In this thesis, we analyze new possibilities in predicting daily ranges, i.e. the differences between daily high and low prices. The main focus of our work lies in investigating how models commonly used for daily ranges modeling can be enhanced to provide better forecasts. In this respect, we explore the added benefit of using more efficient volatility measures as predictors of daily ranges. Volatility measures considered in this work include realized measures of variance (realized range, realized variance) and range-based volatility measures (Parkinson, Garman & Klass, Rogers & Satchell, etc). As a subtask, we empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to simple daily ranges. As another venue of research in this work, we analyze the added benefit of slicing the trading day into different sessions based on trading activity (e.g. Asian, European and American session). In this setting we analyze whether whole-day volatility measures reliably aggregate information coming from all trading sessions. We are led by intuition that different sessions exhibit significantly different characteristics due to different order book thicknesses and trading activity in general. Thus these sessions are expected to provide valuable information concealed in...

The aim of this thesis is to provide an empirical evidence of multifractality in financial time series and to discuss the relevance of this concept for the current financial theory. We have applied two methods, the Multifractal Detrended Fluctuation analysis and the Generalized Hurst exponent method, on components of the Dow Jones Industrial Average. We analyzed daily data of 30 companies traded on U.S. stock markets from 2002 to 2012. We present results supporting presence of multiscaling in open-close returns. Contrary to published literature, we were not able to find any significant multiscaling in volatility. Moreover based on our analysis, multiscaling is not present in standardized returns and as multifractality requires relatively complicated models, this is our most valuable result. 1

ii Abstract This thesis focuses on one of the attractive topics of current financial literature, the application of wavelet-based methods in volatility modeling. It introduces a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH- family model capturing long-memory and asymmetry in volatility, and studies its properties. Based on an extensive Monte Carlo experiment, both the behavior of the new estimator in various situations and its relative performance with respect to two more traditional estimators (maximum likelihood estimator and Fourier-based Whittle estimator) are assessed, along with practical aspects of its application. Possible solutions are proposed for most of the issues detected, including suggestion of a new specification of the estimator. This uses maximal overlap discrete wavelet transform instead of the traditionally used discrete wavelet transform, which should improve the estimator performance in all its applications, not only in the case of FIEGARCH model estimation. The thesis concludes that, after optimization of the estimation setup, the wavelet-based estimator may become an attractive robust alternative to the traditional methods.

Ao se tratar de mercado de capitais, dentre seus principais fatores de análise, encontra-se a discussão a respeito da teoria de eficiência de mercado que é uma teoria que diverge em relação ao comportamento do preço dos ativos, no que diz respeito à sua linearidade ou não. Neste sentido, este trabalho teve como objetivo analisar o comportamento dos principais índices das dez maiores bolsas de valores do mercado, durante o período de junho de 1999 a junho de 2009. Para realização de tal análise foi utilizada a estatística R/S e o cálculo do Expoente de Hurst, por sua vez, validado pelo Teste Estatístico de Wald. A utilização desta metodologia permitiu investigar a presença da memória longa persistente, anti-persistente ou a identificação de um passeio aleatório. Os resultados evidenciaram que, de modo geral, os índices apresentaram presença de memória longa persistente na maior parte do período analisado, devendo-se ressaltar que apenas no período próximo à crise financeira de 2008 foi possível identificar forte presença de um comportamento aleatório. Assim, foi possível aceitar a hipótese de que os mercados são ineficientes na maioria das séries históricas de retornos dos índices. / When it comes to the capital market, among its main factors of analysis, it´s found the debate concerning the market efficiency theory, which is a theory that differs in relation to the behavior of the asset´s price, concerning its linearity or not. In this way, this work aims to analyse the behavior of the main index of the ten major stock market, from june 1999 until june 2009. To the achievement of such analysis it was used the R/S statistics and the Hurst Exponent, which was, validadet by the Wald Test Statistics. The employment of such methodology allowed to investigate the presence of the long persistence memory, anti-persistence or the identification of a random walk. The results showed that, on the whole, the indexes showed the presence of the long persistence memory most of the analysed period, saying the only in the period close to the financial crisis of 2008, it was possible to identify a relevant presence of a random behavior. So, it was possible to accept the hipothesis that the markets are ineffectual in most of the historical series of restoration of indexes.

Este trabalho tem como objetivo a avaliação de três estimadores do parâmetro de integração fracionária d e de um teste para memória longa compartilhada. Os estimadores a serem avaliados são: o estimador de Geweke e Porter-Hudak, o estimador usando o periodograma suavizado e o estimador semiparamétrico truncado de Whittle. A avaliação dos estimadores será no contexto de processos ARFIMA+ARMA, e em relação a variações nos termos autoregressivos e de médias móveis, tanto do termo de memória curta quanto do termo de memória longa. Além disso, serão introduzidos o conceito de modelos com memória longa compartilhada e um método de identificação através da análise de correlação canônica para séries temporais multivariadas proposto, por Ray e Tsay (1997). Por fim, serão apresentadas três aplicações sobre dados reais dos tópicos estudados: uma para a velocidade do vento em São Paulo e Piracicaba e outras duas para séries das bolsas de valores de Hong Kong, Nova Zelândia, Singapura, Brasil e Reino Unido / The goal of this project is the evaluation of three long memory parameter estimators and a common long range dependence test. The estimators evaluated are: the Geweke and Porter-Hudak, the smoothed periodogram and the semiparametric truncated Whittle estimators. The evaluation is in the context of processes ARFIMA+ARMA, and related to variations in the autoregressive and moving average coefficients, both in the short and long memory terms. Furthermore, we describe common long range dependence processes and an identification approach (Ray and Tsay, 1997) for them, using the canonical correlation analysis. Finally, three applications to real data are presented: the first one to the wind\'s speed in the Brazilian cities of São Paulo and Piracicaba, and the other ones to financial time series of the stock markets of Hong Kong, New Zealand, Singapore, Brazil and the United Kingdom.

