Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Proteomic analysis of membrane rafts of melanoma cells identifies protein patterns characteristic of the tumor progression stage.

The molecular mechanisms controlling the progression of melanoma from a localized tumor to an invasive and metastatic disease are poorly understood. In the attempt to start defining a functional protein profile of melanoma progression, we have analyzed by LC-MS/MS the proteins associated with detergent resistant membranes (DRMs), which are enriched in cholesterol/sphingolipids-containing membrane rafts, of melanoma cell lines derived from tumors at different stages of progression. Since membrane rafts are involved in several biological processes, including signal transduction and protein trafficking, we hypothesized that the association of proteins with rafts can be regulated during melanoma development and affect protein function and disease progression. We have identified a total of 177 proteins in the DRMs of the cell lines examined. Among these, we have found groups of proteins preferentially associated with DRMs of either less malignant radial growth phase/vertical growth phase (VGP) cells, or aggressive VGP and metastatic cells suggesting that melanoma cells with different degrees of malignancy have different DRM profiles. Moreover, some proteins were found in DRMs of only some cell lines despite being expressed at similar levels in all the cell lines examined, suggesting the existence of mechanisms controlling their association with DRMs. We expect that understanding the mechanisms regulating DRM targeting and the activity of the proteins differentially associated with DRMs in relation to cell malignancy will help identify new molecular determinants of melanoma progression.

Is it the grain size or the characteristic pore size that controls the induced polarization relaxation time of clean sands and sandstones?

There is a wide range of evidence to suggest that permeability can be constrained through of induced polarization measurements. For clean sands and sandstones, current mechanistic models of induced polarization predict a relationship between the low-frequency time constant inferred from induced polarization measurements and the grain diameter. A number of observations do, however, disagree with this and indicate that the observed relaxation behavior is rather governed by the so-called dynamic pore radius L. To test this hypothesis, we have developed a set of new scaling relationships, which allow the relaxation time to be computed from the pore size and the permeability to be computed from both the Cole-Cole time constant and the formation factor. Moreover, these new scaling relationships can be also used to predict the dependence of the Cole-Cole time constant as a function of the water saturation under unsaturated conditions. Comparative tests of the proposed new relationships with regard to various published experimental results for saturated clean sands and sandstones as well as for partially saturated clean sandstones, do indeed confirm that the dynamic pore radius L is a much more reliable indicator of the observed relaxation behavior than grain-size-based models.

Detection of Raga-characteristic phrases from Hindustani Classical Music Audio

Melodic motifs form essential building blocks in Indian Classical music. The motifs, or key phrases, providestrong cues to the identity of the underlying raga in both Hindustani and Carnatic styles of Indian music. Automatic identification and clustering of similar motifs is relevant in this context. The inherent variations in various instances of a characteristic phrase in a bandish (composition)performance make it challenging to identify similar phrases in a performance. A nyas svara (long note)marks the ending of these phrases. The proposed method does segmentation of phrases through identification ofnyas and computes similarity with the reference characteristic phrase.

Candidate SNPs for carcass and meat traits in Nelore animals and in their crosses with Bos taurus

The objective of this work was to evaluate the effects of single-nucleotide polymorphisms (SNPs) in the genes IGF1 (AF_017143.1:g.198C>T), MSTN (AF_320998.1:g.433C>A), MYOD1 (NC_007313:g.1274A>G) and MYF5 (NC_007303:g.1911A>G) on carcass and meat traits in Nelore (Bos indicus) and Nelore x B. taurus. A total of 300 animals were genotyped and phenotyped for rib eye area (REA), backfat thickness (BT), intramuscular fat (IF), shear force (SF) and myofibrillar fragmentation index (MFI). The effects of allele substitution for each SNP were estimated by regression of the evaluated phenotypes on the number of copies of a particular allele using the general linear model. The polymorphism at IGF1 was non-informative in Nelore animals. In crossbred animals, the IGF1 C allele was associated with greater REA. However, this relation was not significant after Bonferroni correction for multiple testing. The A allele of the MSTN polymorphism was absent in Nelore cattle and was only found in two crossbred animals. The polymorphisms of MYOD1 and MYF5 were little informative in Nelore animals with G allele frequency of 0.097 and A allele frequency of 0.031, respectively. These markers show no association with the analyzed traits in the total sample of evaluated animals.

A characteristic EEG pattern in 4p-syndrome: case report and review of the literature.

Deletions on the short arm of chromosome 4 cause Wolf-Hirschhorn syndrome (WHS) and Pitt-Rogers-Danks syndrome (PRDS). WHS is associated with severe growth and mental retardation, microcephaly, a characteristic facies and congenital malformations. The PRDS phenotype is similar to WHS but generally less severe. Seizures occur in the majority of WHS and PRDS patients. Sgrò et al. [17] described a stereotypic electroclinical pattern in four unrelated WHS patients, consisting of intermittent bursts of 2-3 Hz high voltage slow waves with spike wave activity in the parietal areas during drowsiness and sleep associated with myoclonic jerks. We report a patient with PRDS and the typical EEG pattern and review 14 WHS patients with similar EEG findings reported in the literature. CONCLUSION: Awareness and recognition of the characteristic electroclinical findings in Wolf-Hirschhorn syndrome and Pitt-Rogers-Danks syndrome might help in the early diagnosis of such patients.

