Background Climate variation has affected diverse physical and biological systems worldwide. Population health is one of the most important impacts of climate variation. Although the impact of climate variation on infectious diseases has been of significant concern recently, the relationship between climate variation and infectious diseases, including vector-borne diseases and enteric infections, needs greater clarification. Australia is grappling with developing politically acceptable responses to global warming. In China, few studies have been conducted to examine the effect of climate variation, including global warming, on population health. As residents of developing countries may suffer more from climate change compared with people living in more developed countries, this thesis has significance for both countries. Aims This study aims to contribute to a better understanding of the impact of climate variation on population health, and to provide scientific evidence for policy makers, researchers, public health practitioners and local communities in the development of public health strategies at an early stage, in order to prevent or reduce future risks associated with ongoing climate change. The objectives of this study include: (1) to quantify the association between climate variation and selected vectorborne diseases and enteric infections in different climatic regions in Australia and China; (2) to project the future burden of selected vector-borne diseases and enteric infections based on climate change scenarios in different climatic regions in Australia and China. Methods This ecological study has two components. The first uses time-series analyses to quantify the relationship between meteorological variables and infectious diseases, whereas the second projects the burden of selected infectious diseases using future climate and population scenarios. Temperate and subtropical climatic zones in both Australia and China were selected as the primary study areas, and a study of an Australian tropical region was also conducted. Study of Australia’s temperate zones was conducted in Adelaide, South Australia, as well as the Murray River region in that State. The study of China’s temperate zone was carried out in Jinan, Shandong Province. Subtropical studies were conducted in Baoan, Guangdong Province, China, and Brisbane in Queensland, whilst research for the tropics centred on Townsville, also in Queensland, Australia. The selected infectious diseases - one vector-borne disease and one enteric infection in each country - are Ross River Virus (RRV) infection and salmonellosis in Australia, and malaria and bacillary dysentery in China. Study periods vary from eight to sixteen years (depending upon the availability of data). Climate data, infectious disease surveillance data and demographic data were collected from local authorities. Data analyses conducted in the ecological studies include Spearman correlation analysis, time-series adjusted Poisson regression and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model with consideration of lag effects, seasonality, long-term trends, and autocorrelation, on a weekly or monthly basis depending on data availability, and Hockey Sticky model to detect potential threshold temperatures. In the burden of disease component, analyses include the calculation of an indicator of the burden of disease - Years Lost due to Disabilities (YLDs) - and use scenario-based models to project YLDs for the selected diseases in 2030 and 2050 in Australia and 2020 and 2050 in China respectively. The projections consider both different scenarios of projected temperature and future population change. Results Relationship between climate variation and selected infectious diseases In all the study regions in Australia, maximum temperature, minimum temperature, rainfall and humidity are all significantly related to the number of RRV infections, with lag effects varying from 0 to 3 months. Additionally, high tides in the two seaside regions with tropical (Townsville) or subtropical (Brisbane) climates, and river flow in the temperate region (Murray River region), are related to the number of cases without any lag effects. A potential 1°C increase in maximum or minimum temperature may cause 4%~23% extra cases of RRV infection in the temperate region, 5~8% in the subtropical region, and 6%~15% in the tropical region. Maximum temperature, minimum temperature, humidity and air pressure are significantly related to malaria cases in the temperate city Jinan and subtropical city Baoan in China, with a lag effect range of 0 to 1 month. An association between rainfall and malaria cases was not detected in either region. A potential 1°C increase in maximum or minimum temperature may lead to 4%~15% extra malaria cases in the temperate region, and 12%-18% in the tropical region in China. Maximum temperature, minimum temperature, rainfall and humidity are all significantly related to the number of salmonellosis cases in the three study cities in Australia, with lag effects varying from 0 to 1 month. A