Vinouden huomioiva arvopapereiden hinnoittelumalli ja sen empiirinen testaaminen Suomen markkinoilla

Tutkimuksen tarkoituksena on tutkia osaketuottojen jakauman vinoutta ja sen mahdollisia vaikutuksia osakkeiden hinnoitteluun Suomen markkinoilla. Aineistona käytetään kuutta portfoliota jotka on muodostettu Suomen markkinoilla noteerattavista osakkeista ajanjaksolla 1.1.1987–31.12.2004. Osakkeet on jaettu portfolioihin markkina-arvon mukaan. Empiiriset tulokset osoittavat, että osaketuotot Suomen markkinoilla ovat positiivisesti vinoja mutta pääosin eivät merkitsevästi. Teoreettisen taustan perusteella olisi ollut odotettavaa, että vinoutta olisi ollut enemmän. Regressioanalyysillä ja kahta artikkelia replikoiden tutkittiin perinteisen ja vinouden sisältäviä CAPM-malleja. Odotettavissa oli, että perinteinen CAPM-malli suoriutuu huonommin kuin vinouden sisältävä. Regressio-analyysillä testatessa molemmat mallit suoriutuivat hyvin tuottojen selittämisessä, mutta vakiotermien perusteella kolmimomenttinen malli suoriutuisi paremmin. Regressiomallin ja artikkelin perusteella saadut betat olivat yhteneväisiä. Regressiomallin ja artikkelin perusteella saaduissa gam-moissa oli kuitenkin eroja ja niiden perusteella ei voida tehdä johtopäätöksiä. Regressiomalli näyttäisi kuitenkin huomioivan vinouden.

An outcome and cost analysis of anal fistula plug insertion vs endorectal advancement flap for complex anal fistulae.

AIM: The study aimed to compare the rate of success and cost of anal fistula plug (AFP) insertion and endorectal advancement flap (ERAF) for anal fistula. METHOD: Patients receiving an AFP or ERAF for a complex single fistula tract, defined as involving more than a third of the longitudinal length of of the anal sphincter, were registered in a prospective database. A regression analysis was performed of factors predicting recurrence and contributing to cost. RESULTS: Seventy-one patients (AFP 31, ERAF 40) were analysed. Twelve (39%) recurrences occurred in the AFP and 17 (43%) in the ERAF group (P = 1.00). The median length of stay was 1.23 and 2.0 days (P < 0.001), respectively, and the mean cost of treatment was euro5439 ± euro2629 and euro7957 ± euro5905 (P = 0.021), respectively. On multivariable analysis, postoperative complications, underlying inflammatory bowel disease and fistula recurring after previous treatment were independent predictors of de novo recurrence. It also showed that length of hospital stay ≤ 1 day to be the most significant independent contributor to lower cost (P = 0.023). CONCLUSION: Anal fistula plug and ERAF were equally effective in treating fistula-in-ano, but AFP has a mean cost saving of euro2518 per procedure compared with ERAF. The higher cost for ERAF is due to a longer median length of stay.

Measuring individuals' response quality in self-administered psychological tests : an introduction to Gendre's functional method

The functional method is a new test theory using a new scoring method that assumes complexity in test structure, and thus takes into account every correlation between factors and items. The main specificity of the functional method is to model test scores by multiple regression instead of estimating them by using simplistic sums of points. In order to proceed, the functional method requires the creation of hyperspherical measurement space, in which item responses are expressed by their correlation with orthogonal factors. This method has three main qualities. First, measures are expressed in the absolute metric of correlations; therefore, items, scales and persons are expressed in the same measurement space using the same single metric. Second, factors are systematically orthogonal and without errors, which is optimal in order to predict other outcomes. Such predictions can be performed to estimate how one would answer to other tests, or even to model one's response strategy if it was perfectly coherent. Third, the functional method provides measures of individuals' response validity (i.e., control indices). Herein, we propose a standard procedure in order to identify whether test results are interpretable and to exclude invalid results caused by various response biases based on control indices.

