Neste trabalho, visamos mostrar as características usuais dos dados de alta frequência, bem como utilizar modelagem não paramétrica para estimar a variância/volatilidade para esses dados. Após uma revisão sobre microestrutura de mercado, sazonalidade intradiária, variação quadrática e saltos, utilizamos os dados da PETR4 para estimar a variância realizada e variação bipotente. Determinadas essas séries, testamos se há saltos nas mesmas. Em seguida, analisamos o impacto que a microestrutura de mercado e a sazonalidade intradiária causam na detecção dos saltos. Concluímos que, enquanto a presença de microestrutura aponta para um número de saltos menor que o esperado, a sazonalidade intradiária aponta para o lado contrário, ou seja, ela causa um viés para detectar mais saltos, dada a estrutura típica da curva de volatilidade ao longo do dia em formato de J invertido, causando mais saltos incorretamente detectados no período mais volátil do dia (que corresponde a abertura da bolsa de valores). / In this work, we aim to show the usual characteristics of high-frequency data and the estimation of variance/volatility for this kind of data using nonparametric models. After reviewing concepts about market microstructure, intraday seasonality, quadratic variation and jumps, we use PETR4 data to estimate realized variance and bipower variation. With these series determined, we test for jumps. Then, we analyze the impact that market microstructure and intraday seasonality causes in jump detection. We conclude that while microstructure noise indicates fewer jumps than the ideal amount, intraday seasonality goes in the opposite direction, i.e., it detects more jumps than it should, since the typical inverted-J-shaped intraday volatility pattern tends to incorrectly detect more jumps at the most volatile period (which is when stock markets start negotiations).

O desenvolvimento de tecnologias de integração para circuitos integrados junto com a demanda de cada vez mais processamento digital de sinais, como em sistemas de telecomunicações e aplicações SOC, resultaram na crescente necessidade de circuitos mistos em tecnologia CMOS integrados em um único chip. Em um trabalho anterior, a arquitetura de uma interface analógica para ser usada em aplicações SOC mistas foi desenvolvida e implementada. Basicamente esta interface é composta por uma célula analógica fixa (fixed analog cell – FAC), que translada o sinal de entrada para uma freqüência de processamento fixa, e por um bloco digital que processa este sinal. Primeiramente, as especificações de sistema foram determinadas considerando o processamento de sinais de três bandas de freqüência diferentes: FM, vídeo e celular, seguido por simulações de alto-nível do sistema da FAC. Então, uma arquitetura heteródina integrada CMOS para o front-end que integrará a FAC, composto por 2 mixers ativos e um amplificador de ganho variável, foi apresentada, enumerando-se e propondo-se soluções para os desafios de projeto e metodologia. Os blocos analógicos/RF, juntamente com o front-end, foram projetados e implementados em tecnologia CMOS IBM 0.18μm, apresentando-se simulações e medidas de um protótipo físico. / The development of IC technologies coupled with the demand for more digital signal processing integrated in a single chip has created an increasing need for design of mixed-signal systems in CMOS technology. Previously, a general analog interface architecture targeted to mixed-signal systems on-chip applications was developed and implemented, which is composed by a fixed analog cell (FAC), that translates the input signal to a processing frequency, and a digital block, that processes the signal. The focus of this thesis is to analyze, design and implement analog/RF building blocks suitable for this system. First, a set of system specifications is developed and verified through system level simulations for the FAC system, aiming the signal processing of three target applications: FM, video and digital cellular frequency bands. Then, a fully CMOS integrated dual-conversion heterodyne front-end architecture with 2 active mixers and a variable-gain amplifier is presented, enumerating and proposing solutions for the design challenges and methodology. The stand-alone building blocks and the front-end system are designed and implemented in IBM 0.18μm CMOS process, presenting simulations and experimental data from an actual physical prototype.