potential 1°C increase in maximum or minimum temperature may cause 6%~19% extra salmonellosis cases in the temperate region (Adelaide), 5%~10% in the subtropical region (Brisbane), and 4%~15% in the tropical region (Townsville). The thresholds for the effects of maximum and minimum temperatures are 20ºC and 12ºC respectively in Adelaide. No threshold temperatures are detected in Townsville and Brisbane. Maximum temperature, minimum temperature, humidity, air pressure and rainfall are significantly related to bacillary dysentery cases in the temperate city Jinan and subtropical city Baoan in China, with the lag effect range of 0 to 2 months. A potential 1°C increase in maximum or minimum temperature may cause 7%~15% extra bacillary dysentery cases in the temperate region and 10% ~ 19% in the subtropical region in China. The thresholds for the effects of maximum and minimum temperatures on bacillary dysentery are 17ºC and 8ºC respectively in Jinan. No threshold temperatures are detected in Baoan. Projection of YLDs from target diseases In Australia, considering both climatic and population scenarios, if other factors remain constant, compared with the YLDs observed in 2000, the YLDs for salmonellosis might increase by up to 48% by 2030, and nearly double by 2050 in South Australia, while the YLDs might double by 2030 and increase by up to 143% by 2050 in Brisbane, Queensland. The YLDs for RRV infection might increase by up to 66% by 2030, and nearly double by 2050 in South Australia. They might increase by up to 61% by 2030 and double by 2050 in Brisbane, Queensland. In China, considering both climatic and population scenarios, if other factors remain constant, compared with the YLDs observed in 2000, the YLDs for bacillary dysentery might double by 2020 and triple by 2050 in both Jinan and Baoan. The YLDs for malaria might increase by up to 108% by 2020 and nearly triple by 2050 in Jinan, the temperate city, and increase by up to 144% by 2020 and nearly triple by 2050 in Baoan, the subtropical city. Conclusions 1. Both maximum and minimum temperatures are important in the transmission of vector-borne diseases in various climatic regions in both Australia and China. River flow or high tides may also play an important role in the transmission of such diseases. 2. Both maximum and minimum temperatures play an important role in the transmission of enteric infections in various climatic regions in both Australia and China, with a threshold temperature detected in the temperate regions but not in subtropical and tropical regions. 3. The effects of rainfall and relative humidity on selected infectious diseases vary in different study areas in Australia and China. 4. The burden of temperature-related infectious diseases may greatly increase in the future if there is no effective preventive intervention. Public health implications 1. Implication for health practice • Public health practitioners, together with relevant government organisations, should monitor trends in infectious diseases, as well as other relevant indexes, such as vectors, pathogens, and water and food safety. They should advise policy makers of the potential risks associated with climate change and develop public health strategies to prevent and reduce the impact of infectious disease associated with such change. • Doctors and other clinical practitioners should be prepared and supported in the provision of health care for any expected extra cases associated with climate variation and should play an important role in relevant health education on climate change. • Community participation is of significance to adapt to and mitigate the risk of climate change on population health. Community involvement helps to deliver programmes which more accurately target local needs. Therefore, community should be involved in the partnerships of climate change as early as possible. • Relevant education programs on the potential health impact of climate change should be conducted by government at all levels for different stakeholders, including industries, governments, communities, clinicians and researchers. • Advocacy for adapting to and mitigating climate change should be a longstanding public health activity. 2. Implication for researchers • The main task for researchers is to identify the independent contribution made by key climatic variables and whether there are exposure thresholds for infectious disease transmission. Further studies should include various infectious diseases in different climatic regions. • Developing countries and rural regions are more vulnerable to the impact of climate change so more research should be conducted for people living in those regions. • Studies using summary measures that combine prevalence of disease, quality of life and life expectancy, such as Disability Adjusted Life Years (DALYs), to assess the burden of disease due to climate change is necessary to assist in decision making. • More research should be conducted on the assessment of adaptive strategies and mitigation to future climate change. 