Estudo empírico do comportamento dos depósitos das instituições financeiras brasileiras durante a crise de 2008

A motivação do trabalho surgiu dos efeitos causados pela crise imobiliária nos Estados Unidos em 2008, sendo a quebra do banco de investimento “Lehman Brothers” o estopim para uma série de eventos. No Brasil, os efeitos foram diversos, o presente trabalho se aprofundou nos efeitos sobre as captações, analisando se houve uma corrida bancária dos pequenos e médios bancos para os grandes. Este estudo foi feito por meio da análise de quebra estrutural baseada nos testes OLS Cusum introduzido por Ploberger e Kramer (1992) e Teste F por Chow (1960), bem como por meio da análise de dados em painel, utilizando as metodologias de análise de cluster e o modelo de efeitos fixos. De um modo geral, os nossos resultados demonstram que efetivamente ocorreu uma transferência massiva de recursos dos pequenos e médios bancos para os grandes.

Gráficos de controle X para processos robustos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

(X)over-bar charts with variable parameters

Varying the parameters of the (X) over bar chart has been explored extensively in recent years. In this paper, we extend the study of the (X) over bar chart with variable parameters to include variable action limits. The action limits establish whether the control should be relaxed or not. When the (X) over bar falls near the target, the control is relaxed so that there will be more time before the next sample and/or the next sample will be smaller than usual. When the (X) over bar falls far from the target but not in the action region, the control is tightened so that there is less time before the next sample and/or the next sample will be larger than usual. The goal is to draw the action limits wider than usual when the control is relaxed and narrower than usual when the control is tightened. This new feature then makes the (X) over bar chart more powerful than the CUSUM scheme in detecting shifts in the process mean.

Monitoring the process mean and variance using a synthetic control chart with two-stage testing

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

X̄ Charts with Variable Parameters

Varying the parameters of the X̄ chart has been explored extensively in recent years. In this paper, we extend the study of the X̄ chart with variable parameters to include variable action limits. The action limits establish whether the control should be relaxed or not. When the X̄ falls near the target, the control is relaxed so that there will be more time before the next sample and/or the next sample will be smaller than usual. When the X̄ falls far from the target but not in the action region, the control is tightened so that there is less time before the next sample and/or the next sample will be larger than usual. The goal is to draw the action limits wider than usual when the control is relaxed and narrower than usual when the control is tightened. This new feature then makes the X̄ chart more powerful than the CUSUM scheme in detecting shifts in the process mean.

Analisi della stabilità dei risultati dei test di risposta termica: prove in campo, confronto e analisi critica per diversi metodi di esecuzione e modellizzazione

