Effects of seed origin latitude on the timing of height growth cessation and field performance of silver birch

The aim of this thesis was to increase our knowledge about the effects of seed origin on the timing of height growth cessation and field performance of silver birch from different latitudes, with special attention paid to the browsing damage by moose in young birch plantations. The effect of seed origin latitude and sowing time on timing of height growth cessation of first-year seedlings was studied in a greenhouse experiment with seven seed origins (lat. 58º - 67ºN). Variation in critical night length (CNL) for 50 % bud set within two latitudinally distant stands (60º and 67ºN) was studied in three phytotron experiments. Browsing by moose on 5-11 -year-old silver birch saplings from latitudinally different seed origins (53º - 67ºN) was studied in a field experiment in southern Finland. Yield and stem quality of 22-year-old silver birch trees of Baltic, Finnish and Russian origin (54º - 63ºN) and the effect of latitudinal seed transfers were studied in two provenance trials at Tuusula, southern and Viitasaari, central Finland. The timing of height growth cessation depended systematically on latitude of seed origin and sowing date. The more northern the seed origin, the earlier the growth cessation and the shorter the growth period. Later sowing dates delayed growth cessation but also shortened the growth period. The mean CNL of the southern ecotype was longer, 6.3 ± 0.2 h (95 % confidence interval), than that of the northern ecotype, 3.1 ± 0.3 h. Within-ecotype variance of the CNL was higher in the northern ecotype (0.484 h2) than in the southern ecotype (0.150 h2). Browsing by moose decreased with increasing latitude of seed origin and sapling height. Origins transferred from more southern latitudes were more heavily browsed than the more northern native ones. Southern Finnish seed origins produced the highest volume per unit area in central Finland (lat. 63º11'N). Estonian and north Latvian stand seed origins, and the southern Finnish plus tree origins, were the most productive ones in southern Finland (lat. 60º21'N). Latitudinal seed transfer distance had a significant effect on survival, stem volume/ha and proportion of trees with a stem defect. The relationship of both survival and stem volume/ha to the latitudinal seed transfer distance was curvilinear. Volume was increased by transferring seed from ca. 2 degrees of latitude from the south. A longer transfer from the south, and transfer from the north, decreased the yield. The proportion of trees with a stem defect increased linearly in relation to the latitudinal seed transfer distance from the south.

Informational efficiency of the European Union emission allowance market

This thesis studies the informational efficiency of the European Union emission allowance (EUA) market. In an efficient market, the market price is unpredictable and profits above average are impossible in the long run. The main research problem is does the EUA price follow a random walk. The method is an econometric analysis of the price series, which includes an autocorrelation coefficient test and a variance ratio test. The results reveal that the price series is autocorrelated and therefore a nonrandom walk. In order to find out the extent of predictability, the price series is modelled with an autoregressive model. The conclusion is that the EUA price is autocorrelated only to a small degree and that the predictability cannot be used to make extra profits. The EUA market is therefore considered informationally efficient, although the price series does not fulfill the requirements of a random walk. A market review supports the conclusion, but it is clear that the maturing of the market is still in process.

Stiffer Optical Tweezers through Real-Time Feedback Control

This thesis integrates real-time feedback control into an optical tweezers instrument. The goal is to reduce the variance in the trapped bead s position, -effectively increasing the trap stiffness of the optical tweezers. Trap steering is done with acousto-optic deflectors and control algorithms are implemented with a field-programmable gate array card. When position clamp feedback control is on, the effective trap stiffness increases 12.1-times compared to the stiffness without control. This allows improved spatial control over trapped particles without increasing the trapping laser power.

