Jorge Caiado
ISEG, Mathematics, Faculty Member
- Jorge Caiado, after receiving his Ph.D. in Applied Mathematics to Economics and Management from the Technical Univers... moreJorge Caiado, after receiving his Ph.D. in Applied Mathematics to Economics and Management from the Technical University of Lisbon, joined the School of Economics and Management at Technical University of Lisbon where he is currently Professor of Econometrics and Time Series Analysis. From 1995 to 2003 he was Lecture at the Portuguese Bank Training Institute. During 2004-2005, he was visiting researcher of the Department of Statistics at University Carlos III of Madrid (Spain). He is now Vice-President of the Centre for Applied Mathematics and Economics (CEMAPRE). His research in econometrics, finance, time series analysis, forecasting methods and statistical software (EViews, Stata, and Lingo) has led to numerous publications in journals such as Quantitative Finance, Journal of Retailing and Consumer Services, Computational Statistics & Data Analysis, Management Decision, Journal of Business Economics and Management, Journal of Statistical Computation and Simulation, Communications in Statistics: Simulation and Computation, Physica A: Statistical Mechanics and its Applications, Journal of Hydrologic Engineering, Portuguese Journal of Management Studies, and others. He is also author and co-author of several books and chapters in books such as “Classification and Clustering of Time Series” (Lambert Academic Publishing, 2010), “Computational Statistics” (Physica-Verlag, 2008), “Recent Advances in Stochastic Modeling and Data Analysis” (World Scientific Publishing, 2007), "Handbook of Cluster Analysis (Taylor & Francis , 2015), "Métodos de Previsão em Gestão com aplicações em excel" (Edições Sílabo, 2nd Ed., 2016), "Gestão de Instituições Financeiras" (Edições Sílabo, 2nd Ed., 2008). He is serving as econometric and statistical consultant and trainer for numerous companies and organizations including central banks, commercial and investment banks, bureau of statistics, bureau of economic analysis, transportation and logistic companies, health companies and insurance companies.edit
The statistical discrimination and clustering literature has studied the problem of identifying similarities in time series data. Some studies use non-parametric approaches for splitting a set of time series into clusters by looking at... more
The statistical discrimination and clustering literature has studied the problem of identifying similarities in time series data. Some studies use non-parametric approaches for splitting a set of time series into clusters by looking at their Euclidean distances in the space of points. A new measure of distance between time series based on the normalized periodogram is proposed. Simulation results comparing this measure with others parametric and non-parametric metrics are provided. In particular , the classification of time series as stationary or as non-stationary is discussed. The use of both hierarchical and non-hierarchical clustering algorithms is considered. An illustrative example with economic time series data is also presented.
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This paper deals with hypothesis testing for independent time series with unequal length. It proposes a spectral test based on the distance between the periodogram ordinates and a parametric test based on the distance between the... more
This paper deals with hypothesis testing for independent time series with unequal length. It proposes a spectral test based on the distance between the periodogram ordinates and a parametric test based on the distance between the parameter estimates of fitted autoregressive moving average models. Both tests are compared with a likelihood ratio test based on the pooled spectra. In all cases, the null hypothesis is that the two series under consideration are generated by the same stochastic process. The performance of the three tests is investigated by a Monte Carlo simulation study.
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... 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
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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... 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. An empirical application of this approach to international stock market returns is presented. The results suggest that this metric discriminates reasonably
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This study explores the interconnection between human factors and social factors and analyses the relations influenced by the specific activity and age of firms. A statistical approach is implemented which applies factor analysis... more
This study explores the interconnection between human factors and social factors and analyses the relations influenced by the specific activity and age of firms. A statistical approach is implemented which applies factor analysis techniques, based on a sample of small and medium sized firms from four sectors of activity which are between four and fifteen years old, and are split
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This study explores the interconnection between human factors and social factors and analyses the relations influenced by the specific activity and age of firms. A statistical approach is implemented which applies factor analysis... more
This study explores the interconnection between human factors and social factors and analyses the relations influenced by the specific activity and age of firms. A statistical approach is implemented which applies factor analysis techniques, based on a sample of small and medium sized firms from four sectors of activity which are between four and fifteen years old, and are split into three time periods. It is found that there are interconnected groups of human capital and social capital factors, although a sizeable proportion of the literature conceptually separates these factors and deals with them individually. It is also ascertained that this relationship is influenced by the field of activity and the age of the firms.