Il Test di Risposta Termica (Thermal Response Test-TRT) (Mogenson,1983) è il test esistente con il più alto grado di accuratezza per la caratterizzazione del reservoir geotermico superficiale. Il test consiste in una simulazione in situ del funzionamento di un sistema a circuito chiuso di sfruttamento dell’energia geotermica, per un periodo limitato di tempo, attraverso l’iniezione o estrazione di calore a potenza costante all’interno del geo-scambiatore (Borehole Heat Exchanger-BHE). Dall’analisi della variazione delle temperature del fluido circolante, è possibile avere una stima delle proprietà termiche medie del volume del reservoir geotermico interessato dal test. Le grandezze principali per la caratterizzazione di un serbatoio geotermico sono la conduttività termica (λ), la capacità termica volumetrica (c), la temperatura indisturbata del suolo (Tg) e la resistenza termica del pozzo (Rb); la loro determinazione è necessaria per il corretto progettazione degli geo-scambiatori. I risultati del TRT sono tuttavia sensibili alle condizioni al contorno spazio-temporali quali ad es.: variazione della temperatura del terreno, movimento d’acqua di falda, condizioni metereologiche, eventi stagionali, ecc. Questo lavoro vuole: i) introdurre uno studio sui problemi di caratterizzazione del reservoir geotermico superficiale, in particolare analizzando l’effetto che il movimento d’acqua di falda ha sui parametri termici; ii) analizzare la sensitività dei risultati del test alle variabilità dei parametri caratteristici del funzionamento delle attrezzature. Parte del lavoro della mia tesi è stata svolta in azienda per un periodo di 4 mesi presso la “Groenholland Geo Energy systems” che ha sede ad Amsterdam in Olanda. Tre diversi esperimenti sono stati realizzati sullo stesso sito (stratigrafia nota del terreno: argilla, sabbia fine e sabbia grossa) usando una sonda profonda 30 metri e diversi pozzi per l’estrazione d’acqua e per monitorare gli effetti in prossimità del geo scambiatore. I risultati degli esperimenti sono stati molto diversi tra di loro, non solo in termini di dati registrati (temperature del fluido termovettore), ma in termini dei valori dei parametri ottenuti elaborando i dati. In particolare non è sufficiente adottare il modello classico della sorgente lineare infinita (Infinite Line Source Solution- ILS) (Ingersoll and Plass, 1948), il quale descrive il trasferimento di calore per conduzione in un mezzo omogeneo indefinito a temperatura costante. Infatti, lo scambio di calore avviene anche tramite convezione causata dal movimento d’acqua di falda, non identificabile mediante gli approcci classici tipo CUSUM test (Cumulative Sum test) (Brown e altri,1975) Lo studio della tesi vuole dare un quadro di riferimento per correlare la variabilità dei risultati con la variabilità delle condizioni al contorno. L’analisi integra le metodologie classiche (ILS) con un approccio geostatistico utile a comprendere i fenomeni e fluttuazioni che caratterizzano il test. Lo studio delle principali variabili e parametri del test, quali temperatura in ingresso e uscita del fluido termovettore, portata del fluido e potenza iniettata o estratta, è stato sviluppato mediante: il variogramma temporale, ovvero la semivarianza dell’accrescimento, che esprime il tipo di autocorrelazione temporale della variabile in esame; la covarianza incrociata temporale, ovvero la covarianza fra due variabili del sistema, che ne definisce quantitativamente il grado di correlazione in funzionamento del loro sfasamento temporale. L’approccio geostatistico proposto considera la temperatura del fluido Tf come una funzione aleatoria (FA) non stazionaria nel tempo (Chiles, 1999), il cui trend è formalmente definito, ma deve essere identificato numericamente. Si considera quindi un classico modello a residuo; in cui la FA è modellizzata come la somma di un termine deterministico, la media (il valore atteso) m(t),coincidente col modello descritto dalla teoria della sorgente lineare infinità, e di un termine aleatorio, la fluttuazione, Y(t). Le variabili portata e potenza sono invece considerate delle funzioni aleatorie stazionarie nel tempo, ovvero a media costante. Da questo studio di Tesi si sono raggiunte delle conclusioni molto importanti per lo studio del TRT: Confronto tra gli esperimenti in estrazione di calore, con e senza movimento d’acqua di falda: si studia l’effetto indotto dalla falda sul TRT. E’ possibile caratterizzare quantitativamente l’incremento della conducibilità termica equivalente legata a fenomeni convettivi dovuti al movimento d’acqua di falda. Inoltre, i variogrammi sperimentali evidenziano periodicità simili nei due casi e legate al funzionamento della pompa di calore e della componentistica associata ed alla circolazione del fluido termovettore all’interno della sonda. Tuttavia, la componente advettiva ha un effetto di smorzamento sulle piccole periodicità dei variogrammi, ma di aumento dell’ampiezza delle periodicità maggiori a causa del funzionamento della pompa di calore che deve fornire maggiore energia al sistema per bilanciare le dispersioni dovute al movimento d’acqua di falda. Confronto fra estrazione ed iniezione di calore, con movimento d’acqua di falda: si studia la significatività dei risultati nei due casi. L’analisi delle variografie evidenzia significative differenze nella struttura dei variogrammi sperimentali. In particolare, nel test con iniezione di calore i variogrammi sperimentali delle temperature hanno valori sistematicamente inferiori, circostanza che assicura una migliore precisione nella stima dei parametri termici. Quindi eseguire il TRT in iniezione di calore risulta più preciso. Dall’analisi dei variogrammi sperimentali delle singole variabili quali temperatura del fluido in ingresso e uscita all’interno del geoscambiatore è stato confermato il fenomeno di smorzamento delle oscillazioni da parte del terreno. Dall’analisi delle singole variabili del test (temperature, potenza, portata) è stata confermata l’indipendenza temporale fra portate e temperature. Ciò è evidenziato dalle diverse strutture dei variogrammi diretti e dalle covarianze incrociate prossime a zero. Mediante correlogrami è stato dimostrato la possibilità di calcolare il tempo impiegato dal fluido termovettore per circolare all’interno della sonda. L’analisi geostatistica ha permesso quindi di studiare in dettaglio la sensitività dei risultati del TRT alle diverse condizioni al contorno, quelle legate al reservoir e quelle legate al funzionamento delle attrezzature

