66 resultados para Simplified Models.


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This paper examines how volatility in financial markets can preferable be modeled. The examination investigates how good the models for the volatility, both linear and nonlinear, are in absorbing skewness and kurtosis. The examination is done on the Nordic stock markets, including Finland, Sweden, Norway and Denmark. Different linear and nonlinear models are applied, and the results indicates that a linear model can almost always be used for modeling the series under investigation, even though nonlinear models performs slightly better in some cases. These results indicate that the markets under study are exposed to asymmetric patterns only to a certain degree. Negative shocks generally have a more prominent effect on the markets, but these effects are not really strong. However, in terms of absorbing skewness and kurtosis, nonlinear models outperform linear ones.

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This study evaluates three different time units in option pricing: trading time, calendar time and continuous time using discrete approximations (CTDA). The CTDA-time model partitions the trading day into 30-minute intervals, where each interval is given a weight corresponding to the historical volatility in the respective interval. Furthermore, the non-trading volatility, both overnight and weekend volatility, is included in the first interval of the trading day in the CTDA model. The three models are tested on market prices. The results indicate that the trading-time model gives the best fit to market prices in line with the results of previous studies, but contrary to expectations under non-arbitrage option pricing. Under non-arbitrage pricing, the option premium should reflect the cost of hedging the expected volatility during the option’s remaining life. The study concludes that the historical patterns in volatility are not fully accounted for by the market, rather the market prices options closer to trading time.

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Yhteenveto: Järvien ainetasemallien kehittäminen.

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Yhteenveto: Lumimallit vesistöjen ennustemalleissa

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Acute childhood osteomyelitis (OM), septic arthritis (SA), and their combination osteomyelitis with adjacent septic arthritis (OM+SA), are treated with long courses of antimicrobials and immediate surgery. We conducted a prospective multi-center randomized trial among Finnish children at age 3 months to 15 years in 1983-2005. According to the two-by-two factorial study design, children with OM or OM+SA received 20 or 30 days of antimicrobials, whereas those with SA were treated for 10 or 30 days. In addition, the whole series was randomized to be treated with clindamycin or a first-generation cephalosporin. Cases were included only if the causative agent was isolated. The treatment was instituted intravenously, but only for the first 2-4 days. Percutaneous aspiration was done to obtain a representative sample for bacteriology, but all other surgical intervention was kept at a minimum. A total of 265 patients fulfilled our strict inclusion criteria and were analyzed; 106 children had OM, 134 SA, and 25 OM+SA. In the OM group, one child in the long and one child in the short-term treatment group developed sequelae. One child with SA twice developed a late re-infection of the same joint, but the causative agents differed. Regarding surgery, diagnostic arthrocentesis or corticotomy was the only surgical procedure performed in most cases. Routine arthrotomy was not required even in hip arthritis. Serum C-reactive protein (CRP) proved to be a reliable laboratory index in the diagnosis and monitoring of osteoarticular infections. The recovery rate was similar regardless of whether clindamycin or a first-generation cephalosporin was used. We conclude that a course of 20 days of these well-absorbing antimicrobials is sufficient for OM or OM+SA, and 10 days for SA in most cases beyond the neonatal age. A short intravenous phase of only 2-5 days often suffices. CRP gives valuable information in monitoring the course of illness. Besides diagnostic aspiration, surgery should be reserved for selected cases.

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Cosmopolitan ideals have been on the philosophical agenda for several millennia but the end of the Cold War started a new discussion on state sovereignty, global democracy, the role of international law and global institutions. The Westphalian state system in practice since the 17th century is transforming and the democracy deficit needs new solutions. An impetus has been the fact that in the present world, an international body representing global citizens does not exist. In this Master’s thesis, the possibility of establishing a world parliament is examined. In a case analysis, 17 models on world parliament from two journals, a volume of essays and two other publications are discussed. Based on general observations, the models are divided into four thematic groups. The models are analyzed with an emphasis on feasible and probable elements. Further, a new scenario with a time frame of thirty years is proposed based on the methodology of normative futures studies, taking special interest in causal relationships and actions leading to change. The scenario presents three gradual steps that each need to be realized before a sustainable world parliament is established. The theoretical framework is based on social constructivism, and changes in international and multi-level governance are examined with the concepts of globalization, democracy and sovereignty. A feasible, desirable and credible world parliament is constituted gradually by implying electoral, democratic and legal measures for members initially from exclusively democratic states, parliamentarians, non-governmental organizations and other groups. The parliament should be located outside the United Nations context, since a new body avoids the problem of inefficiency currently prevailing in the UN. The main objectives of the world parliament are to safeguard peace and international law and to offer legal advice in cases when international law has been violated. A feasible world parliament is advisory in the beginning but it is granted legislative powers in the future. The number of members in the world parliament could also be extended following the example of the EU enlargement process.

