The Mean Variance Mixing GARCH (1,1) model

Here we present a general framework for a GARCH (1,1) type of process with innovations with a probability law of the mean- variance mixing type, therefore we call the process in question the mean variance mixing GARCH \ (1,1) or MVM GARCH\(1,1). One implication is a GARCH\ model with skewed innovations and constant mean dynamics. This is achieved without using a location parameter to compensate for time dependence that affects the mean dynamics. From a probabilistic viewpoint the idea is straightforward. We just construct our stochastic process from the desired behavior of the cumulants. Further we provide explicit expressions for the unconditional second to fourth cumulants for the process in question. In the paper we present a specification of the MVM-GARCH process where the mixing variable is of the inverse Gaussian type. On the basis on this assumption we can formulate a maximum likelihood based approach for estimating the process closely related to the approach used to estimate an ordinary GARCH (1,1). Under the distributional assumption that the mixing random process is an inverse Gaussian i.i.d process the MVM-GARCH process is then estimated on log return data from the Standard and Poor 500 index. An analysis for the conditional skewness and kurtosis implied by the process is also presented in the paperGARCH Skewness Conditional Skewness

Approximating the probability distribution of functions of random variables: A new approach

We introduce a new approximation method for the distribution of functions of random variables that are real-valued. The approximation involves moment matching and exploits properties of the class of normal inverse Gaussian distributions. In the paper we we examine the how well the different approximation methods can capture the tail behavior of a function of random variables relative each other. This is obtain done by simulate a number functions of random variables and then investigate the tail behavior for each method. Further we also focus on the regions of unimodality and positive definiteness of the different approximation methods. We show that the new method provides equal or better approximations than Gram-Charlier and Edgeworth expansioApproximation of random variables

Approximating the Probability Distribution of Functions of Random Variables: A New Approach

We introduce a new approximation method for the distribution of functions of random variables that are real-valued. The approximation involves moment matching and exploits properties of the class of normal inverse Gaussian distributions. In the paper we examine the how well the different approximation methods can capture the tail behavior of a function of random variables relative each other. This is done by simulate a number functions of random variables and then investigate the tail behavior for each method. Further we also focus on the regions of unimodality and positive definiteness of the different approximation methods. We show that the new method provides equal or better approximations than Gram-Charlier and Edgeworth expansions. Nous introduisons une nouvelle méthode pour approximer la distribution de variables aléatoires. L'approximation est basée sur la classe de distribution normale inverse gaussienne. On démontre que la nouvelle approximation est meilleure que les expansions Gram-Charlier et Edgeworth.normal inverse Gaussian, Edgeworth expansions, Gram-Charlier, distribution normale inverse gaussienne, expansions d'Edgeworth, Gram-Charlier

Swedish CLARIN activities

Proceedings of the NODALIDA 2009 workshop Nordic Perspectives on the CLARIN Infrastructure of Language Resources. Editors: Rickard Domeij, Kimmo Koskenniemi, Steven Krauwer, Bente Maegaard, Eiríkur Rögnvaldsson and Koenraad de Smedt. NEALT Proceedings Series, Vol. 5 (2009), 1-5. © 2009 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/9207

Approximating the Probability Distribution of Functions of Random Variables: A New Approach

Nous introduisons une nouvelle méthode pour approximer la distribution de variables aléatoires. L'approximation est basée sur la classe de distribution normale inverse gaussienne. On démontre que la nouvelle approximation est meilleure que les expansions Gram-Charlier et Edgeworth.We introduce a new approximation method for the distribution of functions of random variables that are real-valued. The approximation involves moment matching and exploits properties of the class of normal inverse Gaussian distributions. In the paper we examine the how well the different approximation methods can capture the tail behavior of a function of random variables relative each other. This is done by simulate a number functions of random variables and then investigate the tail behavior for each method. Further we also focus on the regions of unimodality and positive definiteness of the different approximation methods. We show that the new method provides equal or better approximations than Gram-Charlier and Edgeworth expansions

Effects of dapagliflozin and n-3 carboxylic acids on non-alcoholic fatty liver disease in people with type 2 diabetes : a double-blind randomised placebo-controlled study