Continuous monitoring of bovine spongiform encephalopathy rapid test performance by weak positive tissue controls and quality control charts

Bovine spongiform encephalopathy (BSE) rapid tests and routine BSE-testing laboratories underlie strict regulations for approval. Due to the lack of BSE-positive control samples, however, full assay validation at the level of individual test runs and continuous monitoring of test performance on-site is difficult. Most rapid tests use synthetic prion protein peptides, but it is not known to which extend they reflect the assay performance on field samples, and whether they are sufficient to indicate on-site assay quality problems. To address this question we compared the test scores of the provided kit peptide controls to those of standardized weak BSE-positive tissue samples in individual test runs as well as continuously over time by quality control charts in two widely used BSE rapid tests. Our results reveal only a weak correlation between the weak positive tissue control and the peptide control scores. We identified kit-lot related shifts in the assay performances that were not reflected by the peptide control scores. Vice versa, not all shifts indicated by the peptide control scores indeed reflected a shift in the assay performance. In conclusion these data highlight that the use of the kit peptide controls for continuous quality control purposes may result in unjustified rejection or acceptance of test runs. However, standardized weak positive tissue controls in combination with Shewhart-CUSUM control charts appear to be reliable in continuously monitoring assay performance on-site to identify undesired deviations.

Learning curve for robotic-assisted laparoscopic colorectal surgery.

BACKGROUND: Robotic-assisted laparoscopic surgery (RALS) is evolving as an important surgical approach in the field of colorectal surgery. We aimed to evaluate the learning curve for RALS procedures involving resections of the rectum and rectosigmoid. METHODS: A series of 50 consecutive RALS procedures were performed between August 2008 and September 2009. Data were entered into a retrospective database and later abstracted for analysis. The surgical procedures included abdominoperineal resection (APR), anterior rectosigmoidectomy (AR), low anterior resection (LAR), and rectopexy (RP). Demographic data and intraoperative parameters including docking time (DT), surgeon console time (SCT), and total operative time (OT) were analyzed. The learning curve was evaluated using the cumulative sum (CUSUM) method. RESULTS: The procedures performed for 50 patients (54% male) included 25 AR (50%), 15 LAR (30%), 6 APR (12%), and 4 RP (8%). The mean age of the patients was 54.4 years, the mean BMI was 27.8 kg/m(2), and the median American Society of Anesthesiologists (ASA) classification was 2. The series had a mean DT of 14 min, a mean SCT of 115.1 min, and a mean OT of 246.1 min. The DT and SCT accounted for 6.3% and 46.8% of the OT, respectively. The SCT learning curve was analyzed. The CUSUM(SCT) learning curve was best modeled as a parabola, with equation CUSUM(SCT) in minutes equal to 0.73 × case number(2) - 31.54 × case number - 107.72 (R = 0.93). The learning curve consisted of three unique phases: phase 1 (the initial 15 cases), phase 2 (the middle 10 cases), and phase 3 (the subsequent cases). Phase 1 represented the initial learning curve, which spanned 15 cases. The phase 2 plateau represented increased competence with the robotic technology. Phase 3 was achieved after 25 cases and represented the mastery phase in which more challenging cases were managed. CONCLUSIONS: The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures. The data suggest that the learning phase was achieved after 15 to 25 cases.

A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems

n this work, a mathematical unifying framework for designing new fault detection schemes in nonlinear stochastic continuous-time dynamical systems is developed. These schemes are based on a stochastic process, called the residual, which reflects the system behavior and whose changes are to be detected. A quickest detection scheme for the residual is proposed, which is based on the computed likelihood ratios for time-varying statistical changes in the Ornstein–Uhlenbeck process. Several expressions are provided, depending on a priori knowledge of the fault, which can be employed in a proposed CUSUM-type approximated scheme. This general setting gathers different existing fault detection schemes within a unifying framework, and allows for the definition of new ones. A comparative simulation example illustrates the behavior of the proposed schemes.

PUE attack detection in CWSN using collaboration and learning behavior

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

Climatic Controls on Phytoplankton Biomass in a Sub-tropical Estuary, Florida Bay, USA

The extraction of climatic signals from time series of biogeochemical data is further complicated in estuarine regions because of the dynamic interaction of land, ocean, and atmosphere. We explored the behavior of potential global and regional climatic stressors to isolate specific shifts or trends, which could have a forcing role on the behavior of biogeochemical descriptors of water quality and phytoplankton biomass from Florida Bay, as an example of a sub-tropical estuary. We performed statistical analysis and subdivided the bay into six zones having unique biogeochemical characteristics. Significant shifts in the drivers were identified in all the chlorophyll a time series. Chlorophyll a concentrations closely follow global forcing and display a generalized declining trend on which seasonal oscillations are superimposed, and it is only interrupted by events of sudden increase triggered by storms which are followed by a relatively rapid return to pre-event conditions trailing again the long-term trend.