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The behavior of international stock market returns in terms of rate of return, unconditional volatility, skewness, excess kurtosis, serial dependence and long-memory is examined. A factor analysis approach is employed to identify the... more
The behavior of international stock market returns in terms of rate of return, unconditional volatility, skewness, excess kurtosis, serial dependence and long-memory is examined. A factor analysis approach is employed to identify the underlying dimensions of stock market returns. In our approach, the factors are estimated not from the observed historical returns but from their empirical properties, without imposing any restriction about the time dependence of the observations. To identify clusters of markets and multivariate outliers, factor analysis is then used to generate factor scores. The findings suggest the existence of meaningful factors which determine the differences in terms of the dependence structure between developed and emerging market returns.
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In this paper, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Exponential Smoothing, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. We investigate... more
In this paper, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Exponential Smoothing, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. We investigate whether combining forecasts from different methods and from different origins and horizons could improve forecast accuracy. We use daily data for water consumption in Spain from 1 January 2001 to 30 June 2006.
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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... 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
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This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we... more
This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, 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
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Previous studies have investigated the comovements of international equity returns by using mean correlations, cointegration, common factor analysis, and other approaches. This paper investigates the evolution of the affinity among major... more
Previous studies have investigated the comovements of international equity returns by using mean correlations, cointegration, common factor analysis, and other approaches. This paper investigates the evolution of the affinity among major euro and non-euro area stock markets in the period 1966-2006 by using distance-based methods for clustering analysis of time series. A periodogram-based metric for mean and squared returns is
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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... 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 make the spectral estimates
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We propose a periodogram-based metric for classification and clustering of time series with different sample sizes. For such cases, we know that the Euclidean distance between the periodogram ordinates cannot be used. One possible way to... more
We propose a periodogram-based metric for classification and clustering of time series with different sample sizes. For such cases, we know that the Euclidean distance between the periodogram ordinates cannot be used. One possible way to deal with this problem is to interpolate lineary one of the periodograms in order to estimate ordinates of the same frequencies.
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The comparison and classification of time series is an important issue in practical time series analysis. For these purposes, various methods have been proposed in the literature, but all have shortcomings, especially when the observed... more
The comparison and classification of time series is an important issue in practical time series analysis. For these purposes, various methods have been proposed in the literature, but all have shortcomings, especially when the observed time series have different sample sizes. In this paper, we propose spectral domain methods for handling time series of unequal length. The methods make the
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This paper uses structural equation modeling to examine the linkages between financial performance, sporting performance and stock market performance for English football clubs over the period from 1995 to 2007. The results indicate that... more
This paper uses structural equation modeling to examine the linkages between financial performance, sporting performance and stock market performance for English football clubs over the period from 1995 to 2007. The results indicate that there is a strong correlation between financial and sporting latent constructs. Additionally, the study indicates that the sports managers seek to achieve a minimum level of
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The volatility clustering often seen in financial data has increased the interest of researchers in applying good models to measure and forecast stock returns. This paper aims to model the volatility for daily and weekly returns of the... more
The volatility clustering often seen in financial data has increased the interest of researchers in applying good models to measure and forecast stock returns. This paper aims to model the volatility for daily and weekly returns of the Portuguese Stock Index PSI-20. By using simple GARCH, GARCH-M, Exponential GARCH (EGARCH) and Threshold ARCH (TARCH) models, we find support that there are significant asymmetric shocks to volatility in the daily stock returns, but not in the weekly stock returns. We also find that some weekly returns time series properties are substantially different from properties of daily returns, and the persistence in conditional volatility is different for some of the sub-periods referred. Finally, we compare the forecasting performance of the various volatility models in the sample periods before and after the terrorist attack on September 11, 2001.
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ABSTRACT Purpose ‐ The aim of this paper is to evaluate the human capital and social capital of managers and the influence of these attributes on the performance of small and medium-sized Portuguese companies. Design/methodology/approach... more
ABSTRACT Purpose ‐ The aim of this paper is to evaluate the human capital and social capital of managers and the influence of these attributes on the performance of small and medium-sized Portuguese companies. Design/methodology/approach ‐ The structural modeling approach was applied to a sample of 199 small and medium-sized companies aged between 3 and 15 years, from five different sectors of activity. Findings ‐ It was found that human capital affects social capital, and that experience and cognitive ability influence personal relations and complicity. Organizational performance is strongly influenced by human capital through the cognitive ability of the manager. Practical implications ‐ Based on these findings managers can gain a better knowledge about how to improve the performance of their firms, for example through adjustments in communication methods or strategic decision capacities. Originality/value ‐ This work is innovative in the sense that it confirms the influence of human capital on social capital, and shows that it is cognitive ability that affects organizational performance.
