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In this paper, we study the intradaily distributional and temporal properties of the IBM stock in the time period November 1990 until February 1991. We do this by exploratory analysis by means of semi Markov chains, i. e. a Markov chain where time between events is considered random. Furthermore, the behaviour of the methods is studied under some commonly used models.

In this paper, we use functional data analysis to model a time varying unconditional distribution of financial intraday returns. This is in the spirit of the recent development of realized volatility modeling (e.g. Andersen et al, 2001), where one of the moments of this unconditional distribution, the realized volatility, is assumed to change smoothly over time. In the approach used in this paper we instead assume that the entire distribution function changes smoothly over time. This enables us to study auto- and cross dependencies of different parts of the unconditional distribution with no model assumptions but the smoothness of the distribution function. We develop a simulation based procedure for statistical inference of the model. Finally, we apply the method to the Swiss Franc-US Dollar exchange rate 1985-1991.

In this paper, the authors examine the effects of measurement errors on volatility measures. This is done by first expressing the moment properties of general volatility models with measurement errors in terms of the corresponding moments for the underlying unobserved signal process. Then the consequences of measurement errors for some GARCH and stochastic volatility models are evaluated. It is shown that measurement error causes the autocorrelation function, here for the squared process, to start and remain lower than for the underlying unobserved signal process. The size of the effects are highly dependent on the degree of persistence in the volatility. Finally, the consequences of measurement errors on time-varying VaR measures are studied.

In a first order autoregressive model with drift, we derive the likelihood ratio test for a unit root against the stationary alternative. We also derive the test in a state space model with trend. Finite sample and asymptotic critical values are obtained by Monte Carlo simulations. A simulation study investigates the power performance of the likelihood ratio test and we also examine how a bias correction of the test affects the results.

Kronisk Myeloisk Leukemi (KML) är en form av blodcancer som idag har goda behandlingsmöjligheter och en hög andel överlevande. Vid behandling av sjukdomen mäts responsen efter 12 månader genom att undersöka om patienten uppnått MMR, komplett cytogenetisk respons. Målet i denna uppsats är att hitta variabler som skiljer de patienter som visar eftersökt respons från dem som inte gör det – för att kunna konstruera en modell som skiljer dessa båda grupper åt och som har en god förmåga att klassificera observationerna.

Modellen konstrueras med hjälp av metoden diskriminantanalys och baseras på ett datamaterial som är en sammanställning av tre olika studier. Klassificeringsresultatet för den aktuella metoden jämförs med en logistisk regressions resultat av samma datamaterial med avseende på metodernas förmåga till klassificering av individer. Variablerna som inkluderas i den slutgiltiga diskriminantanalysen är typ av behandling, riskgrupp, hemoglobinhalt, andel vita blodkroppar, kön och respons på behandling efter 3 månader. Klassificeringsförmågan är marginellt bättre än för den logistiska regressionen.

Microfinance programs like the Self Help Bank Linkage Program in India have been increasingly promoted for their positive economic impact and the belief that they empower women. However, only a few studies rigorously examine the link between microfinance and women’s empowerment. This paper contributes by arguing that women empowerment takes place when women challenge the existing social norms and culture, to effectively improve their well being. It empirically validates this hypothesis by using quasi-experimental household sample data collected for five states in India for 2000 and 2003. A general structural model is estimated by employing appropriate techniques to treat the ordinal variables in  order to estimate the impact of the Self Help Group (SHG) on women empowerment for 2000 and 2003. The results strongly demonstrate that on average, there is a significant increase in the women empowerment of the SHG members group. No such significant change is observed however, for the members of the control group. The elegance of the result lies in the fact that the group of SHG participants show clear evidence of a significant and higher empowerment, while allowing for the possibility that some members might have been more empowered than others.

Microfinance programs like Self Help Group Bank linkage program (SHG), aim to empower women through provision of financial services. We investigate this further to determine whether it is the economic or the non-economic factors that have a greater impact on empowering women. Using household survey data on SHG from India, a general structural model is adopted where the latent women empowerment and its latent components (economic factors and financial confidence, managerial control, behavioural changes, education and networking, communication and political participation and awareness) are measured using observed indicators. The results show that for SHG members, economic factors, managerial control and behavioural changes are the most significant factors in empowering women.