Exact Solution of Bayes and Minimax Change-Detection Problems

The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.

DEMANDA TRIMESTRAL POR EMISIÓN MONETARIA: ESTIMACIÓN MEDIANTE TRES TÉCNICAS ESTADÍSTICAS

Este documento presenta la estimación de la demanda trimestral por emisión monetaria mediante tres técnicas estadísticas, a saber: mínimos cuadrados ordinarios, corrección de errores y vectores autorregresivos. La estimación de la demanda se realizó para el periodo 1987–1997. En general las ecuaciones estimadas presentaron resultados satisfactorios en términos económicos y estadísticos. La capacidad de predicción se verificó con los bajos errores de pronóstico, inferiores al 3% para 1997. Se comprobó la estabilidad de la demanda de corto y largo plazo mediante los estadísticos Cusum y Cusum-Cuadrado, así como con la prueba de cointegración de Johansen.

Power Study on Testing Epidemic Alternatives

Detecting change points in epidemic models has been studied by many scholars. Yao (1993) summarized five existing test statistics in the literature. Out of those test statistics, it was observed that the likelihood ratio statistic showed its standout power. However, all of the existing test statistics are based on an assumption that population variance is known, which is an unrealistic assumption in practice. To avoid assuming known population variance, a new test statistic for detecting epidemic models is studied in this thesis. The new test statistic is a parameter-free test statistic which is more powerful compared to the existing test statistics. Different sample sizes and lengths of epidemic durations are used for the power comparison purpose. Monte Carlo simulation is used to find the critical values of the new test statistic and to perform the power comparison. Based on the Monte Carlo simulation result, it can be concluded that the sample size and the length of the duration have some effect on the power of the tests. It can also be observed that the new test statistic studied in this thesis has higher power than the existing test statistics do in all of cases.

Hilbert Space Valued Signal Plus Noise Models: Analysis of Structural Breaks under High Dimensionality and Temporal Dependence

This thesis is concerned with change point analysis for time series, i.e. with detection of structural breaks in time-ordered, random data. This long-standing research field regained popularity over the last few years and is still undergoing, as statistical analysis in general, a transformation to high-dimensional problems. We focus on the fundamental »change in the mean« problem and provide extensions of the classical non-parametric Darling-Erdős-type cumulative sum (CUSUM) testing and estimation theory within highdimensional Hilbert space settings. In the first part we contribute to (long run) principal component based testing methods for Hilbert space valued time series under a rather broad (abrupt, epidemic, gradual, multiple) change setting and under dependence. For the dependence structure we consider either traditional m-dependence assumptions or more recently developed m-approximability conditions which cover, e.g., MA, AR and ARCH models. We derive Gumbel and Brownian bridge type approximations of the distribution of the test statistic under the null hypothesis of no change and consistency conditions under the alternative. A new formulation of the test statistic using projections on subspaces allows us to simplify the standard proof techniques and to weaken common assumptions on the covariance structure. Furthermore, we propose to adjust the principal components by an implicit estimation of a (possible) change direction. This approach adds flexibility to projection based methods, weakens typical technical conditions and provides better consistency properties under the alternative. In the second part we contribute to estimation methods for common changes in the means of panels of Hilbert space valued time series. We analyze weighted CUSUM estimates within a recently proposed »high-dimensional low sample size (HDLSS)« framework, where the sample size is fixed but the number of panels increases. We derive sharp conditions on »pointwise asymptotic accuracy« or »uniform asymptotic accuracy« of those estimates in terms of the weighting function. Particularly, we prove that a covariance-based correction of Darling-Erdős-type CUSUM estimates is required to guarantee uniform asymptotic accuracy under moderate dependence conditions within panels and that these conditions are fulfilled, e.g., by any MA(1) time series. As a counterexample we show that for AR(1) time series, close to the non-stationary case, the dependence is too strong and uniform asymptotic accuracy cannot be ensured. Finally, we conduct simulations to demonstrate that our results are practically applicable and that our methodological suggestions are advantageous.