Opaskoirien pentutestin perinnölliset tunnusluvut

Tutkimuksen tarkoituksena oli selvittää Opaskoirakoulun pentutestissä mitattavien ominaisuuksien perinnölliset tunnusluvut sekä niihin vaikuttavat tekijät. Aineisto koostui Opaskoirakoululla vuosina 1988–2008 pentutestin suorittaneista koirista (900 kpl). Suomen Kennelliito ry:stä saatiin sukulaisuusaineisto, johon täydennettiin rekisteriin kuulumattomat koirat. Tutkittavia ominaisuuksia oli 11 kappaletta: käyttäytyminen sylissä, luoksetulo, kontakti, taistelu, alistus, palautuminen, ääniherkkyys, käyttäytyminen pöydällä, seuraaminen, toimintakyky ja hermorakenne. Kaikki ominaisuudet arvostellaan pentutestissä valmiiden käyttäytymismallien mukaisesti. Aineiston esikäsittelyyn ja alustaviin analyyseihin käytettiin Microsoft Office Excel 2003-ohjelmaa sekä WSYS-L ja XWSYS-ohjelmistoja. Kiinteiden tekijöiden luokitteluun ja merkitsevyyden testaamiseen käytettiin WSYS-L ja XWSYS-ohjelmistoa. Varianssikomponentit sekä periytymisasteet laskettiin Restricted Maximum Likelihood (REML)-menetelmällä käyttäen VCE6-ohjelmistoa Tutkittujen ominaisuuksien periytymisasteiden arviot olivat alhaisia tai keskinkertaisia (h2= 0,07-0,39). Korkeimmat periytymisasteiden arviot olivat ominaisuuksilla alistus (0,39), toimintakyky (0,32) ja kontakti (0,31). Ominaisuuksien väliset geneettiset korrelaatiot olivat pääosin positiivisia. Poikkeuksen muodosti ominaisuus alistus, joka oli negatiivisesti korreloitunut palautumisen (-0,47) ja seuraamisen (-0,64) kanssa. Osa ominaisuuksista oli erittäin voimakkaasti korreloituneita (r > 0,8). Fenotyyppiset korrelaatiot vaihtelivat välillä 0,11–0,73 ja olivat geneettisiä korrelaatioita matalampia. Tämän tutkimuksen perusteella ominaisuuksissa käyttäytyminen sylissä, luoksetulo, kontakti, taistelu, alistus, ääniherkkyys, käyttäytyminen pöydällä ja toimintakyky on geneettistä vaihtelua ja sen perusteella niitä on mahdollista muuttaa haluttuun suuntaan jalostuksen avulla.

Männyn neulaskadon arviointi laserkeilauksella

Leaf and needle biomasses are key factors in forest health. Insects that feed on needles cause growth losses and tree mortality. Insect outbreaks in Finnish forests have increased rapidly during the last decade and due to climate change the damages are expected to become more serious. There is a need for cost-efficient methods for inventorying these outbreaks. Remote sensing is a promising means for estimating forests and damages. The purpose of this study is to investigate the usability of airborne laser scanning in estimating Scots pine defoliation caused by the common pine sawfly (Diprion pini L.). The study area is situated in Ilomantsi district, eastern Finland. Study materials included high-pulse airborne laser scannings from July and October 2008. Reference data consisted of 90 circular field plots measured in May-June 2009. Defoliation percentage on these field plots was estimated visually. The study was made on plot-level and methods used were linear regression, unsupervised classification, Maximum likelihood method, and stepwise linear regression. Field plots were divided in defoliation classes in two different ways: When divided in two classes the defoliation percentages used were 0–20 % and 20–100 % and when divided in four classes 0–10 %, 10–20 %, 20–30 % and 30–100 %. The results varied depending on method and laser scanning. In the first laser scanning the best results were obtained with stepwise linear regression. The kappa value was 0,47 when using two classes and 0,37 when divided in four classes. In the second laser scanning the best results were obtained with Maximum likelihood. The kappa values were 0,42 and 0,37, correspondingly. The feature that explained defoliation best was vegetation index (pulses reflected from height > 2m / all pulses). There was no significant difference in the results between the two laser scannings so the seasonal change in defoliation could not be detected in this study.