3. Implication for policies • Public and preventive health strategies that consider local climatic conditions and their impact on vector and food borne diseases are important in reducing such impact due to climate change in the future. • The extra health burden that may be caused by future climate change may have a great impact on the currently overloaded public health system in both developed and developing countries. Long-term planning about health resource allocation, infrastructure establishment, and relevant response mechanisms should be developed at relevant government levels. • Effective prevention and intervention strategies will be possible only if the efforts of relevant sectors, including governments, communities, industries, research institutions, clinical professionals and individuals, have coordinated responses. • International and regional collaborations are necessary to address this global issue. In addition, strategies of an international dimension should be translated into regional and local actions. This is extremely important to developing countries such as China and India. • Sustainable development policies with consideration given to reducing green house gases and environmental degradation need immediate action which will benefit future generations. Health priorities should include the prevention of climate change. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1290777 / Thesis(Ph.D.)-- School of Population Health and Clinical Practice, 2007

<p>Takeover is a business activity which really started in the beginning of the eighties and which still takes a strong part in the business and financial area all over the world. According to our studies as the desire for further acknowledgements and the desire of building a career around financial activities, this study has been naturally conducted in the banking area.</p><p>Regarding the steady use of acquisition like a powerful process with some positive and negative sides, we decided to implement a comparison of different mergers and acquisitions in the banking industry in the United States and Europe. This comparison has been supported and based on the third main topic of our study: performance.</p><p>These large and complex subjects combined together lead to the following hypotheses:</p><p>Hypothesis 1: Performance is not improved after takeover in the banking industry.</p><p>Hypothesis 2: The level of post takeover performance is the same in the U.S. as in the European bank acquisitions.</p><p>Based on the historical data and knowledge, the United States was the pioneer in the development of such gathers in the banking sector. Considering the United States as a reference, a first purpose was to compare them with the bank mergers and acquisitions in Europe. Stating on some possible differences as increasing our own knowledge have been some others purposes which have supported our work.</p><p>A first large part of our work was focused, through a large literature review, on the enhancement of our knowledge as the statements of the basis and support for the analysis.</p><p>To illustrate and to try to answer our research question, we have conducted our study based on a sample of 20 acquisitions which were achieved in the banking industry between March 1998 and May 2004. 10 of these acquisitions had been achieved in the United States as the 10 remaining acquisitions had been executed in Europe.</p><p>The analysis has been achieved by collecting data in Thomson Datastream Advance.</p><p>Based on a quantitative method, we applied two financial models: The Market Model (MM) and the Market-Adjusted Returns Model (MAR) supported by the Cumulative Abnormal Returns Method (CARs).</p><p>The post-takeover study has been delimited on a period of 42 months after the public announcement.</p><p>The study and the comparison between the United States and Europe have shown some differences between the two areas. Nevertheless it seems that negative abnormal returns are usually the case after such takeovers on the whole period studied. Some positive abnormal returns have been recorded at different points in the time into the studying period.</p><p>According to the models we applied, the US banks results seem to be better than the ones of European banks: the differences range from 5,58 to 16,65 points under the MM, and from 1,66 to 18,08 points under the MAR model.</p>