Wind drift of snowfall between the radar volume and ground

This study evaluates how the advection of precipitation, or wind drift, between the radar volume and ground affects radar measurements of precipitation. Normally precipitation is assumed to fall vertically to the ground from the contributing volume, and thus the radar measurement represents the geographical location immediately below. In this study radar measurements are corrected using hydrometeor trajectories calculated from measured and forecasted winds, and the effect of trajectory-correction on the radar measurements is evaluated. Wind drift statistics for Finland are compiled using sounding data from two weather stations spanning two years. For each sounding, the hydrometeor phase at ground level is estimated and drift distance calculated using different originating level heights. This way the drift statistics are constructed as a function of range from radar and elevation angle. On average, wind drift of 1 km was exceeded at approximately 60 km distance, while drift of 10 km was exceeded at 100 km distance. Trajectories were calculated using model winds in order to produce a trajectory-corrected ground field from radar PPI images. It was found that at the upwind side from the radar the effective measuring area was reduced as some trajectories exited the radar volume scan. In the downwind side areas near the edge of the radar measuring area experience improved precipitation detection. The effect of trajectory-correction is most prominent in instant measurements and diminishes when accumulating over longer time periods. Furthermore, measurements of intensive and small scale precipitation patterns benefit most from wind drift correction. The contribution of wind drift on the uncertainty of estimated Ze (S) - relationship was studied by simulating the effect of different error sources to the uncertainty in the relationship coefficients a and b. The overall uncertainty was assumed to consist of systematic errors of both the radar and the gauge, as well as errors by turbulence at the gauge orifice and by wind drift of precipitation. The focus of the analysis is error associated with wind drift, which was determined by describing the spatial structure of the reflectivity field using spatial autocovariance (or variogram). This spatial structure was then used with calculated drift distances to estimate the variance in radar measurement produced by precipitation drift, relative to the other error sources. It was found that error by wind drift was of similar magnitude with error by turbulence at gauge orifice at all ranges from radar, with systematic errors of the instruments being a minor issue. The correction method presented in the study could be used in radar nowcasting products to improve the estimation of visibility and local precipitation intensities. The method however only considers pure snow, and for operational purposes some improvements are desirable, such as melting layer detection, VPR correction and taking solid state hydrometeor type into account, which would improve the estimation of vertical velocities of the hydrometeors.

Computational Methods for Detecting Large-Scale Chromosome Rearrangements in SNP Data

Large-scale chromosome rearrangements such as copy number variants (CNVs) and inversions encompass a considerable proportion of the genetic variation between human individuals. In a number of cases, they have been closely linked with various inheritable diseases. Single-nucleotide polymorphisms (SNPs) are another large part of the genetic variance between individuals. They are also typically abundant and their measuring is straightforward and cheap. This thesis presents computational means of using SNPs to detect the presence of inversions and deletions, a particular variety of CNVs. Technically, the inversion-detection algorithm detects the suppressed recombination rate between inverted and non-inverted haplotype populations whereas the deletion-detection algorithm uses the EM-algorithm to estimate the haplotype frequencies of a window with and without a deletion haplotype. As a contribution to population biology, a coalescent simulator for simulating inversion polymorphisms has been developed. Coalescent simulation is a backward-in-time method of modelling population ancestry. Technically, the simulator also models multiple crossovers by using the Counting model as the chiasma interference model. Finally, this thesis includes an experimental section. The aforementioned methods were tested on synthetic data to evaluate their power and specificity. They were also applied to the HapMap Phase II and Phase III data sets, yielding a number of candidates for previously unknown inversions, deletions and also correctly detecting known such rearrangements.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Evolutionary Genetics in the WIld : from Populations to Individuals

Predicting evolutionary outcomes and reconstructing past evolutionary transitions are among the main goals of evolutionary biology. Ultimately, understanding the mechanisms of evolutionary change will also provide answers to the timely question of whether and how organisms will adapt to changing environmental conditions. In this thesis, I have investigated the relative roles of natural selection, random genetic drift and genetic correlations in the evolution of complex traits at different levels of organisation from populations to individuals. I have shown that natural selection has been the driving force behind body shape divergence of marine and freshwater threespine stickleback (Gasterosteus aculeatus) populations, while genetic drift may have played a significant role in the more fine scale divergence among isolated freshwater populations. These results are concurrent with the patterns that have emerged in the published studies comparing the relative importance of natural selection and genetic drift as explanations for population divergence in different traits and taxa. I have also shown that body shape and armour divergence among threespine stickleback populations is likely to be biased by the patterns of genetic variation and covariation. Body shape and armour variation along the most likely direction of evolution the direction of maximum genetic variance reflects the general patterns of variation observed wild populations across the distribution range of the threespine stickleback. Conversely, it appears that genetic correlations between the sexes have not imposed significant constraints on the evolution of sexual dimorphism in threespine stickleback body shape and armour. I have demonstrated that the patterns of evolution seen in the wild can be experimentally recreated to tease out the effects of different selection agents in detail. In addition, I have shown how important it is to take into account the correlative nature of traits, when making interpretations about the effects of natural selection on individual traits. Overall, this thesis provides a demonstration of how considering the relative roles of different mechanism of evolutionary change at different levels of organisation can aid in an emergence of a comprehensive picture of how adaptive divergence in wild populations occurs.