Measurement of the Single-Top-Quark Production Cross Section at CDF

We report a measurement of the single top quark production cross section in 2.2 ~fb-1 of p-pbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events are classified as signal-like by three parallel analyses which use likelihood, matrix element, and neural network discriminants. These results are combined in order to improve the sensitivity. We observe a signal consistent with the standard model prediction, but inconsistent with the background-only model by 3.7 standard deviations with a median expected sensitivity of 4.9 standard deviations. We measure a cross section of 2.2 +0.7 -0.6(stat+sys) pb, extract the CKM matrix element value |V_{tb}|=0.88 +0.13 -0.12 (stat+sys) +- 0.07(theory), and set the limit |V_{tb}|>0.66 at the 95% C.L.

Top Quark Mass Measurement in the lepton+jets Channel Using a Matrix Element Method and in situ Jet Energy Calibration

A precision measurement of the top quark mass m_t is obtained using a sample of ttbar events from ppbar collisions at the Fermilab Tevatron with the CDF II detector. Selected events require an electron or muon, large missing transverse energy, and exactly four high-energy jets, at least one of which is tagged as coming from a b quark. A likelihood is calculated using a matrix element method with quasi-Monte Carlo integration taking into account finite detector resolution and jet mass effects. The event likelihood is a function of m_t and a parameter DJES to calibrate the jet energy scale /in situ/. Using a total of 1087 events, a value of m_t = 173.0 +/- 1.2 GeV/c^2 is measured.

Top quark mass measurement in the lepton plus jets channel using a modified matrix element method

We report a measurement of the top quark mass, m_t, obtained from ppbar collisions at sqrt(s) = 1.96 TeV at the Fermilab Tevatron using the CDF II detector. We analyze a sample corresponding to an integrated luminosity of 1.9 fb^-1. We select events with an electron or muon, large missing transverse energy, and exactly four high-energy jets in the central region of the detector, at least one of which is tagged as coming from a b quark. We calculate a signal likelihood using a matrix element integration method, with effective propagators to take into account assumptions on event kinematics. Our event likelihood is a function of m_t and a parameter JES that determines /in situ/ the calibration of the jet energies. We use a neural network discriminant to distinguish signal from background events. We also apply a cut on the peak value of each event likelihood curve to reduce the contribution of background and badly reconstructed events. Using the 318 events that pass all selection criteria, we find m_t = 172.7 +/- 1.8 (stat. + JES) +/- 1.2 (syst.) GeV/c^2.

Measurement of the tt̅ cross section in pp̅ collisions at √s=1.96 TeV using dilepton events with a lepton plus track selection

This paper reports a measurement of the cross section for the pair production of top quarks in ppbar collisions at sqrt(s) = 1.96 TeV at the Fermilab Tevatron. The data was collected from the CDF II detector in a set of runs with a total integrated luminosity of 1.1 fb^{-1}. The cross section is measured in the dilepton channel, the subset of ttbar events in which both top quarks decay through t -> Wb -> l nu b where l = e, mu, or tau. The lepton pair is reconstructed as one identified electron or muon and one isolated track. The use of an isolated track to identify the second lepton increases the ttbar acceptance, particularly for the case in which one W decays as W -> tau nu. The purity of the sample may be further improved at the cost of a reduction in the number of signal events, by requiring an identified b-jet. We present the results of measurements performed with and without the request of an identified b-jet. The former is the first published CDF result for which a b-jet requirement is added to the dilepton selection. In the CDF data there are 129 pretag lepton + track candidate events, of which 69 are tagged. With the tagging information, the sample is divided into tagged and untagged sub-samples, and a combined cross section is calculated by maximizing a likelihood. The result is sigma_{ttbar} = 9.6 +/- 1.2 (stat.) -0.5 +0.6 (sys.) +/- 0.6 (lum.) pb, assuming a branching ratio of BR(W -> ell nu) = 10.8% and a top mass of m_t = 175 GeV/c^2.