In this thesis, we explore two different approaches to causal inferences. The traditional approach models the theoretical relationship between the outcome variables and their explanatory variables, i.e., the science, at the same time as the systematic differences between treated and control subjects are modeled, i.e., the assignment mechanism. The alternative approach, based on Rubin's Causal Model (RCM), makes it possible to model the science and the assignment mechanism separately in a two-step procedure. In the first step, no outcome variables are used when the assignment mechanism is modeled, the treated students are matched with similar control students using this mechanism, and the models for the science are determined. Outcome variables are only used in the second step when these pre-specified models for the science are fitted. In the first paper, we use the traditional approach to evaluate whether a husband is more prone to quit smoking when his wife quits smoking than he would have been had his wife not quit. We find evidence that this is the case, but that our analysis must rely on restrictive assumptions. In the subsequent two papers, we use the alternative RCM approach to evaluate if a Harvard freshman who does not smoke (observed potential outcome) is more prone to start smoking when he shares a suite with at least one smoker, than he would have been had he shared a suite with only smokers (missing potential outcomes). We do not find evidence that this is the case, and the small and insignificant treatment effect is robust against various assumptions that we make regarding covariate adjustments and missing potential outcomes. In contrast, we do find such evidence when we use the traditional approach previously used in the literature to evaluate peer effects relating to smoking, but the treatment effect is not robust against the assumptions that we make regarding covariate adjustments. These contrasting results in the two latter papers allow us to conclude that there are a number of advantages with the alternative RCM approach over the traditional approaches previously used to evaluate peer effects relating to smoking. Because the RCM does not use the outcome variables when the assignment mechanism is modeled, it can be re-fit repeatedly without biasing the models for the science. The assignment mechanism can then often be modeled to fit the data better and, because the models for the science can consequently better control for the assignment mechanism, they can be fit with less restrictive assumptions. Moreover, because the RCM models two distinct processes separately, the implications of the assumptions that are made on these processes become more transparent. Finally, the RCM can derive the two potential outcomes needed for drawing causal inferences explicitly, which enhances the transparency of the assumptions made with regard to the missing potential outcomes. / Diss. Stockholm : Handelshögskolan, 2006 S. 1-13: sammanfattning, s. [15]-161: 4 uppsatser

Takeover is a business activity which really started in the beginning of the eighties and which still takes a strong part in the business and financial area all over the world. According to our studies as the desire for further acknowledgements and the desire of building a career around financial activities, this study has been naturally conducted in the banking area. Regarding the steady use of acquisition like a powerful process with some positive and negative sides, we decided to implement a comparison of different mergers and acquisitions in the banking industry in the United States and Europe. This comparison has been supported and based on the third main topic of our study: performance. These large and complex subjects combined together lead to the following hypotheses: Hypothesis 1: Performance is not improved after takeover in the banking industry. Hypothesis 2: The level of post takeover performance is the same in the U.S. as in the European bank acquisitions. Based on the historical data and knowledge, the United States was the pioneer in the development of such gathers in the banking sector. Considering the United States as a reference, a first purpose was to compare them with the bank mergers and acquisitions in Europe. Stating on some possible differences as increasing our own knowledge have been some others purposes which have supported our work. A first large part of our work was focused, through a large literature review, on the enhancement of our knowledge as the statements of the basis and support for the analysis. To illustrate and to try to answer our research question, we have conducted our study based on a sample of 20 acquisitions which were achieved in the banking industry between March 1998 and May 2004. 10 of these acquisitions had been achieved in the United States as the 10 remaining acquisitions had been executed in Europe. The analysis has been achieved by collecting data in Thomson Datastream Advance. Based on a quantitative method, we applied two financial models: The Market Model (MM) and the Market-Adjusted Returns Model (MAR) supported by the Cumulative Abnormal Returns Method (CARs). The post-takeover study has been delimited on a period of 42 months after the public announcement. The study and the comparison between the United States and Europe have shown some differences between the two areas. Nevertheless it seems that negative abnormal returns are usually the case after such takeovers on the whole period studied. Some positive abnormal returns have been recorded at different points in the time into the studying period. According to the models we applied, the US banks results seem to be better than the ones of European banks: the differences range from 5,58 to 16,65 points under the MM, and from 1,66 to 18,08 points under the MAR model.