Este trabalho tem como objetivo a avaliação de três estimadores do parâmetro de integração fracionária d e de um teste para memória longa compartilhada. Os estimadores a serem avaliados são: o estimador de Geweke e Porter-Hudak, o estimador usando o periodograma suavizado e o estimador semiparamétrico truncado de Whittle. A avaliação dos estimadores será no contexto de processos ARFIMA+ARMA, e em relação a variações nos termos autoregressivos e de médias móveis, tanto do termo de memória curta quanto do termo de memória longa. Além disso, serão introduzidos o conceito de modelos com memória longa compartilhada e um método de identificação através da análise de correlação canônica para séries temporais multivariadas proposto, por Ray e Tsay (1997). Por fim, serão apresentadas três aplicações sobre dados reais dos tópicos estudados: uma para a velocidade do vento em São Paulo e Piracicaba e outras duas para séries das bolsas de valores de Hong Kong, Nova Zelândia, Singapura, Brasil e Reino Unido / The goal of this project is the evaluation of three long memory parameter estimators and a common long range dependence test. The estimators evaluated are: the Geweke and Porter-Hudak, the smoothed periodogram and the semiparametric truncated Whittle estimators. The evaluation is in the context of processes ARFIMA+ARMA, and related to variations in the autoregressive and moving average coefficients, both in the short and long memory terms. Furthermore, we describe common long range dependence processes and an identification approach (Ray and Tsay, 1997) for them, using the canonical correlation analysis. Finally, three applications to real data are presented: the first one to the wind\'s speed in the Brazilian cities of São Paulo and Piracicaba, and the other ones to financial time series of the stock markets of Hong Kong, New Zealand, Singapore, Brazil and the United Kingdom.

[pt] Este trabalho tem como objetivo o estudo das séries de energia natural afluente (ENAs) por meio de modelos de memória longa, no intuito de gerar cenários hidrológicos sintéticos. Séries temporais com memória longa são definidas como séries que apresentam persistente dependência entre observações afastadas por um longo período de tempo. Inicialmente procedeu-se uma análise exploratória através da qual foi possível encontrar características de série temporais com longa dependência. Os modelos empregados nesta dissertação foram os SARFIMA (p,d.q)x(P,D.Q)s em que os parâmetros dˆ e Dˆ assumem valores fracionários, para que seja possível a incorporação de efeitos de longa dependência e/ou cíclicos. Também foi utilizada a técnica de computação intensiva bootstrap em diversas etapas, dentre elas a construção de um teste não paramétrico para significância dos parâmetros fracionários, assim como bootstrap nos resíduos do modelo para a geração de séries hidrológicas sintéticas. Para averiguar a adequabilidade dos cenários gerados, foram realizados testes estatísticos de igualdade de médias, igualdade de variâncias, testes de aderência e análise de sequências. Por meio destes, pode-se concluir que os modelos empregados nesta dissertação conseguiram reproduzir de maneira satisfatória o histórico disponível de ENAs. / [en] The aim of this thesis is to study the series of natural energy surging (NES) through long memory models, whose interest is to fit models capable of generating synthetic hydrological series. Time Series with long memory are defined as a series which have persistent dependence between observations separated by a long period of time. Firstly, we proceed to the exploration analysis where we found particulars of long memory time series. The models employed is this work were SARFIMA (p, d, q)x(P, D,Q)s where parameters d and D assume fractional values so as to incorporate long memory and/or cycles effects. It was also used a intensive computational technique called bootstrap in various stages, among them the construction of a non-parametric test for the significant of fractional parameters and the bootstrap in the residual models for generating synthetic hydrological series. In order verify the accuracy of the scenarios generated, statistical tests were performed for equal means, equal variance, adherence test and sequence analysis. Through these, we can conclude that the models used in this thesis could satisfactorily reproduce the history of natural energy surging available.

No description available.

Persistence of stock returns is an extensively studied and discussed theme in the analysis of financial markets. Antipersistence is usually attributed to volatilities. However, not only volatilities but also stock returns can exhibit antipersistence. Antipersistent noise has a somewhat rougher appearance than Gaussian noise. Heuristically spoken, price movements are more likely followed by movements in the opposite direction than in the same direction. The pertaining integrated process exhibits a smaller range – prices seem to stay in the vicinity of the initial value. We apply a widely used test based upon the modified R/S-Method by Lo [1991] to daily returns of 21 German stocks from 1960 to 2008. Combining this test with the concept of moving windows by Carbone et al. [2004], we are able to determine periods of antipersistence for some of the series under examination. Our results suggest that antipersistence can be found for stocks and periods where extraordinary corporate actions such as mergers & acquisitions or financial distress are present. These effects should be properly accounted for when choosing and designing models for inference.

No description available.