Men´s health behaviour, health beliefs and need for health counselling : A study amongst 40-year-old males from one Helsinki City region

Tavoitteena oli tutkia 40-vuotiaiden miesten terveyskäyttäytymistä, terveysuskomuksia ja miesten saamaa terveysneuvontaa Helsingissä. 273 miestä vastasi kyselyyn ja osallistui terveystutkimuksiin. Terveydentilan perusteella miehet arvioitiin matalan (n=145) ja korkean (n=128) riskin ryhmiin. Khin neliö-testillä tutkittiin elämäntapa- ja riskitekijöitä koetun terveyden (hyvä, keskinkertainen/huono) luokissa ja verrattiin matalan ja korkean riskin ryhmiä em. tekijöiden osalta. Askeltavalla logistisella regressiomallilla analysoitiin tulosmuuttujia taustatekijöiden, terveyskäyttäytymisen, terveysuskomusten ja kliinisten riskitekijöiden avulla sekä arvioitiin oireiden ja vaivojen suhdetta koettuun terveydentilaan. Korkeassa riskissä olevien terveyttä seurattiin vuosina 2001–2004 analysoimalla mini-intervention vaikutusta terveysriskeihin ja elintapoihin varianssianalyysin avulla (ANOVA) (n=46). Matalasta vastausprosentista johtuen (39.6%), ei-vastanneiden aineistoa kerättiin käyttämällä syvähaastattelua (n=28) sekä puhelinkyselyä (n=40). Lopullinen aineisto koostui 341 miehestä. Tulokset osoittivat, että miehillä oli sydän- ja verisuonitautiriskejä. Kaksi kolmesta osallistuneista oli ylipainoisia tai lihavia, yli kolmanneksella vyötärönympärys oli ≥100 cm, ja yli 40%:llä oli diastolinen verenpaine ≥90 mmHg. Yli puolet tupakoi päivittäin ja 40% käytti alkoholia runsaasti. Ristiriitaisuutta ilmensi se, että huolimatta riskitekijöistä noin puolet miehistä koki terveydentilansa hyväksi. Sairauden tai vamman puute, hyvä suun terveydentila ja normaali vyötärönympärys olivat yhteydessä hyväksi koettuun terveydentilaan. Suora yhteys voitiin havaita omaisten tarjoaman neuvonnan ja vähäisen alkoholin käytön välillä. Masennus ja unettomuus olivat voimakkaasti yhteydessä loppuun palamiseen. Miehillä oli erilaisia fyysisiä ja psyykkisiä oireita, jotka korreloivat voimakkaasti masennuksen kanssa. Pieni määrä miehistä koki saaneensa terveysneuvontaa hoitohenkilökunnalta verrattuna perheenjäseniltä saatuun ohjaukseen. Korkeariskisten miesten (n=46) arvot parantuivat merkitsevästi lyhyellä aikavälillä. Kolesteroliarvoja lukuunottamatta ne palautuivat kolmen vuoden kuluttua alkumittausarvoja kohti. Laadullinen tutkimus osoitti, että “ei-vastanneet“ eivät osallistuneet projektiin, sillä he olivat oireettomia tai kiireisiä. Heillä todettiin samoja terveysriskejä kuin projektiin osallistuneilla. Syvähaastattelussa miehet toivat esille kokemuksiaan huolista, vihan tunteista, peloista ja yksinäisyydestä. Hoidonantajien on tärkeää ymmärtää ristiriidat miesten subjektiivisen ja objektiivisen terveydentilan välillä, mikä auttaa havaitsemaan esteitä terveyskäyttäytymiselle. Yhä enemmän tarvitaan yhteistyötä yksityisen ja julkisen terveydenhuollon välillä varmistamaan terveystottumusten jatkuminen miesten keskuudessa.