Gazpacho consumption is associated with lower blood pressure and reduced hypertension in a high cardiovascular risk cohort. Cross-sectional study of the PREDIMED trial

Hypertension is a major public health problem and a leading cause of death and disability in both developed and developing countries, affecting onequarter of the world"s adult population. Our aim was to evaluate whether the consumption of gazpacho, a Mediterranean vegetable-based cold soup rich in phytochemicals, is associated with lower blood pressure (BP) and/or reduced prevalence of hypertension in individuals at high cardiovascular risk. Methods and results: We selected 3995 individuals (58% women, mean age 67 y) at high cardiovascular risk (81% hypertensive) recruited into the PREDIMED study. BP, weight, and dietary and physical activity data were collected. In multivariate linear regression analyses, after adjustment, moderate and high gazpacho consumption categories were associated with reduced mean systolic BP of 1.9 mm Hg [95% confidence interval (CI): 3.4; 0.6] and 2.6 mm Hg (CI: 4.2; 1.0), respectively, and reduced diastolic BP of 1.5 mm Hg (CI: 2.3; 0.6) and 1.9 mm Hg (CI: 2.8; 1.1). By multiple-adjusted logistic regression analysis, gazpacho consumption was associated with a lower prevalence of hypertension, with OR Z 0.85 (CI: 0.73; 0.99) for each 250 g/week increase and OR Z 0.73 (CI: 0.55; 0.98) for high gazpacho consumption groups compared to the no-consumption group. Conclusions: Gazpacho consumption was inversely associated with systolic and diastolic BP and prevalence of hypertension in a cross-sectional Mediterranean population at high cardiovascular risk. The association between gazpacho intake and reduction of BP is probably due to synergy among several bioactive compounds present in the vegetable ingredients used to make the recipe.

Gazpacho consumption is associated with lower blood pressure and reduced hypertension in a high cardiovascular risk cohort. Cross-sectional study of the PREDIMED trial

Hypertension is a major public health problem and a leading cause of death and disability in both developed and developing countries, affecting onequarter of the world"s adult population. Our aim was to evaluate whether the consumption of gazpacho, a Mediterranean vegetable-based cold soup rich in phytochemicals, is associated with lower blood pressure (BP) and/or reduced prevalence of hypertension in individuals at high cardiovascular risk. Methods and results: We selected 3995 individuals (58% women, mean age 67 y) at high cardiovascular risk (81% hypertensive) recruited into the PREDIMED study. BP, weight, and dietary and physical activity data were collected. In multivariate linear regression analyses, after adjustment, moderate and high gazpacho consumption categories were associated with reduced mean systolic BP of 1.9 mm Hg [95% confidence interval (CI): 3.4; 0.6] and 2.6 mm Hg (CI: 4.2; 1.0), respectively, and reduced diastolic BP of 1.5 mm Hg (CI: 2.3; 0.6) and 1.9 mm Hg (CI: 2.8; 1.1). By multiple-adjusted logistic regression analysis, gazpacho consumption was associated with a lower prevalence of hypertension, with OR Z 0.85 (CI: 0.73; 0.99) for each 250 g/week increase and OR Z 0.73 (CI: 0.55; 0.98) for high gazpacho consumption groups compared to the no-consumption group. Conclusions: Gazpacho consumption was inversely associated with systolic and diastolic BP and prevalence of hypertension in a cross-sectional Mediterranean population at high cardiovascular risk. The association between gazpacho intake and reduction of BP is probably due to synergy among several bioactive compounds present in the vegetable ingredients used to make the recipe.

Symmetric or asymmetric gasoline prices? A meta-analysis approach

The analysis of price asymmetries in the gasoline market is one of the most studied in the energy economics literature. Nevertheless, the great variability of results makes it very difficult to extract conclusive results on the existence or not of asymmetries. This paper shows through a meta-analysis approach how the industry segment analysed, the quality and quantity of data, the estimator and the model used may explain this heterogeneity of results.

Regional Science trends through the analysis of the main facts of the 51st ERSA Conference

The 51st ERSA Conference held in Barcelona in 2011 was one of the largest ever. By examining the characteristics of the conference, this paper identifies the main trends in Regional Science and draws on a broad array of sources of information: the delegates" demographic details, the conference program itself, a satisfaction survey conducted among delegates, a quality survey addressed to those chairing the sessions and, finally, a bibliometric database including each author signing a paper presented at the conference. We finally run a regression analysis from which we show that for ERSA delegates what matters most is quality, and this must be the direction that future conferences should move toward. Ultimately, ERSA conferences are comprehensive, all-embracing occasions, representing an ideal opportunity for regional scientists to present their work to each other and to network.