Bakgrund: De flesta svenskarna sparar i form av värdepapper för att investera sina pengar och få en avkastning. Vilket placeringsalternativ ska de välja mellan investering i traditionella eller speciella fonder? De traditionella fonderna har en relativ avkastning och en stor risk, medan de speciella eller hedgefonderna har en lägre risk och en absolut positiv avkastning oavsett marknadsläge.I denna studie kommer att undersökas om hedgefonders avkastningsmönster är trovärdig, och om deras målsättning har uppnåtts under åtta års period. Syfte: Syftet med denna studie är att undersöka om det finns ett samband mellan olika svenska hedgefonders investeringsstrategier och avkastningsmönster samt undersöka hur dessa hedgefonder skiljer sig från de traditionella fonderna och marknadsindexet. Delsyftet är att studera två olika perioder och urskilja hur fonderna presterar under hög respektive låg konjunktur läge. Metod: Studien är baserad på forskningsstrategin kvantitativa metoden. Sekundär data i form av historiska avkastningssiffror för åttaårsperiod är avhämtad. Olika nyckeltal är valda för uträckningen och analysen. Korrelation, regression och hypotesprövning är de utvalda statistiska metoder som ska leda författaren att analysera och dra slutsats. Slutsats: De hedgefonderna har under de olika perioderna genererat en genomsnittlig positiv avkastning trots de låga värden. De har lägre totalrisk samt marknadsrisk än de traditionella, och en låg korrelation mellan varandra. Vidare har studien visat att räntearbitrage och marknadsneutrala strategier har presterat bäst under låg konjunktur.Sammanfattningsvis hedgefonders avkastningsmönster skiljer sig mellan de olika strategierna och inom varje strategi. Trots på den låga positiva avkastningen anses hedgefonder ett bättre placeringsalternativ än traditionella fonder i tider där marknaden går ner.Avkastningsmönster är en fördom på kortsikt men anses vara en verklighet långsiktigt. / Background: The majority of the Swedish population saves in the form of securities to invest and receive a return. Which investment option should they choose? Should they invest in mutual or special funds? The mutual funds have a relative return and come with a high risk, while the special funds, also known as hedge funds, have an absolute positive return regardless of the market situation and this fund type accounts for a lower risk. This study will investigate whether the return pattern in the hedge funds are valid or not, and if their objective was achieved during this 8 year period. Purpose: The purpose of this study is to investigate if there is a relationship between Swedish hedge funds' investment strategies and their return pattern as well as examining how these hedge funds differ from the mutual funds and the market index. The sub focus is studying two different periods and discerns how the funds perform under high and low economic situation. Methodology: The study is based on results obtained from the research strategy, of a quantitative character. Secondary data in the form of historical returns for the eight-year period is utilized. Different ratios are utilized for calculations and analysis. Correlation, regression, and hypothesis testing are the chosen statistical methods that will lead the author to analyze and draw conclusions. Conclusions: The hedge funds have in the different periods generated an average positive return despite the low values. They have lower total risk and market risk than mutual ones, and a low correlation between each other. Furthermore, the study has shown that rate arbitrage and market neutral strategies perform best under low economy context.In summary, hedge funds' return pattern differs between the diverse strategies and within each strategy. Despite the low positive returns hedge funds are considered a better investment option than mutual funds in times when the market is unstable.The return pattern does not apply to short term investments but it does apply to long term investments.

Las tasas brutas de morbi-mortalidad no son indicadores fiables del resultado del producto sanitario, siendo necesario el uso de escalas de riesgo adjustadas por paciente y gravedad. En nuestro estudio se validaron 5 escalas de riesgo para predecir morbilidad y mortalidad en nuestros pacientes sometidos a cirugía programada (POSSUM, P-POSSUM, SAPS II, APACHE II, MODS y MPM). Tras la validación se aplicaron prospectivamente, demostrándose la utilidad de POSSUM y P-POSSUM para predecir morbilidad y mortalidad, por lo que se recomienda su uso en los servicios quirúrgicos. / the use of raw tases to mesuring health results not only is innacuracy but also is dangerous, due to the fact that, the results in medicine depend on the ability of phisician, phisiological status, pre and postoperative cares and kind of intervention. The aim of our study is the validation and prospective aplication of 6 adjusted risk scores (POSSUM, P-POSSUM, SAPS II, APACHE II, MOD S and MPM). We can draw the following conclusions: POSSUM and P-POSSUM are POSSUM and P-POSSUM systems have a high reliability in application for measuring risk of mortality and morbidity in patients studied. APACHE II, SAPS II and MODS scores do not have good reliability in their application for predicting mortality in surgical patients. The use of the POSSUM and P-POSSUM systems is highly recommended in the surgery services to monitor and detect errors in clinical practice.