Timing of puberty : Genetic regulation

In the general population, the timing of puberty is normally distributed. This variation is determined by genetic and environmental factors, but the exact mechanisms underlying these influences remain elusive. The purpose of this study was to gain insight into genetic regulation of pubertal timing. Contributions of genetic versus environmental factors to the normal variation of pubertal timing were explored in twins. Familial occurrence and inheritance patterns of constitutional delay of growth and puberty, CDGP (a variant of normal pubertal timing), were studied in pedigrees of patients with this condition. To ultimately detect genes involved in the regulation of pubertal timing, genetic loci conferring susceptibility to CDGP were mapped by linkage analysis in the same family cohort. To subdivide the overall phenotypic variance of pubertal timing into genetic and environmental components, genetic modeling based on monozygous twins sharing 100% and dizygous twins sharing 50% of their genes was used in 2309 girls and 1828 boys from the FinnTwin 12-17 study. The timing of puberty was estimated from height growth, i.e. change in the relative height between the age when pubertal growth velocity peaks in the general population and adulthood. This reflects the percentage of adult height achieved at the average peak height velocity age, and thus, pubertal timing. Boys and girls diagnosed with CDGP were gathered through medical records from six pediatric clinics in Finland. First-degree relatives of the probands were invited to participate by letter; altogether, 286 families were recruited. When possible, families were extended to include also second-, third-, or fourth-degree relatives. The timing of puberty in all family members was primarily assessed from longitudinal growth data. Delayed puberty was defined by onset of pubertal growth spurt or peak height velocity taking place 1.5 (relaxed criterion) or 2 SD (strict criterion) beyond the mean. If growth data were unavailable, pubertal timing was based on interviews. In this case, CDGP criteria were set as having undergone pubertal development more than 2 (strict criterion) or 1.5 years (relaxed criterion) later than their peers, or menarche after 15 (strict criterion) or 14 years (relaxed criterion). Familial occurrence of strict CDGP was explored in families of 124 patients (95 males and 29 females) from two clinics in Southern Finland. In linkage analysis, we used relaxed CDGP criteria; 52 families with solely growth data-based CDGP diagnoses were selected from all clinics. Based on twin data, genetic factors explain 86% and 82% of the variance of pubertal timing in girls and boys, respectively. In families, 80% of male and 76% of female probands had affected first-degree relatives, in whom CDGP was 15 times more common than the expected (2.5%). In 74% (17 of 23) of the extended families with only one affected parent, familial patterns were consistent with autosomal dominant inheritance. By using 383 multiallelic markers and subsequently fine-mapping with 25 additional markers, significant linkage for CDGP was detected to the pericentromeric region of chromosome 2, to 2p13-2q13 (multipoint HLOD 4.44, α 0.41). The findings of the large twin study imply that the vast majority of the normal variation of pubertal timing is attributed to genetic effects. Moreover, the high frequency of dominant inheritance patterns and the large number of affected relatives of CDGP patients suggest that genetic factors also markedly contribute to constitutional delay of puberty. Detection of the locus 2p13-2q13 in the pericentromeric region of chromosome 2 associating with CDGP is one step towards unraveling the genes that determine pubertal timing.

Primordial Isocurvature Perturbation in Light of CMB and LSS Data

The increased accuracy in the cosmological observations, especially in the measurements of the comic microwave background, allow us to study the primordial perturbations in grater detail. In this thesis, we allow the possibility for a correlated isocurvature perturbations alongside the usual adiabatic perturbations. Thus far the simplest six parameter \Lambda CDM model has been able to accommodate all the observational data rather well. However, we find that the 3-year WMAP data and the 2006 Boomerang data favour a nonzero nonadiabatic contribution to the CMB angular power sprctrum. This is primordial isocurvature perturbation that is positively correlated with the primordial curvature perturbation. Compared with the adiabatic \Lambda CMD model we have four additional parameters describing the increased complexity if the primordial perturbations. Our best-fit model has a 4% nonadiabatic contribution to the CMB temperature variance and the fit is improved by \Delta\chi^2 = 9.7. We can attribute this preference for isocurvature to a feature in the peak structure of the angular power spectrum, namely, the widths of the second and third acoustic peak. Along the way, we have improved our analysis methods by identifying some issues with the parametrisation of the primordial perturbation spectra and suggesting ways to handle these. Due to the improvements, the convergence of our Markov chains is improved. The change of parametrisation has an effect on the MCMC analysis because of the change in priors. We have checked our results against this and find only marginal differences between our parametrisation.