Aims/hypothesis The EFFECT-II study aimed to investigate the effects of dapagliflozin and omega-3 (n-3) carboxylic acids (OM-3CA). individually or combined, on liver fat content in individuals with type 2 diabetes and non-alcoholic fatty liver disease (NAFLD). Methods This randomised placebo-controlled double-blind parallel-group study was performed at five clinical research centres at university hospitals in Sweden. 84 participants with type 2 diabetes and NAFLD were randomly assigned 1:1:1:1 to four treatments by a centralised randomisation system, and all participants as well as investigators and staff involved in the study conduct and analyses were blinded to treatments. Each group received oral doses of one of the following: 10 mg dapagliflozin (n = 21). 4 g OM3-CA (n = 20), a combination of both (n = 22) or placebo (n = 21). The primary endpoint was liver fat content assessed by MRI (proton density fat fraction [PDFF]) and, in addition, total liver volume and markers of glucose and lipid metabolism as well as of hepatocyte injury and oxidative stress were assessed at baseline and after 12 weeks of treatment (completion of the trial). Results Participants had a mean age of 65.5 years (SD 5.9), BMI 31.2 kg/m(2) (3.5) and liver PDFF 18% (9.3). All active treatments significantly reduced liver PDFF from baseline, relative changes: OM-3CA, -15%; dapagliflozin, -13%; OM-3CA + dapagliflozin, -21%. Only the combination treatment reduced liver PDFF (p = 0.046) and total liver fat volume (relative change, -24%,p = 0.037) in comparison with placebo. There was an interaction between the PNPLA31148M polymorphism and change in liver PDFF in the active treatment groups (p = 0.03). Dapagliflozin monotherapy, but not the combination with OM-3CA, reduced the levels of hepatocyte injury biomarkers, including alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transfcrase (gamma-GT), cytokeratin (CK) 18-M30 and CK 18-M65 and plasma fibroblast growth factor 21 (FGF21). Changes in gamma-GT correlated with changes in liver PDFF (rho = 0.53, p = 0.02). Dapagliflozin alone and in combination with OM-3CA improved glucose control and reduced body weight and abdominal fat volumes. Fatty acid oxidative stress biomarkers were not affected by treatments. There were no new or unexpected adverse events compared with previous studies with these treatments. Conclusions/interpretation Combined treatment with dapagliflozin and OM-3CA significantly reduced liver fat content. Dapagliflozin monotherapy reduced all measured hepatocyte injury biomarkers and FGF21, suggesting a disease-modifying effect in NAFLD

Risk factors for subarachnoid haemorrhage : a nationwide cohort of 950 000 adults

BACKGROUND: Subarachnoid haemorrhage (SAH) is a devastating disease, with high mortality rate and substantial disability among survivors. Its causes are poorly understood. We aimed to investigate risk factors for SAH using a novel nationwide cohort consortium. METHODS: We obtained individual participant data of 949 683 persons (330 334 women) between 25 and 90 years old, with no history of SAH at baseline, from 21 population-based cohorts. Outcomes were obtained from the Swedish Patient and Causes of Death Registries. RESULTS: During 13 704 959 person-years of follow-up, 2659 cases of first-ever fatal or non-fatal SAH occurred, with an age-standardized incidence rate of 9.0 [95% confidence interval (CI) (7.4-10.6)/100 000 person-years] in men and 13.8 [(11.4-16.2)/100 000 person-years] in women. The incidence rate increased exponentially with higher age. In multivariable-adjusted Poisson models, marked sex interactions for current smoking and body mass index (BMI) were observed. Current smoking conferred a rate ratio (RR) of 2.24 (95% CI 1.95-2.57) in women and 1.62 (1.47-1.79) in men. One standard deviation higher BMI was associated with an RR of 0.86 (0.81-0.92) in women and 1.02 (0.96-1.08) in men. Higher blood pressure and lower education level were also associated with higher risk of SAH. CONCLUSIONS: The risk of SAH is 45% higher in women than in men, with substantial sex differences in risk factor strengths. In particular, a markedly stronger adverse effect of smoking in women may motivate targeted public health initiatives