Microfinance programmes like the Self Help Bank Linkage Program in India have been increasingly promoted for their positive economic impact and the belief that they empower women. However, only a few studies rigorously examine the link between microfinance and women's empowerment. This article contributes to this discussion by arguing that women's empowerment takes place when women challenge the existing social norms and culture, to effectively improve their well-being. It empirically validates this hypothesis by using quasi-experimental household sample data collected for five states in India for 2000 and 2003. A general model is estimated by employing appropriate techniques to treat the ordinal variables in order to estimate the impact of the Self Help Group (SHG) on women's empowerment for 2000 and 2003. The results strongly demonstrate that on average, there is a significant increase in the empowerment of women in the SHG members group. No such significant change is observed however, for the members of the control group. The elegance of the result lies in the fact that the group of SHG participants show clear evidence of a significant and higher empowerment, while allowing for the possibility that some members might have been more empowered than others.

Reliable classification systems and clinical tests are sought for the care of patients with low back pain (LBP). The objectives of this clinical study were to evaluate inter-examiner reliability in the classification of patients with LBP, the influence of radiological findings on the classification and the reliability of some clinical tests. Two examiners independently assessed 50 outpatients with LBP. Inter-examiner reliability in classification of patients with LBP using Kirkkaldy-Willis classification (KWC) system and in 30 clinical tests was calculated as percentage agreement and kappa coefficients (kappa). Inter-examiner reliability was excellent (kappa > 0.8) for classification according to KWC. Radiological findings did not influence the reliability. Age of the patient, movement range, and pain and neurological signs seemed to guide the decision on classification. The reliability of clinical tests was good (kappa > 0.6) in 6 tests and moderate (kappa > 0.4) in 12 tests. Good inter-examiner reliability was found for the SLR test, movement range and sensibility testing with spurs in dermatome areas. We conclude that the KWC for classifying patients with LBP seems to be a reliable classification system depending on a few key observations and that moderate and good inter-examiner reliability can be achieved in several clinical tests in the assessment of LBP.

Statistisk inferens grundar sig ofta i ett fördelningsantagande beträffande den underliggande datagenereringsprocessen. Huruvida antagandet håller eller ej är viktigt för testens validitet. I denna uppsats undersöks likelihoodkvottestet (LR) och Hettmansperger & McKean's test (HM), i en regressionskontext. För LR-testet görs ett normalitetsantagande vilket jämförs mot HM-testet, för vilket ett fördelningsantagande inte behöver göras. Uppsatsen syftar till att jämföra testens styrka för att avgöra vilket av de två som är optimalt. Jämförelsen baseras dels på empiriska data och dels på simulerade data. Det empiriska datasetet återsamplas med icke-parametrisk bootstrap och de simulerade datasetet genereras med parametrisk bootstrap under ett normalfördelningsantagande samt för ett t-fördelningsantagande. Resultaten för det empiriska datasetet tyder på att HM-testet generellt uppnår högst styrka. Utfallet för det simulerade datasetet indikerar att LR- testet generellt erhåller högst styrka. Vid en jämförelse av testernas empiriska signifikansnivåer pekar resultaten på att Likelihoodkvottestet följer den asymptotiska fördelningen tämligen väl medan Hettmansperger & McKean's test konsekvent inflaterar de empiriska signifikansnivåerna.

Tidigare forskning på finansiella data har visat att det i vissa fall föreligger en negativ korrelation mellan historisk avkastning och framtida volatilitet. Alltså att en negativ nyhet gör att volatiliteten ökar mer än vad en positiv nyhet hade orsakat. Detta fenomen benämns som asymmetrisk volatilitet eller leverage effect och har tydliga ekonomiska och ekonometriska implikationer. Ickelinjära GARCH-modeller och tester har tagits fram för att behandla och undersöka detta fenomen. Då vi skattar modellerna paå den realiserade avkastningen för HQ aktien får vi fram att omvänt resonemang gäller för våra data. Det innebär, för HQ aktien, att en positiv nyhet gör att volatiliteten ökar mer än vad en negativ nyhet av samma storlek hade orsakat.

Rhodiola rosea (roseroot) extract is a commercially successful product, primarily used to reduce the effect of fatigue on physical and mental performance. In this perspective we present our investigation of the most recent studies performed on human subjects. With a focus on the statistical methods we found considerable shortcomings in all but one of the studies that claim significant improvement from roseroot extract. Overall, the study designs have not been well explained. Experimental results have been confused and appear to be in some cases incorrect. Some of the conclusions are based on selected results and contradicting data have not been adequately taken into account. We point to other studies of higher quality performed on roseroot, several that found no significant effect and one that did. We conclude that the currently available evidence for the claimed effects is insufficient and that the effect of Rhodiola rosea is in need of further investigation before therapeutic claims can be made.