Hedging Options with Different Time Units in the Pricing Models

This study examined the effects of the Greeks of the options and the trading results of delta hedging strategies, with three different time units or option-pricing models. These time units were calendar time, trading time and continuous time using discrete approximation (CTDA) time. The CTDA time model is a pricing model, that among others accounts for intraday and weekend, patterns in volatility. For the CTDA time model some additional theta measures, which were believed to be usable in trading, were developed. The study appears to verify that there were differences in the Greeks with different time units. It also revealed that these differences influence the delta hedging of options or portfolios. Although it is difficult to say anything about which is the most usable of the different time models, as this much depends on the traders view of the passing of time, different market conditions and different portfolios, the CTDA time model can be viewed as an attractive alternative.

An Empirical Comparison of Linear and Nonlinear Volatility Models for Nordic Stock Returns

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.

Evaluating Option Pricing Models

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.

Development of mass balance models for lakes

Yhteenveto: Järvien ainetasemallien kehittäminen.

Snow cover models in operational watershed forecasting

Yhteenveto: Lumimallit vesistöjen ennustemalleissa

Transcriptional analysis of persistent Chlamydia pneumoniae infection in vitro

Chlamydia pneumoniae can cause acute respiratory infections including pneumonia. Repeated and persistent Chlamydia infections occur and persistent C. pneumoniae infection may have a role in the pathogenesis of atherosclerosis and coronary heart disease and may also contribute to the development of chronic inflammatory lung diseases like chronic obstructive pulmonary disease (COPD) and asthma. In this thesis in vitro models for persistent C. pneumonia infection were established in epithelial and monocyte/macrophage cell lines. Expression of host cell genes in the persistent C. pneumoniae infection model of epithelial cells was studied by microarray and RT-PCR. In the monocyte/macrophage infection model expression of selected C. pneumoniae genes were studied by RT-PCR and immunofluorescence microscopy. Chlamydia is able to modulate host cell gene expression and apoptosis of host cells, which may assist Chlamydia to evade the host cells' immune responses. This, in turn, may lead to extended survival of the organism inside epithelial cells and promote the development of persistent infection. To simulate persistent C. pneumoniae infection in vivo, we set up a persistent infection model exposing the HL cell cultures to IFN-gamma. When HL cell cultures were treated with moderate concentration of IFN-gamma, the replication of C. pneumoniae DNA was unaffected while differentiation into infectious elementary bodies (EB) was strongly inhibited. By transmission electron microscopy small atypical inclusions were identified in IFN-gamma treated cultures. No second cycle of infection was observed in cells exposed to IFN-gamma , whereas C. pneumoniae was able to undergo a second cycle of infection in unexposed HL cells. Although monocytic cells can naturally restrict chlamydial growth, IFN-gamma further reduced production of infectious C. pneumoniae in Mono Mac 6 cells. Under both studied conditions no second cycle of infection could be detected in monocytic cell line suggesting persistent infection in these cells. As a step toward understanding the role of host genes in the development and pathogenesis of persistent C. pneumoniae infection, modulation of host cell gene expression during IFN-gamma induced persistent infection was examined and compared to that seen during active C. pneumoniae infection or IFN-gamma treatment. Total RNA was collected at 6 to 150 h after infection of an epithelial cell line (HL) and analyzed by a cDNA array (available at that time) representing approximately 4000 human transcripts. In initial analysis 250 of the 4000 genes were identified as differentially expressed upon active and persistent chlamydial infection and IFN-gamma treatment. In persistent infection more potent up-regulation of many genes was observed in IFN-gamma induced persistent infection than in active infection or in IFN-gamma treated cell cultures. Also sustained up-regulation was observed for some genes. In addition, we could identify nine host cell genes whose transcription was specifically altered during the IFN-gamma induced persistent C. pneumoniae infection. Strongest up-regulation in persistent infection in relation to controls was identified for insulin like growth factor binding protein 6, interferon-stimulated protein 15 kDa, cyclin D1 and interleukin 7 receptor. These results suggest that during persistent infection, C. pneumoniae reprograms the host transcriptional machinery regulating a variety of cellular processes including adhesion, cell cycle regulation, growth and inflammatory response, all of which may play important roles in the pathogenesis of persistent C. pneumoniae infection. C. pneumoniae DNA can be detected in peripheral blood mononuclear cells indicating that the bacterium can also infect monocytic cells in vivo and thereby monocytes can assist the spread of infection from the lungs to other anatomical sites. Persistent infection established at these sites could promote inflammation and enhance pathology. Thus, the mononuclear cells are in a strategic position in the development of persistent infection. To investigate the intracellular replication and fate of C. pneumoniae in mononuclear cells we analyzed the transcription of 11 C. pneumoniae genes in Mono Mac 6 cells during infection by real time RT-PCR. Our results suggest that the transcriptional profile of the studied genes in monocytes is different from that seen in epithelial cells and that IFN-gamma has a less significant effect on C. pneumoniae transcription in monocytes. Furthermore, our study shows that type III secretion system (T3SS) related genes are transcribed and that Chlamydia possesses a functional T3SS during infection in monocytes. Since C. pneumoniae infection in monocytes has been implicated to have reduced antibiotic susceptibility, this creates opportunities for novel therapeutics targeting T3SS in the management of chlamydial infection in monocytes.