Generalised regression estimation for domain class frequencies

This study examines the properties of Generalised Regression (GREG) estimators for domain class frequencies and proportions. The family of GREG estimators forms the class of design-based model-assisted estimators. All GREG estimators utilise auxiliary information via modelling. The classic GREG estimator with a linear fixed effects assisting model (GREG-lin) is one example. But when estimating class frequencies, the study variable is binary or polytomous. Therefore logistic-type assisting models (e.g. logistic or probit model) should be preferred over the linear one. However, other GREG estimators than GREG-lin are rarely used, and knowledge about their properties is limited. This study examines the properties of L-GREG estimators, which are GREG estimators with fixed-effects logistic-type models. Three research questions are addressed. First, I study whether and when L-GREG estimators are more accurate than GREG-lin. Theoretical results and Monte Carlo experiments which cover both equal and unequal probability sampling designs and a wide variety of model formulations show that in standard situations, the difference between L-GREG and GREG-lin is small. But in the case of a strong assisting model, two interesting situations arise: if the domain sample size is reasonably large, L-GREG is more accurate than GREG-lin, and if the domain sample size is very small, estimation of assisting model parameters may be inaccurate, resulting in bias for L-GREG. Second, I study variance estimation for the L-GREG estimators. The standard variance estimator (S) for all GREG estimators resembles the Sen-Yates-Grundy variance estimator, but it is a double sum of prediction errors, not of the observed values of the study variable. Monte Carlo experiments show that S underestimates the variance of L-GREG especially if the domain sample size is minor, or if the assisting model is strong. Third, since the standard variance estimator S often fails for the L-GREG estimators, I propose a new augmented variance estimator (A). The difference between S and the new estimator A is that the latter takes into account the difference between the sample fit model and the census fit model. In Monte Carlo experiments, the new estimator A outperformed the standard estimator S in terms of bias, root mean square error and coverage rate. Thus the new estimator provides a good alternative to the standard estimator.

Origins of the sex differences in handedness and mental rotation ability : genetic, environmental and hormonal effects

In humans, well-replicated and robust sex differences in cognitive functions exist for handedness and mental rotation ability. A common characteristic in human cognitive functions is the lateralization of language functions. Handedness is a common measure of laterality and is related to language lateralization. The prevalence of left-handedness is higher in males than in females, the male to female ratio being about 1.2. Among cognitive abilities, the largest sex difference is evident in the Vandenberg and Kuse Mental Rotation Test (MRT), which requires the ability to rotate objects in mental space. On average, males achieve scores one standard deviation higher than females in the MRT. The present thesis investigated the origins of the sex differences in laterality and spatial ability as represented by handedness and mental rotation ability, respectively. Two population-based Finnish twin cohorts were utilized in this study. Handedness was studied in 25 810 twins and 4068 singletons born before 1958 from the Older Finnish Twin Cohort, and in 4736 twins born in 1983-87 from the FinnTwin12. MRT was studied in a sub-sample of 804 young adult participants from the FinnTwin12 sample. The main findings of this study were: 1) the prevalence of left-handedness was higher among males than among females in both singletons and in twins; 2) males had significantly higher scores than females in MRT; 3) about one quarter of the variance in handedness and about half of the variance in MRT was explained by genetic effects, whereas the remainder of the variance in these traits was explained by environmental effects unique to each individual. The magnitude of the genetic effects was similar in both sexes; 4) left-handedness was significantly less common in female co-twins of a male than in female co-twins of a female, and female co-twins of a male scored significantly higher than did female co-twins of a female in the Mental Rotation Test. This dissertation discusses whether these differences between females from opposite- and same-sex twin pairs are due to the prenatal transfer of testosterone from the male fetus in females with male co-twins or whether they arise from postnatal socialization effects.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.