A eletroencefalografia (EEG) é uma das evidências tomadas na avaliação de indicação cirúrgica, em casos de pacientes portadores de epilepsia refratária a medicamentos, que pode auxiliar na localização da área responsável pela origem das crises epilépticas. Ao longo das últimas décadas, além das bandas de frequências já tradicionalmente avaliadas (até cerca de 40Hz), a EEG tem despertado o interesse de pesquisadores também para bandas de frequências mais altas. Passaram a ser encontradas evidências de que oscilações de alta frequência, conhecidas por HFO (High Frequency Oscillations), podem ser usadas como biomarcadores de epilepsia. Diversos estudos têm sido realizados em busca de uma melhor compreensão sobre HFO, a fim de viabilizar sua utilização em aplicações clínicas. Entretanto, características não lineares e de complexidade, que podem contribuir na análise de sinais com origem em sistemas biológicos, não têm sido investigadas neste tipo de sinais. Este estudo propôs a investigação de características extraídas de sinais de EEG com presença de HFO, de pacientes portadores de epilepsia refratária, através de métodos considerados como de análise não linear. Análise de Dinâmica Simbólica, Análise de Flutuações Destendenciadas (DFA), Entropia Multiescala (MSE) e Análise qSDiff foram aplicadas em segmentos de sinais de EEG intracraniano, amostrados a 5kHz, de pacientes portadores de epilepsia refratária, e também em alguns sinais simulados de características conhecidas para fins de comparação. Os resultados dos diferentes métodos investigados apontaram características semelhantes entre os segmentos de EEG analisados e séries simuladas de ruído browniano, sugerindo que os sinais de EEG em geral têm perfil bastante suavizado, são não estacionários e exibem correlações de longo alcance. Foram também levantadas evidências de que tanto HFO quanto os segmentos de EEG onde estão inseridas têm padrões mais regulares de variação e são menos complexas que segmentos de EEG sem HFO, sugerindo a degradação da complexidade fisiológica desta região cerebral, que poderia estar relacionada com mecanismos fisiopatológicos da epilepsia. Todos os métodos investigados sugeriram que as características e propriedades não lineares, relacionadas a complexidade inerente dos sinais de EEG, podem ser úteis na análise de HFO, principalmente pelas evidências de que estas características se alteram nas HFO, quando comparadas ao restante do sinal onde elas se encontram e também a outros sinais sem sua presença. / Electroencephalography (EEG) is one of the evidences taken in the evaluation of surgical indication, in cases of patients with drug refractory epilepsy, which may help in locating the area responsible for the origin of epileptic seizures. Over the last few decades, in addition to the frequency bands that have traditionally been evaluated (up to about 40Hz), the EEG has attracted researchers also to higher frequency bands. Evidence has been found that high frequency oscillations (HFO), can be used as biomarkers of epilepsy. Many studies have been carried out in search of a better understanding about HFO, in order to make it feasible to use in clinical applications. However, nonlinear and complex features, which may contribute to the analysis of signals originating from biological systems, have not been investigated in this type of signals. This study proposed the investigation of features extracted from EEG signals with HFO of patients with refractory epilepsy, using nonlinear analysis methods. Symbolic Dynamics Analysis, Detrended Fluctuation Analysis (DFA), Multiscale Entropy (MSE) and qSDiff Analysis were applied to segments of intracranial EEG signals, sampled at 5kHz, from patients with refractory epilepsy, as well as some features-known simulated signals for comparison purposes. Results of the different investigated methods pointed out similar features between the analyzed EEG segments and the simulated series of Brownian noise, suggesting that EEG signals, in general, have a very smoothed profile, are nonstationary and exhibit long- range correlations. Evidence has also been raised that both HFO and the EEG segments where they are inserted have more regular patterns of variation and are less complex than EEG segments without HFO, suggesting the degradation of the physiological complexity of this brain region, which could be related to pathophysiological mechanisms of epilepsy. All the investigated methods suggested that nonlinear features and properties, related to the inherent complexity of EEG signals, may be useful in HFO analysis, mainly because of the evidence that these features change in HFOs when compared to the rest of the signal where they are and other signals without their presence.