Polymorphisms in candidate genes and their association with carcass traits and meat quality in Nellore cattle

The objective of this work was to estimate the allele polymorphism frequencies of genes in Nellore cattle and associate them with meat quality and carcass traits. Six hundred males were genotyped for the following polymorphisms: DGAT1 (VNTR with 18 nucleotides at the promoter region); ANK1, a new polymorphism, identified and mapped here at the gene regulatory region NW_001494427.3; TCAP (AY428575.1:g.346G>A); and MYOG (NW_001501985:g.511G>C). In the association study, phenotype data of hot carcass weight, ribeye area, backfat thickness, percentage of intramuscular fat, shear force, myofibrillar fragmentation index, meat color (L*, a*, b*), and cooking losses were used. Allele B from the ANK1 gene was associated with greater redness (a*). Alleles 5R, 6R, and 7R from the DGAT1 VNTR gene were associated with increased intramuscular fat, reduced cooking losses and increased ribeye area, respectively. The single nucleotide polymorphism (SNP) of the TCAP gene was not polymorphic, and MYOG alleles were not associated with any of the evaluated characteristics. These results indicate that ANK1 and DGAT1 genes can be used in the selection of Nellore cattle for carcass and meat quality.

Frequencies of candidate genes and associations with carcass and meat traits in Nellore and crossbred cattle

Abstract: The objective of this work was to estimate allelic frequencies of the polymorphisms IGF2/MboII (G > T) of the insulin-like growth factor 2 (IGF2) gene, DQ499531.1:g.134A > T of the pro-melanin-concentrating hormone (PMCH) gene, and DQ667048.1:g.3290G > T of the RARrelated orphan receptor C (RORC) gene in beef cattle of different genetic groups, and to evaluate the associations between these polymorphisms and traits related to carcass composition and meat quality. Data on carcass and meat quality of 499 animals was used: of 313 Nellore (Bos indicus) and of 186 Nellore crossed with different taurine (Bos taurus) breeds. For the IGF2/MboII polymorphism, the frequencies found for the G allele were 0.231 and 0.631 for Nellore and crossed breeds, respectively. For the DQ499531.1:g.134A > T polymorphism, the allelic frequencies of A were 0.850 for Nellore and 0.905 for crossed breeds. For the DQ667048.1:g.3290G > T polymorphism, the allelic frequencies of G were 0.797 and 0.460 for Nellore and crossed breeds, respectively. The evaluated single nucleotide polymorphisms (SNPs) are not significantly associated with carcass and meat traits (rib eye area, back fat thickness, shear force, total lipids, and myofibrillar fragmentation index), suggesting little utility of the analyzed polymorphisms of the IGF2, PMHC, and RORC genes as selection markers in the studied cattle populations.

Comparison of carcass composition by parts and tissues between cocks and capons

The effect of caponisation on carcass composition by parts and tissues was examined. Twenty-eight castrated and twenty male Penedesenca Negra chicks reared under free-range conditions were slaughtered at 28 weeks of age. The birds were castrated at 4 or 8 weeks. The left sides of the carcasses were quartered (wing, breast, thigh and drumstick), and the parts dissected into the tissue components (skin, subcutaneous fat, intermuscular fat, muscle, bone and tendons). Capons showed more abdominal, intermuscular and subcutaneous fat than the cocks, both at the same slaughter age and at the same weight. The breast and thigh were heavier in the capons than in the cocks. However, the whole muscle mass in the breast was increased by caponisation. This favourable effect was achieved at the expense of decreasing the carcass yield. The age of castration up to 8 weeks did not affect the carcass composition of the parts and tissues.

Receiver operating characteristic (ROC) curve for classification of18F-NaF uptake on PET/CT

Abstract Objective: To assess the cutoff values established by ROC curves to classify18F-NaF uptake as normal or malignant. Materials and Methods: PET/CT images were acquired 1 hour after administration of 185 MBq of18F-NaF. Volumes of interest (VOIs) were drawn on three regions of the skeleton as follows: proximal right humerus diaphysis (HD), proximal right femoral diaphysis (FD) and first vertebral body (VB1), in a total of 254 patients, totalling 762 VOIs. The uptake in the VOIs was classified as normal or malignant on the basis of the radiopharmaceutical distribution pattern and of the CT images. A total of 675 volumes were classified as normal and 52 were classified as malignant. Thirty-five VOIs classified as indeterminate or nonmalignant lesions were excluded from analysis. The standardized uptake value (SUV) measured on the VOIs were plotted on an ROC curve for each one of the three regions. The area under the ROC (AUC) as well as the best cutoff SUVs to classify the VOIs were calculated. The best cutoff values were established as the ones with higher result of the sum of sensitivity and specificity. Results: The AUCs were 0.933, 0.889 and 0.975 for UD, FD and VB1, respectively. The best SUV cutoffs were 9.0 (sensitivity: 73%; specificity: 99%), 8.4 (sensitivity: 79%; specificity: 94%) and 21.0 (sensitivity: 93%; specificity: 95%) for UD, FD and VB1, respectively. Conclusion: The best cutoff value varies according to bone region of analysis and it is not possible to establish one value for the whole body.