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This thesis is composed of an introductory chapter and four applications each of them constituting an own chapter. The common element underlying each of the chapters is the econometric methodology. The applications rely mostly on the leading econometric techniques related to estimation of causal effects. The first chapter introduces the econometric techniques that are employed in the remaining chapters. Chapter 2 studies the effects of shocking news on student performance. It exploits the fact that the school shooting in Kauhajoki in 2008 coincided with the matriculation examination period of that fall. It shows that the performance of men declined due to the news of the school shooting. For women the similar pattern remains unobserved. Chapter 3 studies the effects of minimum wage on employment by employing the original Card and Krueger (1994; CK) and Neumark and Wascher (2000; NW) data together with the changes-in-changes (CIC) estimator. As the main result it shows that the employment effect of an increase in the minimum wage is positive for small fast-food restaurants and negative for big fast-food restaurants. Therefore, it shows that the controversial positive employment effect reported by CK is overturned for big fast-food restaurants and that the NW data are shown, in contrast to their original results, to provide support for the positive employment effect. Chapter 4 employs the state-specific U.S. data (collected by Cohen and Einav [2003; CE]) on traffic fatalities to re-evaluate the effects of seat belt laws on the traffic fatalities by using the CIC estimator. It confirms the CE results that on the average an implementation of a mandatory seat belt law results in an increase in the seat belt usage rate and a decrease in the total fatality rate. In contrast to CE, it also finds evidence on compensating-behavior theory, which is observed especially in the states by the border of the U.S. Chapter 5 studies the life cycle consumption in Finland, with the special interest laid on the baby boomers and the older households. It shows that the baby boomers smooth their consumption over the life cycle more than other generations. It also shows that the old households smoothed their life cycle consumption more as a result of the recession in the 1990s, compared to young households.

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Background Acute bacterial meningitis (BM) continues to be an important cause of childhood mortality and morbidity, especially in developing countries. Prognostic scales and the identification of risk factors for adverse outcome both aid in assessing disease severity. New antimicrobial agents or adjunctive treatments - except for oral glycerol - have essentially failed to improve BM prognosis. A retrospective observational analysis found paracetamol beneficial in adult bacteraemic patients, and some experts recommend slow β-lactam infusion. We examined these treatments in a prospective, double-blind, placebo-controlled clinical trial. Patients and methods A retrospective analysis included 555 children treated for BM in 2004 in the infectious disease ward of the Paediatric Hospital of Luanda, Angola. Our prospective study randomised 723 children into four groups, to receive a combination of cefotaxime infusion or boluses every 6 hours for the first 24 hours and oral paracetamol or placebo for 48 hours. The primary endpoints were 1) death or severe neurological sequelae (SeNeSe), and 2) deafness. Results In the retrospective study, the mortality of children with blood transfusion was 23% (30 of 128) vs. without blood transfusion 39% (109 of 282; p=0.004). In the prospective study, 272 (38%) of the children died. Of those 451 surviving, 68 (15%) showed SeNeSe, and 12% (45 of 374) were deaf. Whereas no difference between treatment groups was observable in primary endpoints, the early mortality in the infusion-paracetamol group was lower, with the difference (Fisher s exact test) from the other groups at 24, 48, and 72 hours being significant (p=0.041, 0.0005, and 0.005, respectively). Prognostic factors for adverse outcomes were impaired consciousness, dyspnoea, seizures, delayed presentation, and absence of electricity at home (Simple Luanda Scale, SLS); the Bayesian Luanda Scale (BLS) also included abnormally low or high blood glucose. Conclusions New studies concerning the possible beneficial effect of blood transfusion, and concerning longer treatment with cefotaxime infusion and oral paracetamol, and a study to validate our simple prognostic scales are warranted.

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In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

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This thesis report attempts to improve the models for predicting forest stand structure for practical use, e.g. forest management planning (FMP) purposes in Finland. Comparisons were made between Weibull and Johnson s SB distribution and alternative regression estimation methods. Data used for preliminary studies was local but the final models were based on representative data. Models were validated mainly in terms of bias and RMSE in the main stand characteristics (e.g. volume) using independent data. The bivariate SBB distribution model was used to mimic realistic variations in tree dimensions by including within-diameter-class height variation. Using the traditional method, diameter distribution with the expected height resulted in reduced height variation, whereas the alternative bivariate method utilized the error-term of the height model. The lack of models for FMP was covered to some extent by the models for peatland and juvenile stands. The validation of these models showed that the more sophisticated regression estimation methods provided slightly improved accuracy. A flexible prediction and application for stand structure consisted of seemingly unrelated regression models for eight stand characteristics, the parameters of three optional distributions and Näslund s height curve. The cross-model covariance structure was used for linear prediction application, in which the expected values of the models were calibrated with the known stand characteristics. This provided a framework to validate the optional distributions and the optional set of stand characteristics. Height distribution is recommended for the earliest state of stands because of its continuous feature. From the mean height of about 4 m, Weibull dbh-frequency distribution is recommended in young stands if the input variables consist of arithmetic stand characteristics. In advanced stands, basal area-dbh distribution models are recommended. Näslund s height curve proved useful. Some efficient transformations of stand characteristics are introduced, e.g. the shape index, which combined the basal area, the stem number and the median diameter. Shape index enabled SB model for peatland stands to detect large variation in stand densities. This model also demonstrated reasonable behaviour for stands in mineral soils.