This thesis explores the relation between fiancial stability and macroeconomic policy. The first chapter tackles the topic of financial stability from the point of wiev of a the single bank. In that model banks take explicitly into account the probability of default of their counterparties on the interbank market. In this way, an endogenous constraint to the credit supply is defined. That constraint evolves along the business cycle. I show that monetary policy alone is not able to ease credit conditions during a crisis. The second chapter nests a complex network model inside a state-of-the-art DSGE model. Using the tools of network analysis it is possible to trace how contagion spreads between banks (i.e. what is the likelihood that the default of one bank spreds to other banks, how many institution are affected) and how its probability avolves following exogenous shocks. With this tool I test partial equilibrium macropolicy tools (i.e. direct lendings to banks) and the effectiveness of monetary policy during crisis. Finally, in the last chapter I analyze, with high frequency data, the impact of conventional and unconventional monetary policy surprises, finding that the response of markets to menetary policy increased over time. / Questa tesi studia la relazione tra stabilità finanziaria e politica economica. Il primo capitolo della tesi affronta l'argomento della stabilità finanziaria dal punto di vista della singola banca. In quel modello ciascuna banca tiene esplicitamente in considerazine la probabilità di insulvenza delle sue controparti sul mercato interbancario. In questo modo si genera un vincolo endogeno all'offerta di credito. Tale vincolo evolve con il ciclo economico. Il modello mostra come la politica monetaria da sola non sia sufficiente a migliorare le condizioni del credito sui mercati finanziari dureante le crisi. Il secondo capitolo inserisce un modello di network all'interno di un mdoello DSGE standard. Analizzando il modello di network è possibile seguire come il contagio si diffonda tra le banche (qual è la probabilità che l'insolvenza di una banca si diffonda ad altre, qaule il numero di istituzioni coinvolte) e come tale probabilità evolva a seguito di shock esogeni. Con questi strumenti è possibile valutare politiche microeconomiche (per esempio prestiti diretti alle banche) e l'efficacia della politica moentaria durante le crisi. Infine, nell'ultimo capitolo, utilizzando dati ad alta frequenza, stimo l'impatto di shock di politica monetaria (convenzionali e non) trovando che la sensibilità dei mercati è aumentanta nel tempo.

Les travaux effectués pendant la thèse ont principalement porté sur la modélisation et le calcul du comportement haute-fréquence (HF) des câbles électriques. Ces phénomènes physiques mis en jeu combinent les effets capacitifs et inductifs ainsi que les effets de peau et de proximité. Pour prendre en compte de ces comportements, nous utilisons une approche basée sur des circuits équivalents à base aux paramètres linéiques qui varient en fonction de la fréquence. La détermination des éléments du schéma équivalent a été effectuée en résolvant des problèmes d'électrostatique et de magnétoharmonique en utilisant la méthode des éléments finis. Ensuite, nous avons travaillé sur la méthode des lignes de transport (TLM) associée à une approche modale pour déterminer les fréquences de résonance du système en prenant en compte les interconnexions aux extrémités du câble. Nous avons mis en œuvre la méthode ci-dessus pour plusieurs types de câble électrique : bifilaire blindé, blindé de 4 conducteurs, AC triphasée et enfin HVDC. Le comportement HF de ces câbles a été étudié en utilisant l'approche développé. / The work during the thesis focused on the modeling and calculation of high frequency (HF) behavior in the power cables. These physical phenomena involved combining capacitive and inductive as well as the effects of skin and proximity effects. To account for this behavior, we use an approach based on equivalent circuits based on linear parameters that vary depending on the frequency approach. The determination of the equivalent circuit elements was performed by solving electrostatic problems and magnetoharmonic using the finite element method. Then we worked on the Transmission Lines Method (TLM) associated with a modal approach to determine the resonance frequencies of the system taking into account the interconnections to the ends of cable. We have implemented the above method for several types of electric cable: shielded wire, shielded 4 wires, three phases AC and finally the HVDC cable. The HF behavior of these cables has been studied using the developed approach.

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

The thesis analyses high frequency trading, specifically its main characteristics, which make it different from algorithmic trading. Furthermore, the thesis looks closer into major risks, which are new to market, and their impact on market quality and other investors. The next chapter is dedicated to trading strategies, which are typical for high frequency trading. In conclusion, there is discussed the impact on the market quality caused by high frequency trading, namely in terms of liquidity, volatility and price discovery.

The main objective of this thesis is to investigate whether multivariate models using Highfrequency data provide significantly more accurate forecasts of Value at Risk and Expected Shortfall than multivariate models using only daily data. Our objective is very topical since the Basel Committee announced in 2013 that is going to change the risk measure used for calculation of capital requirement from Value at Risk to Expected Shortfall. The further improvement of accuracy of both risk measures can be also achieved by incorporation of high-frequency data that are rapidly more available due to significant technological progress. Therefore, we employed parsimonious Heterogeneous Autoregression and its asymmetric version that uses high-frequency data for the modeling of realized covariance matrix. The benchmark models are chosen well established DCC-GARCH and EWMA. The computation of Value at Risk (VaR) and Expected Shortfall (ES) is done through parametric, semi-parametric and Monte Carlo simulations. The loss distributions are represented by multivariate Gaussian, Student t, multivariate distributions simulated by Copula functions and multivariate filtered historical simulations. There are used univariate loss distributions: Generalized Pareto Distribution from EVT, empirical and standard parametric distributions. The main finding is that Heterogeneous Autoregression model using high-frequency data delivered superior or at least the same accuracy of forecasts of VaR to benchmark models based on daily data. Finally, the backtesting of ES remains still very challenging and applied Test I. and II. did not provide credible validation of the forecasts.