World parliament – fact or fiction? On the feasibility of world parliamentary models

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.

Models of Dispersal and Diversification

Ecology and evolutionary biology is the study of life on this planet. One of the many methods applied to answering the great diversity of questions regarding the lives and characteristics of individual organisms, is the utilization of mathematical models. Such models are used in a wide variety of ways. Some help us to reason, functioning as aids to, or substitutes for, our own fallible logic, thus making argumentation and thinking clearer. Models which help our reasoning can lead to conceptual clarification; by expressing ideas in algebraic terms, the relationship between different concepts become clearer. Other mathematical models are used to better understand yet more complicated models, or to develop mathematical tools for their analysis. Though helping us to reason and being used as tools in the craftmanship of science, many models do not tell us much about the real biological phenomena we are, at least initially, interested in. The main reason for this is that any mathematical model is a simplification of the real world, reducing the complexity and variety of interactions and idiosynchracies of individual organisms. What such models can tell us, however, both is and has been very valuable throughout the history of ecology and evolution. Minimally, a model simplifying the complex world can tell us that in principle, the patterns produced in a model could also be produced in the real world. We can never know how different a simplified mathematical representation is from the real world, but the similarity models do strive for, gives us confidence that their results could apply. This thesis deals with a variety of different models, used for different purposes. One model deals with how one can measure and analyse invasions; the expanding phase of invasive species. Earlier analyses claims to have shown that such invasions can be a regulated phenomena, that higher invasion speeds at a given point in time will lead to a reduction in speed. Two simple mathematical models show that analysis on this particular measure of invasion speed need not be evidence of regulation. In the context of dispersal evolution, two models acting as proof-of-principle are presented. Parent-offspring conflict emerges when there are different evolutionary optima for adaptive behavior for parents and offspring. We show that the evolution of dispersal distances can entail such a conflict, and that under parental control of dispersal (as, for example, in higher plants) wider dispersal kernels are optimal. We also show that dispersal homeostasis can be optimal; in a setting where dispersal decisions (to leave or stay in a natal patch) are made, strategies that divide their seeds or eggs into fractions that disperse or not, as opposed to randomized for each seed, can prevail. We also present a model of the evolution of bet-hedging strategies; evolutionary adaptations that occur despite their fitness, on average, being lower than a competing strategy. Such strategies can win in the long run because they have a reduced variance in fitness coupled with a reduction in mean fitness, and fitness is of a multiplicative nature across generations, and therefore sensitive to variability. This model is used for conceptual clarification; by developing a population genetical model with uncertain fitness and expressing genotypic variance in fitness as a product between individual level variance and correlations between individuals of a genotype. We arrive at expressions that intuitively reflect two of the main categorizations of bet-hedging strategies; conservative vs diversifying and within- vs between-generation bet hedging. In addition, this model shows that these divisions in fact are false dichotomies.

Applications of Treatment Effects Models and Semiparametric Estimation

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.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

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).