I denna uppsats undersöks om världshändelser skapar abnorma effekter hos oljebolags aktiekurser och om dessa effekter ter sig olika beroende på företagens olika storlek. Undersökningen utförs med hjälp av en eventstudie som genomförs på sex oljebolag med tre världshändelser som utgångspunkt. De valda världshändelserna bestod av två naturkatastrofer och en större ekonomisk händelse. Företagen som valdes delades in i två grupper om tre företag, där ena gruppen innehöll de större företagen och den andra gruppen de mindre. Slutsatserna som har kunnat dras av undersökningen är att händelserna i två av de tre undersökta fallen orsakade signifikanta abnorma under- eller överavkastningar hos oljebolagens aktier vilket bevisar en viss ineffektivitet hos marknaden. Det generella utfallet var att den ekonomiska händelsen visade sig ha en större påverkan på aktiekurserna än de två naturkatastroferna hade. Samtidigt kunde det påvisas en större skillnad mellan de större och de mindre företagens aktiekursers reaktioner gällande den ekonomiska händelsen. Resultaten visade att de mindre företagen drabbades hårdare. / This essay examines whether world events create abnormal effects of oil companies stock prices and whether these effects appear different depending on the companies’ different sizes. The analysis is performed using an event study conducted in six oil companies with three world events as a starting point. The selected world events consisted of two natural disasters and a greater economic event. The companies selected were divided into two groups of three companies, in which one group contained the larger companies and the second group the smaller ones. The conclusion that has been drawn from the study is that the events in two of the three cases studied caused significant abnormal deficit or excess returns of oil companies’ shares, which proves certain inefficiency of the market. The general outcome was that the economic event turned out to have a greater impact on the firms’ stock prices than the two natural disasters had. It was possible to distinguish a significant difference between the stock prices reactions of the larger and smaller firms regarding the economic event. The result showed that the smaller companies were affected to a larger extent.

A fundamental challenge in target detection in hyperspectral imagery is spectral variability. In target detection applications, we are provided with a pure target signature; we do not have a collection of samples that characterize the spectral variability of the target. Another problem is that the performance of stochastic detection algorithms such as the spectral matched filter can be detrimentally affected by the assumptions of multivariate normality of the data, which are often violated in practical situations. We address the challenge of lack of training samples by creating two models to characterize the target class spectral variability --the first model makes no assumptions regarding inter-band correlation, while the second model uses a first-order Markovbased scheme to exploit correlation between bands. Using these models, we present two techniques for meeting these challenges-the kernel-based support vector data description (SVDD) and spectral fringe-adjusted joint transform correlation (SFJTC). We have developed an algorithm that uses the kernel-based SVDD for use in full-pixel target detection scenarios. We have addressed optimization of the SVDD kernel-width parameter using the golden-section search algorithm for unconstrained optimization. We investigated a proper number of signatures N to generate for the SVDD target class and found that only a small number of training samples is required relative to the dimensionality (number of bands). We have extended decision-level fusion techniques using the majority vote rule for the purpose of alleviating the problem of selecting a proper value of s 2 for either of our target variability models. We have shown that heavy spectral variability may cause SFJTC-based detection to suffer and have addressed this by developing an algorithm that selects an optimal combination of the discrete wavelet transform (DWT) coefficients of the signatures for use as features for detection. For most scenarios, our results show that our SVDD-based detection scheme provides low false positive rates while maintaining higher true positive rates than popular stochastic detection algorithms. Our results also show that our SFJTC-based detection scheme using the DWT coefficients can yield significant detection improvement compared to use of SFJTC using the original signatures and traditional stochastic and deterministic algorithms.