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ABSTRACT This paper uses logistic regression analysis to examine how intramural and extramural R&D, acquisition of machinery, equipment and software, acquisition of external knowledge, training, market introduction and other... more
ABSTRACT This paper uses logistic regression analysis to examine how intramural and extramural R&D, acquisition of machinery, equipment and software, acquisition of external knowledge, training, market introduction and other procedures and technical preparations determine the innovation behaviour of manufacturing and service firms. We adopt a multidimensional view of innovation by considering product, process, organizational and marketing innovations as dependent variables separately. The study reports on the Community Innovation Survey (CIS4) of a small open-economy country. The empirical results indicate that intramural R&D has a positive impact on innovation. In contrast, the influence of extramural R&D on innovation is unclear. All innovation activities contribute towards organizational innovation. The study also suggests that there are no significant differences between services and manufacturing firms concerning the propensity to innovation.
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ABSTRACT This paper uses factor analysis methods to identify structures associated with human and social capital in a small country with an open-economy, based on a survey of small- and medium-sized companies across different sectors. The... more
ABSTRACT This paper uses factor analysis methods to identify structures associated with human and social capital in a small country with an open-economy, based on a survey of small- and medium-sized companies across different sectors. The purpose of this research is to investigate the influences of entrepreneurial and managerial behaviours on the relationship between human capital and social capital. The results indicate that the principal factor is highly correlated to the variables of experience, professional proficiency and cognitive ability, which are predominant characteristics of the entrepreneur, as well as status variables such as interlinking, family support, personal relations and social relations. The study also suggests that links between human capital and social capital are more salient in manufacturing and construction companies than in the wholesale trade, retail trade and services sectors.
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Several authors have been investigating which factors influence academic performance in undergraduate business and accounting courses. However, most of these studies are not conclusive and some results are contradictory. This study aims... more
Several authors have been investigating which factors influence academic performance in undergraduate business and accounting courses. However, most of these studies are not conclusive and some results are contradictory. This study aims to determine which demographic (age, sex, ...
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Os métodos estruturais de modelização de equações simultâneas usam a teoria económica para descrever as relações entre importantes variáveis económicas. Contudo, na maioria dos casos, a teoria económica não consegue estabelecer uma... more
Os métodos estruturais de modelização de equações simultâneas usam a teoria económica para descrever as relações entre importantes variáveis económicas. Contudo, na maioria dos casos, a teoria económica não consegue estabelecer uma especificação rigorosa da relação dinâmica entre essas variáveis e, além disso, os processos de estimação e inferência são complicados pelo facto de que podem aparecer variáveis endógenas em
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RESUMO O presente artigo pretende apresentar os principais resultados de um estudo empírico de modelação da série cronológica da taxa de juro nominal da operação activa do crédito a particulares em Portugal realizado por Caiado (1997).... more
RESUMO O presente artigo pretende apresentar os principais resultados de um estudo empírico de modelação da série cronológica da taxa de juro nominal da operação activa do crédito a particulares em Portugal realizado por Caiado (1997). Com base na metodologia dos modelos ARIMA com variáveis de intervenção e detecção de outliers , vai avaliar-se o impacto de alterações de relevo
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In addition to the members of the Editorial Board, the individuals listed below refereed manuscripts that were submitted to the journal. Their assistance is gratefully acknowledged. ... Ahmed Albatineh Kshanti Greene Jeffrey Andrews... more
In addition to the members of the Editorial Board, the individuals listed below refereed manuscripts that were submitted to the journal. Their assistance is gratefully acknowledged. ... Ahmed Albatineh Kshanti Greene Jeffrey Andrews Patrick Groenen Ron Artstein Brian Habing Elizabeth Ayers David Hand Mohammed Bennani Dosse Christian Hennig Halima Bensmail Bob Henson Wicher Bergsma John Hinde Patrice Bertrand François Husson Christophe Biernacki Huengsun Hwang Tammo Bijmolt Cem Iyigun Magnus Bordewich Julie Josse Paula Brito Sebastian Kaiser ...
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This paper proposes an asymmetric-volatility based method for cluster analysis of stock returns. Using the information about the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are... more
This paper proposes an asymmetric-volatility based method for cluster analysis of stock returns. Using the information about the estimated parameters in the TARCH equation, 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 "blue-chip" stocks used to compute the Dow Jones Industrial Average (DJIA) index.