Measurement of the top quark mass at CDF using the “neutrino ϕ weighting” template method on a lepton plus isolated track sample

We present a measurement of the top quark mass with t-tbar dilepton events produced in p-pbar collisions at the Fermilab Tevatron $\sqrt{s}$=1.96 TeV and collected by the CDF II detector. A sample of 328 events with a charged electron or muon and an isolated track, corresponding to an integrated luminosity of 2.9 fb$^{-1}$, are selected as t-tbar candidates. To account for the unconstrained event kinematics, we scan over the phase space of the azimuthal angles ($\phi_{\nu_1},\phi_{\nu_2}$) of neutrinos and reconstruct the top quark mass for each $\phi_{\nu_1},\phi_{\nu_2}$ pair by minimizing a $\chi^2$ function in the t-tbar dilepton hypothesis. We assign $\chi^2$-dependent weights to the solutions in order to build a preferred mass for each event. Preferred mass distributions (templates) are built from simulated t-tbar and background events, and parameterized in order to provide continuous probability density functions. A likelihood fit to the mass distribution in data as a weighted sum of signal and background probability density functions gives a top quark mass of $165.5^{+{3.4}}_{-{3.3}}$(stat.)$\pm 3.1$(syst.) GeV/$c^2$.

Top quark mass measurement in the tt̅ all hadronic channel using a matrix element technique in pp̅ collisions at √s=1.96 TeV

We present a measurement of the top quark mass in the all-hadronic channel (\tt $\to$ \bb$q_{1}\bar{q_{2}}q_{3}\bar{q_{4}}$) using 943 pb$^{-1}$ of \ppbar collisions at $\sqrt {s} = 1.96$ TeV collected at the CDF II detector at Fermilab (CDF). We apply the standard model production and decay matrix-element (ME) to $\ttbar$ candidate events. We calculate per-event probability densities according to the ME calculation and construct template models of signal and background. The scale of the jet energy is calibrated using additional templates formed with the invariant mass of pairs of jets. These templates form an overall likelihood function that depends on the top quark mass and on the jet energy scale (JES). We estimate both by maximizing this function. Given 72 observed events, we measure a top quark mass of 171.1 $\pm$ 3.7 (stat.+JES) $\pm$ 2.1 (syst.) GeV/$c^{2}$. The combined uncertainty on the top quark mass is 4.3 GeV/$c^{2}$.

Essays on Stock Options, Incentives, and Managerial Action

Executive compensation and managerial behavior have received an increasing amount of attention in the financial economics literature since the mid 1970s. The purpose of this thesis is to extend our understanding of managerial compensation, especially how stock option compensation is linked to the actions undertaken by the management. Furthermore, managerial compensation is continuously and heatedly debated in the media and an emerging consensus from this discussion seems to be that there still exists gaps in our knowledge of optimal contracting. In Finland, the first executive stock options were introduced in the 1980s and throughout the last 15 years it has become increasingly popular for Finnish listed firms to use this type of managerial compensation. The empirical work in the thesis is conducted using data from Finland, in contrast to most previous studies that predominantly use U.S. data. Using Finnish data provides insight of how market conditions affect compensation and managerial action and provides an opportunity to explore what parts of the U.S. evidence can be generalized to other markets. The thesis consists of four essays. The first essay investigates the exercise policy of the executive stock option holders in Finland. In summary, Essay 1 contributes to our understanding of the exercise policies by examining both the determinants of the exercise decision and the markets reaction to the actual exercises. The second essay analyzes the factors driving stock option grants using data for Finnish publicly listed firms. Several agency theory based variables are found to have have explanatory power on the likelihood of a stock option grant. Essay 2 also contributes to our understanding of behavioral factors, such as prior stock return, as determinants of stock option compensation. The third essay investigates the tax and stock option motives for share repurchases and dividend distributions. We document strong support for the tax motive for share repurchases. Furthermore, we also analyze the dividend distribution decision in companies with stock options and find a significant difference between companies with and without dividend protected options. We thus document that the cutting of dividends found in previous U.S. studies can be avoided by dividend protection. In the fourth essay we approach the puzzle of negative skewness in stock returns from an altogether different angle than in previous studies. We suggest that negative skewness in stock returns is generated by management disclosure practices and find proof for this. More specifically, we find that negative skewness in daily returns is induced by returns for days when non-scheduled firm specific news is disclosed.

Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

Factors Driving Stock Option Grants - Empirical Evidence from Finland

This study contributes to the executive stock option literature by looking at factors driving the introduction of such a compensation form on a firm level. Using a discrete decision model I test the explanatory power of several agency theory based variables and find strong support for predictability of the form of executive compensation. Ownership concentration and liquidity are found to have a significant negative effect on the probability of stock option adoption. Furtermore, I find evidence of CEO ownership, institutional ownership, investment intensity, and historical market return having a significant and a positive relationship to the likelihood of adopting a executive stock option program.

Bootstrap and Fast Double Bootstrap Tests of Cointegration Rank with Financial Time Series

The likelihood ratio test of cointegration rank is the most widely used test for cointegration. Many studies have shown that its finite sample distribution is not well approximated by the limiting distribution. The article introduces and evaluates by Monte Carlo simulation experiments bootstrap and fast double bootstrap (FDB) algorithms for the likelihood ratio test. It finds that the performance of the bootstrap test is very good. The more sophisticated FDB produces a further improvement in cases where the performance of the asymptotic test is very unsatisfactory and the ordinary bootstrap does not work as well as it might. Furthermore, the Monte Carlo simulations provide a number of guidelines on when the bootstrap and FDB tests can be expected to work well. Finally, the tests are applied to US interest rates and international stock prices series. It is found that the asymptotic test tends to overestimate the cointegration rank, while the bootstrap and FDB tests choose the correct cointegration rank.

The Power of Bootstrap Tests of Cointegration Rank with Financial Time Series

Bootstrap likelihood ratio tests of cointegration rank are commonly used because they tend to have rejection probabilities that are closer to the nominal level than the rejection probabilities of the correspond- ing asymptotic tests. The e¤ect of bootstrapping the test on its power is largely unknown. We show that a new computationally inexpensive procedure can be applied to the estimation of the power function of the bootstrap test of cointegration rank. The bootstrap test is found to have a power function close to that of the level-adjusted asymp- totic test. The bootstrap test estimates the level-adjusted power of the asymptotic test highly accurately. The bootstrap test may have low power to reject the null hypothesis of cointegration rank zero, or underestimate the cointegration rank. An empirical application to Euribor interest rates is provided as an illustration of the findings.

Tests for Cointegration Rank and the Initial Condition

Many economic events involve initial observations that substantially deviate from long-run steady state. Initial conditions of this type have been found to impact diversely on the power of univariate unit root tests, whereas the impact on multivariate tests is largely unknown. This paper investigates the impact of the initial condition on tests for cointegration rank. We compare the local power of the widely used likelihood ratio (LR) test with the local power of a test based on the eigenvalues of the companion matrix. We find that the power of the LR test is increasing in the magnitude of the initial condition, whereas the power of the other test is decreasing. The behaviour of the tests is investigated in an application to price convergence.

What Determines Stock Option Contract Design?

This paper analyzes factors driving the design of stock option plans for Finnish firms. We examine determinants of the scope of plans, exercise price, target group, and dividend protection. The scope is found to be negatively related to Tobin’s Q and positively related to proxies for monitoring costs. The scope is also greater in broad-based plans, and in plans with dividend protection. Prior stock return is found to be negatively related to the size of the premium (out-of-the-moneyness), whereas dividend protection increases the premium. The results also suggest that investment intensity, cash flow, and monitoring costs are associated with the likelihood of granting premium (out-of-the-money) stock options. Furthermore, the likelihood of granting broad-based plans is increasing in institutional ownership and cash flow constraints, and decreasing in firm size. Broad-based plans are also more likely among firms in growth industries. We find support that the likelihood of dividend protection is decreasing in foreign ownership. In addition, firms paying zero-dividends are less likely to include dividend protection, whereas higher unsystematic risk is associated with a greater likelihood of including dividend protection.