Communications in Statistics - Simulation and Computation, Feb 19, 2009
In statistical data analysis, it is often important to compare, classify, and cluster different t... more In statistical data analysis, it is often important to compare, classify, and cluster different time series. For these purposes various methods have been proposed in the literature, but they usually assume time series with the same sample size. In this paper, we propose a spectral domain method for handling time series of unequal length. The method makes the spectral estimates comparable by producing statistics at the same frequency. The procedure is compared with other possible methods by a Monte Carlo simulation study. As an illustrative example, the proposed method is applied to cluster industrial production series of some developed countries.
This article may be used for research, teaching, and private study purposes. Any substantial or s... more This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.
This study investigates the presence of deterministic dependencies in international stock markets... more This study investigates the presence of deterministic dependencies in international stock markets using recurrence plots and recurrence quantification analysis (RQA). The results are based on a large set of free float-adjusted market capitalization stock indices, covering a period of 15 years. The statistical tests suggest that the dynamics of stock prices in emerging markets is characterized by higher values of RQA measures when compared to their developed counterparts. The behavior of stock markets during critical financial events, such as the burst of the technology bubble, the Asian currency crisis, and the recent subprime mortgage crisis, is analyzed by performing RQA in sliding windows. It is shown that during these events stock markets exhibit a distinctive behavior that is characterized by temporary decreases in the fraction of recurrence points contained in diagonal and vertical structures.
This study introduces a new distance measure for clustering financial time series based on varian... more This study introduces a new distance measure for clustering financial time series based on variance ratio test statistics. The proposed metric attempts to assess the level of interdependence of time series from the point of view of return predictability. Simulation results show that this metric aggregates better time series according to their serial dependence structure than a metric based on the sample autocorrelations. An empirical application of this approach to international stock market returns is presented. The results suggest that this metric discriminates reasonably well stock markets according to size and level of development. Furthermore, despite the substantial evolution of individual variance ratio statistics, the clustering pattern remains fairly stable across different time periods. * An earlier version of this paper was circulated under the title "Clustering global equity markets with variance ratio tests".
This study investigates the presence of deterministic dependencies in international stock markets... more This study investigates the presence of deterministic dependencies in international stock markets using recurrence plots and recurrence quantification analysis (RQA). The results are based on a large set of free float-adjusted market capitalization stock indices, covering a period of 15 years. The statistical tests suggest that the dynamics of stock prices in emerging markets is characterized by higher values of RQA measures when compared to their developed counterparts. The behavior of stock markets during critical financial events, such as the burst of the technology bubble, the Asian currency crisis, and the recent subprime mortgage crisis, is analyzed by performing RQA in sliding windows. It is shown that during these events stock markets exhibit a distinctive behavior that is characterized by temporary decreases in the fraction of recurrence points contained in diagonal and vertical structures.
We compare a data-driven domain agnostic set of canonical features with a smaller collection of f... more We compare a data-driven domain agnostic set of canonical features with a smaller collection of features that capture well-known stylized facts about financial asset returns. We show that these facts discriminate better different asset types than general-purpose features. Therefore, financial time series analysis is a domain where well-informed expert knowledge may not be disregarded in favor of agnostic representations of the data.
In this article, we examine the daily water demand forecasting performance of double seasonal uni... more In this article, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Holt-Winters, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. A within-week seasonal cycle and a within-year seasonal cycle are accommodated in the various model speci…cations to capture both seasonalities. We investigate whether combining forecasts from di¤erent methods for di¤erent origins and horizons could improve forecast accuracy. The analysis is made with daily data for water consumption in Granada, Spain.
Introduction: Several studies regarding the values and attitudes of Economics students have notic... more Introduction: Several studies regarding the values and attitudes of Economics students have noticed a greater leaning towards the free riding phenomena and the market economy. Are these traits always valid? Do they coexist with other sociological relevant aspects? Materials and Methods: A survey was conducted in Lisbon (Portugal) in 2016 with Economics students. In addition to the economic view, it was studied their self-perception at the left-right spectrum and their interest in politics. The results of this survey were compared with previous research on three social groups (young citizens, elder citizens, and other students). The data were statistically analyzed through correlation and factorial analysis tests. Results: The research revealed a tendency towards a right-wing self-perception and an increased concern about politics by these Portuguese students. However, these traits were attenuated, because those Economics students converge with other group's values, specially the "young citizens" and the "old citizens". Generally, groups with greater leaning towards free riding are also more inclined to pro-market ideas, right-wing, and interested in politics. Results indicate the existence of other substantially different behavioral components, being one of them correspondent to the variables used to measure "free riding" and an opposite component which we can label "open-mindedness". Discussion: As a whole, the results suggest a considerable influence of Economics in the mental framework of these students. Evidence seems to signal a diffuse cultural influence, corresponding to a simplified and impoverished version of the academic field.
In this article, we examine the daily water demand forecasting performance of double seasonal uni... more In this article, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Holt-Winters, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. A within-week seasonal cycle and a within-year seasonal cycle are accommodated in the various model speci…cations to capture both seasonalities. We investigate whether combining forecasts from di¤erent methods for di¤erent origins and horizons could improve forecast accuracy. The analysis is made with daily data for water consumption in Granada, Spain.
This paper proposes volatility and spectral based methods for cluster analysis of stock returns. ... more This paper proposes volatility and spectral based methods for cluster analysis of stock returns. Using the information about both the estimated parameters in the threshold GARCH (or TGARCH) equation and the periodogram of the squared returns, we compute a distance matrix for the stock returns. Clusters are formed by looking to the hierarchical structure tree (or dendrogram) and the computed principal coordinates. We employ these techniques to investigate the similarities and dissimilarities between the "bluechip" stocks used to compute the Dow Jones Industrial Average (DJIA) index.
Most of economic and financial time series have a nonstationary behavior. There are different typ... more Most of economic and financial time series have a nonstationary behavior. There are different types of nonstationary processes, such as those with stochastic trend and those with deterministic trend. In practice, it can be quite difficult to distinguish between the two processes. In this paper, we compare random walk and determinist trend processes using sample autocorrelation, sample partial autocorrelation and periodogram based metrics.
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