to their problems in studying as well as their thinking strategies and attributions: 1) ill-being, 2) carefree, and 3) committed and optimistic students. Ill-being students reported most negative emotions, achieved the worst grades, experienced anxiety rather than flow and were also the youngest. Carefree students, on the other hand, expressed the least negative emotions and spent the least time on self-studying, and like committed students, experienced flow. In addition, committed students reported positive emotions the most often and achieved the best grades on the course. In the future, more in-depth understanding how and why especially young first year students experience their studying hard is needed, because early state of the studies is shown to predict later study success.

Productive coexistence and gain in agroforestry systems.

Productive coexistence and coexistence gain of populations were studied using nine years' data from field experiments of Taxodium ascendens-intercrop systems in Lixiahe, Jiangsu Province, China. A theoretical framework for productive coexistence in agroforestry was developed. Interaction patterns between trees and intercrops were presented within this framework. A model framework was developed to describe the coexistence gain and interaction of populations in T. ascendens-intercrop systems. Facilitation and resource sharing were identified as main contribution to the advantage of species combination in agroforestry. The model of population interaction developed in the present study was accepted for describing the interaction of populations in T. ascendens-intercrop systems, because it explained a high proportion of the variance of experimental data and fitted well the observations in most intercropping types. The model developed in the present study provides flexibility for describing different patterns of intra- and inter-specific interactions. Model coefficients were applied to the determination of the ecological compatibility of species. Managed T. ascendens-intercrop systems were advantageous as compared to a monoculture of trees or arable crops. In T. ascendens stands up to the age of three, arable crops contributed about 50-80 % of the total biomass yield of agroforestry. The diameter or height growth of T. ascendens was not significantly influenced by intercrops, indicating that intercropping under trees produced extra yields but did not depress the tree growth. When the trees were young (during the first three years), T. ascendens did not depress the crop yields, and a land equivalent ratio greater than unity was obtained together with a high yield of both components. The diameter and height of the trees were similar in four spacing configurations with an equal number of trees per hectare up to the age of eight, but wider between-rows open range were beneficial for the intercrops. The relationship between open-ranges and species coexistence was also analysed and the distribution of soil nutrients studied.

Measurement of acceleration while walking as an automated method for gait assessment in dairy cattle

The aims were to determine whether measures of acceleration of the legs and back of dairy cows while they walk could help detect changes in gait or locomotion associated with lameness and differences in the walking surface. In 2 experiments, 12 or 24 multiparous dairy cows were fitted with five 3-dimensional accelerometers, 1 attached to each leg and 1 to the back, and acceleration data were collected while cows walked in a straight line on concrete (experiment 1) or on both concrete and rubber (experiment 2). Cows were video-recorded while walking to assess overall gait, asymmetry of the steps, and walking speed. In experiment 1, cows were selected to maximize the range of gait scores, whereas no clinically lame cows were enrolled in experiment 2. For each accelerometer location, overall acceleration was calculated as the magnitude of the 3-dimensional acceleration vector and the variance of overall acceleration, as well as the asymmetry of variance of acceleration within the front and rear pair of legs. In experiment 1, the asymmetry of variance of acceleration in the front and rear legs was positively correlated with overall gait and the visually assessed asymmetry of the steps (r ≥0.6). Walking speed was negatively correlated with the asymmetry of variance of the rear legs (r=−0.8) and positively correlated with the acceleration and the variance of acceleration of each leg and back (r ≥0.7). In experiment 2, cows had lower gait scores [2.3 vs. 2.6; standard error of the difference (SED)=0.1, measured on a 5-point scale] and lower scores for asymmetry of the steps (18.0 vs. 23.1; SED=2.2, measured on a continuous 100-unit scale) when they walked on rubber compared with concrete, and their walking speed increased (1.28 vs. 1.22m/s; SED=0.02). The acceleration of the front (1.67 vs. 1.72g; SED=0.02) and rear (1.62 vs. 1.67g; SED=0.02) legs and the variance of acceleration of the rear legs (0.88 vs. 0.94g; SED=0.03) were lower when cows walked on rubber compared with concrete. Despite the improvements in gait score that occurred when cows walked on rubber, the asymmetry of variance of acceleration of the front leg was higher (15.2 vs. 10.4%; SED=2.0). The difference in walking speed between concrete and rubber correlated with the difference in the mean acceleration and the difference in the variance of acceleration of the legs and back (r ≥0.6). Three-dimensional accelerometers seem to be a promising tool for lameness detection on farm and to study walking surfaces, especially when attached to a leg.