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

O6-Methylguanine-DNA methyltransferase protein expression by immunohistochemistry in brain and non-brain systemic tumours: systematic review and meta-analysis of correlation with methylation-specific polymerase chain reaction

Background: The DNA repair protein O6-Methylguanine-DNA methyltransferase (MGMT) confers resistance to alkylating agents. Several methods have been applied to its analysis, with methylation-specific polymerase chain reaction (MSP) the most commonly used for promoter methylation study, while immunohistochemistry (IHC) has become the most frequently used for the detection of MGMT protein expression. Agreement on the best and most reliable technique for evaluating MGMT status remains unsettled. The aim of this study was to perform a systematic review and meta-analysis of the correlation between IHC and MSP. Methods A computer-aided search of MEDLINE (1950-October 2009), EBSCO (1966-October 2009) and EMBASE (1974-October 2009) was performed for relevant publications. Studies meeting inclusion criteria were those comparing MGMT protein expression by IHC with MGMT promoter methylation by MSP in the same cohort of patients. Methodological quality was assessed by using the QUADAS and STARD instruments. Previously published guidelines were followed for meta-analysis performance. Results Of 254 studies identified as eligible for full-text review, 52 (20.5%) met the inclusion criteria. The review showed that results of MGMT protein expression by IHC are not in close agreement with those obtained with MSP. Moreover, type of tumour (primary brain tumour vs others) was an independent covariate of accuracy estimates in the meta-regression analysis beyond the cut-off value. Conclusions Protein expression assessed by IHC alone fails to reflect the promoter methylation status of MGMT. Thus, in attempts at clinical diagnosis the two methods seem to select different groups of patients and should not be used interchangeably.

A Hierarchical Approach for Multi-task Logistic Regression

Peer-reviewed

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Analysis of laboratory intercomparison data: a matter of independence

When laboratory intercomparison exercises are conducted, there is no a priori dependence of the concentration of a certain compound determined in one laboratory to that determined by another(s). The same applies when comparing different methodologies. A existing data set of total mercury readings in fish muscle samples involved in a Brazilian intercomparison exercise was used to show that correlation analysis is the most effective statistical tool in this kind of experiments. Problems associated with alternative analytical tools such as mean or paired 't'-test comparison and regression analysis are discussed.

Financial stress transmission in EMU sovereign bond market volatility: a connectedness analysis

This paper measures the connectedness in EMU sovereign market volatility between April 1999 and January 2014, in order to monitor stress transmission and to identify episodes of intensive spillovers from one country to the others. To this end, we first perform a static and dynamic analysis to measure the total volatility connectedness in the entire period (the system-wide approach) using a framework recently proposed by Diebold and Yılmaz (2014). Second, we make use of a dynamic analysis to evaluate the net directional connectedness for each country and apply panel model techniques to investigate its determinants. Finally, to gain further insights, we examine the timevarying behaviour of net pair-wise directional connectedness at different stages of the recent sovereign debt crisis.

Predictors of remission in the treatment of major depressive disorder: real-world evidence from a 6-month prospective observational study

BACKGROUND: This study examined potential predictors of remission among patients treated for major depressive disorder (MDD) in a naturalistic clinical setting, mostly in the Middle East, East Asia, and Mexico. METHODS: Data for this post hoc analysis were taken from a 6-month prospective, noninterventional, observational study that involved 1,549 MDD patients without sexual dysfunction at baseline in 12 countries worldwide. Depression severity was measured using the Clinical Global Impression of Severity and the 16-item Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR16). Depression-related pain was measured using the pain-related items of the Somatic Symptom Inventory. Remission was defined as a QIDS-SR16 score ≤5. Generalized estimating equation regression models were used to examine baseline factors associated with remission during follow-up. RESULTS: Being from East Asia (odds ratio [OR] 0.48 versus Mexico; P<0.001), a higher level of depression severity at baseline (OR 0.77, P=0.003, for Clinical Global Impression of Severity; OR 0.92, P<0.001, for QIDS-SR16), more previous MDD episodes (OR 0.92, P=0.007), previous treatments/therapies for depression (OR 0.78, P=0.030), and having any significant psychiatric and medical comorbidity at baseline (OR 0.60, P<0.001) were negatively associated with remission, whereas being male (OR 1.29, P=0.026) and treatment with duloxetine (OR 2.38 versus selective serotonin reuptake inhibitors, P<0.001) were positively associated with remission. However, the association between Somatic Symptom Inventory pain scores and remission no longer appeared to be significant in this multiple regression (P=0.580), (P=0.008 in descriptive statistics), although it remained significant in a subgroup of patients treated with selective serotonin reuptake inhibitors (OR 0.97, P=0.023), but not in those treated with duloxetine (P=0.182). CONCLUSION: These findings are largely consistent with previous reports from the USA and Europe. They also highlight the potential mediating role of treatment with duloxetine on the negative relationship between depression-related pain and outcomes of depression.