Cochlear dead regions (DRs) are areas in the cochlea where inner hair cells and/or neurones are functioning so poorly that a sound that causes peak basilar membrane motion in that region is more efficiently detected via off-frequency listening. The Threshold Equalising Noise (TEN) test is a clinical test procedure for detecting DRs. Psychophysical Tuning Curves (PTCs) can be used to identify the boundary frequency of the DR although the clinical importance of doing this has yet to be determined. Some studies have suggested that the reduction of amplification well inside the DR may be beneficial; however, other studies have been unable to replicate these findings in a more typical clinical population. Three studies were completed in order to:1. determine the prevalence of DRs in a clinical sample of the UK adult population,2. investigate repeatability, agreement and clinical feasibility of the TEN-test and fast PTCs in a clinical setting, and 3. determine the benefit of high-frequency amplification in ears with and without DRs, when listening to nonsense syllable speech material in quiet and babble. In the first study, 343 hearing-impaired adults were tested for DRs using the TEN-test. In total, 36% (95% confidence interval 31-41) of these adults had a DR in at least one ear, but frequently at 4 kHz only. Only 3% (1-5) of participants had a DR spanning more than three consecutive frequencies. These findings suggest that DRs usually only span 1 or 2 clinically-relevant frequencies. In the second study, the TEN-test was completed on 70 ears at frequencies between 0.5 and 4 kHz. Fast PTCs were measured on 20 ears at ≥ 2 frequencies. The TEN-test and fast PTCs were highly repeatable on retest (97% and 100%, respectively). There was 87% agreement between the two procedures in terms of the presence of off-frequency listening, with the TEN-test less likely to detect a DR than fast PTCs. Compared to the TEN-test, fast PTCs had a 10% lower ‘conclusive finding’ rate and the test duration was typically 40 minutes longer. Therefore, the TEN-test is more clinically acceptable, but it may underestimate the extent of a DR because of its inability to precisely identify the boundary frequency. In the third study, 18 ears with a high-frequency DR and 18 matched ears without a DR were tested. Vowel-Consonant-Vowel (VCV) stimuli were presented in quiet and babble when listening with an unfiltered and three low-pass filtered hearing aid settings. Best performance was obtained in the unfiltered condition; however the DR group performed significantly poorer than the controls in babble. There was no evidence to support reducing amplification in ears with a DR. However, participants with DRs may benefit from counseling about the limitations of listening in noise. In summary, DRs are relatively prevalent in hearing-impaired adults and can be diagnosed most efficiently in a clinical setting using the TEN-test. However, DRs are often restricted to a narrow frequency range and, in the typical adult clinical population, there is no evidence to support deviating from prescription targets.

Metal halide lamp is one kind of the most compact high-performance light sources. Because of their good color rendering index and high luminous efficacy, these lamps are often preferred in locations where color and efficacy are important, such as supermarkets, gymnasiums, ice rinks and sporting arenas. Unfortunately, acoustic resonance phenomenon occurs in metal halide lamps and causes light flicker, lamp arc bending and rotation, lamp extinction and in the worst case, arc tube explosion, when the lamps are operated in high-frequency bands. This thesis takes place in the context of developing electronic ballasts with robust acoustic resonance detection and avoidance mechanisms. To this end, several envelope detection methods such as the multiplier circuit, rectifier circuit, and lock-in amplifier, are proposed to characterize fluctuations of acoustic resonance. Furthermore, statistical criteria based on the standard deviation of these fluctuations are proposed to assess acoustic resonance occurrence and classify its severity. The proposed criteria enable classifying between no acoustic resonance and acoustic resonance cases based upon either a two-dimensional plane, a histogram or a boxplot. These analyses are confirmed by the study of spectral variations (variations of the spectral irradiance and colorimetric parameters) as well. Standard deviations and relative standard deviations of these variations are also correlated with the presence of acoustic resonance. The results from this study show that whatever voltage envelope variations or spectral variations are significantly influenced by acoustic resonance phenomena. A set of metal halide lamps from different manufacturers and with different powers are tested in our experiments. We concluded that our designed multiplier and rectifier circuits for acoustic resonance detection have the same sensitivity as the lock-in amplifier, paving the way for the implementation of this function directly into the ballast circuit board.