Effect of supplementation with MgCO3 and L-tryptophan on the welfare and on the carcass and meat quality of two halothane pig genotypes (NN and nn)

Sixty-one animals with different Halothane genes (homozygous halothane positive, n=34; and homozygous halothane negative, n=27) were fed with three diets (controlgroup, with no supplement; magnesium (Mg) group with 1.28g MgCO3/kg and tryptophan (Trp) group with 5g L-Trp/kg) during the last 5 days before slaughter. Animals were submitted to minimal stress ante mortem conditions. Pig behaviour was recorded at the experimental farm, raceway to the CO2 stunning system and during the stunning period. Corneal reflexes were recorded after stunning as well. There were no differences in feed intake among diets (p>0.05) during the 5 days of treatment. Thehalothane positive (nn) group had lower intake than the halothane negative (NN) group(p<0.01). The behaviour of the pigs in the raceway did not differ (p>0.05) among treatments or halothane genotype. A significant (p<0.001) interaction diet*halothane was found in the time to appear the first retreat attempt during the exposure to the CO2 system. In the nn group, the time of performing the first retreat attempt was later in the Mg (p<0.05) than the Control group. Moreover, in the Mg group, the nn had a later (p<0.05) first retreat attempt than the NN. Thus, Mg supplementation could have a positive effect on welfare of nn pigs. The nn had a lower proportion of animals thatshowed corneal reflexes after stunning than NN, indicating a higher effectiveness of thestunning method in nn pigs. Neither Mg nor Trp affected carcass quality and meat quality parameters, although significant differences were found between genotypes

The performance and the characteristic field of a centrifugal compressor

Tässä työssä tarkastellaan radiaalikompressorin puristusprosessiin liittyvä peruslaskenta. Ilmankosteuden vaikutukset laskentaan huomioidaan ja kompressorin tunnuskenttä esitellään tässä työssä. Esimerkkinä lasketaan pisteitä kompressorin tunnuskentästä.

Poultry carcass decomposition and physicochemical analysis of compounds in different Composter types

This study aimed to assess five composter types in poultry carcasses decomposition and to perform a physicochemical analysis of the compounds obtained. Composter types used were six-hole brick, wood, screen, windrow with three PVC pipes with six holes and windrow with three PVC pipes with 10 holes. Composting was followed by four periods using wood shaving like substrate with one bird carcass placed in each composter. Pile turning was performed every 10 days and temperature in each layer was measured on 1st, 7th, 14th, 19th and 29th day, at 3 p.m., as well as room temperature. Temperature during pile turning was also measured at five points per layer and carcass weighing performed to calculate decomposition percentage. Physicochemical parameters evaluated in substrates were moisture, ash, phosphorus, potassium, nitrogen, pH, organic carbon and C/N ratio, up to 30 days. Data were analyzed by repeated measures model, using MIXED method of SAS software. All values of final physicochemical composition of substrates were found according to values of IN-25, except nitrogen. The composter types were efficient in decomposition of poultry carcasses.

Performance characteristic of moving average trading rules in the Finnish stock market

The thesis examines the profitability of DMAC trading rules in the Finnish stock market over the 1996-2012 period. It contributes to the existing technical analysis literature by comparing for the first time the performance of DMAC strategies based on individual stock trading portfolios to the performance of index trading strategies based on the trading on the index (OMX Helsinki 25) that consists of the same stocks. Besides, the market frictions including transaction costs and taxes are taken into account, and the results are reported from both institutional and individual investor’s perspective. Performance characteristic of DMAC rules are evaluated by simulating 19,900 different trading strategies in total for two non- overlapping 8-year sub-periods, and decomposing the full-sample-period performance of DMAC trading strategies into distinct bullish- and bearish-period performances. The results show that the best DMAC rules have predictive power on future price trends, and these rules are able to outperform buy-and-hold strategy. Although the performance of the DMAC strategies is highly dependent on the combination of moving average lengths, the best DMAC rules of the first sub-period have also performed well during the latter sub-period in the case of individual stock trading strategies. According to the results, the outperformance of DMAC trading rules over buy-and-hold strategy is mostly attributed to their superiority during the bearish periods, and particularly, during stock market crashes.