Title from PDF of title page. / Document formatted into pages; contains 104 pages. / Thesis (M.S.I.E.)--University of South Florida, 2003. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: Medical decision problems are extremely complex owing to their dynamic nature, large number of variable factors, and the associated uncertainty. Decision support technology entered the medical field long after other areas such as the airline industry and the manufacturing industry. Yet, it is rapidly becoming an indispensable tool in medical decision making problems including the class of sequential decision problems. In these problems, physicians decide on a treatment plan that optimizes a benefit measure such as the treatment cost, and the quality of life of the patient. The last decade saw the emergence of many decision support applications in medicine. However, the existing models have limited applications to decision problems with very few states and actions. An urgent need is being felt by the medical research community to expand the applications to more complex dynamic problems with large state and action spaces. / ABSTRACT: This thesis proposes a methodology which models the class of sequential medical decision problems as a Markov decision process, and solves the model using a simulation based reinforcement learning (RL) algorithm. Such a methodology is capable of obtaining near optimal treatment strategies for problems with large state and action spaces. This methodology overcomes, to a large extent, the computational complexity of the value-iteration and policy-iteration algorithms of dynamic programming. An average reward reinforcement-learning algorithm is developed. The algorithm is applied on a sample problem of treating hereditary spherocytosis. The application demonstrates the ability of the proposed methodology to obtain effective treatment strategies for sequential medical decision problems. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.

Sparčiai kintant finansinių institucijų veiklos sąlygoms, didėjant finansinių rinkų nepastovumui bei veiklos mastams, atsirandant vis naujoms finansinėms priemonėms, o kartu su jomis ir naujoms finansinių institucijų rizikos rūšims, ypač išaugo prekybinio portfelio rizikos valdymo poreikis. Tą įrodo ir tai, kad po eilės solidžių ir pakankamai konservatyvių finansinių institucijų, tokių kaip Baring, Daiwa, Sumitomo, Metallgesellschaft, Orange County, Long Term Capital Management, bankrotų ar milžiniškų nuostolių patyrimo praeito amžiaus paskutiniame dešimtmetyje didžiosios pasaulio finansinės institucijos bei šalių centriniai bankai ėmė iš esmės griežtinti rinkos rizikos valdymo procedūras. Kaip parodė vėlesnė minėtų kompanijų istorijos analiz�����, pagrindinė jų nuostolių ar bankrotų priežastis buvo nesugebėjimas tinkamai valdyti prekybinį portfelį įtakojančios rinkos rizikos. Prekybinio portfelio rizikos valdymas tampa vis aktualesnis ir Lietuvos finansinėms institucijoms, ypač investicinių bei pensijų fondų valdytojams, investuojantiems į užsienio vertybinius popierius, denominuotus kitomis valiutomis nei litas ar euras. / The scientific problem of the dissertation is search of adequacy of the trading portfolio risk management methods and models to the current economic, technological, and informational circumstances of financial institutions. The main features of science novelty characteristic to this research are the following: (i)the comparative study on Value at Risk estimation methods allowed to make important theoretic conclusion that selection of Value at Risk estimation methods depends mostly on characteristics of the portfolio under investigation; theoretic recommendations regarding selection of Value at Risk estimation methods were suggested as well; (ii)the comparative study on performance of volatility forecasting models allowed to make important theoretic conclusion that selection of Value at Risk estimation methods depends on characteristics of the data under investigation and selected criteria for assessment of forecasting accuracy; in the context of risk management, the priority was given to operational rather than statistical accuracy assessment techniques in the context of risk management; (iii)the comparative study on risk adjustment measures allowed making important theoretic conclusion that selection of risk adjustment measures depends mostly on characteristics of the portfolio under investigation; theoretic recommendations regarding selection of risk adjustment measures were suggested as well.