O presente trabalho trata-se de um estudo de testes de sazonalidade em séries temporais lineares. O texto é resultado de uma vasta pesquisa abrangendo diversos artigos e livros relacionados ao tema. Inicialmente, um teste de raízes unitárias correspondente a frequências sazonais para dados trimestrais é apresentado. Esse teste é denominado procedimento HEGY e permite que raízes unitárias sejam testadas em algumas frequências sazonais isoladas, sem assumir que raízes unitárias estejam presentes em todas as frequências sazonais. Em seguida, a extensão desse teste para dados mensais é analisada e um teste mais poderoso que combina o procedimento trimestral e mensal é apresentado. Observações atípicas e erros de medida são estudados, a fim de avaliar os efeitos que causam no comportamento dos testes de raízes unitárias e de apresentar um teste que contemple a correção de atipicidades. Por fim, é analisada a robustez assintótica do procedimento HEGY na presença de quebras estruturais (mudança de magnitude finita na média sazonal) e um teste mais poderoso que incorpora a quebra estrutural é apresentado. A fim de ilustrar e complementar as análises teóricas apresentadas, algumas aplicações em séries temporais reais são desenvolvidas. Os dados analisados foram obtidos do Instituto Brasileiro de Geografia e Estatística (IBGE) e o software utilizado para análise foi o R. / This current paper is a testing study for seasonality in time linear series. The text is the result of an extensive search covering several articles and books related to this subject. Initially, a test of unit roots corresponding to seasonal frequencies in quarterly data is presented. This test is called procedure HEGY and it allows the unit roots to be tested in some isolated seasonal frequencies, without assuming that the unit roots are present at all seasonal frequencies. Then, the extension of this test to monthly data is analyzed and a test that combines the most powerful procedure is presented quarterly and monthly. Atypical observations and errors of measurement are studied to evaluate the effects that they can cause on the behavior of the unit root tests and to present a test that includes the correction of this difference. Finally, we examined the asymptotic robustness procedure HEGY in the presence of structural breaks (finite magnitude of change in seasonal average) and a more powerful test that incorporates a structural break is introduced. In order to illustrate and complement the presented theoretical analysis, some applications in real time series are developed. The data were obtained from the Instituto Brasileiro de Geografia e Estatística (IBGE) and the R software was used for the analysis.

O presente trabalho trata-se de um estudo de testes de sazonalidade em séries temporais lineares. O texto é resultado de uma vasta pesquisa abrangendo diversos artigos e livros relacionados ao tema. Inicialmente, um teste de raízes unitárias correspondente a frequências sazonais para dados trimestrais é apresentado. Esse teste é denominado procedimento HEGY e permite que raízes unitárias sejam testadas em algumas frequências sazonais isoladas, sem assumir que raízes unitárias estejam presentes em todas as frequências sazonais. Em seguida, a extensão desse teste para dados mensais é analisada e um teste mais poderoso que combina o procedimento trimestral e mensal é apresentado. Observações atípicas e erros de medida são estudados, a fim de avaliar os efeitos que causam no comportamento dos testes de raízes unitárias e de apresentar um teste que contemple a correção de atipicidades. Por fim, é analisada a robustez assintótica do procedimento HEGY na presença de quebras estruturais (mudança de magnitude finita na média sazonal) e um teste mais poderoso que incorpora a quebra estrutural é apresentado. A fim de ilustrar e complementar as análises teóricas apresentadas, algumas aplicações em séries temporais reais são desenvolvidas. Os dados analisados foram obtidos do Instituto Brasileiro de Geografia e Estatística (IBGE) e o software utilizado para análise foi o R. / This current paper is a testing study for seasonality in time linear series. The text is the result of an extensive search covering several articles and books related to this subject. Initially, a test of unit roots corresponding to seasonal frequencies in quarterly data is presented. This test is called procedure HEGY and it allows the unit roots to be tested in some isolated seasonal frequencies, without assuming that the unit roots are present at all seasonal frequencies. Then, the extension of this test to monthly data is analyzed and a test that combines the most powerful procedure is presented quarterly and monthly. Atypical observations and errors of measurement are studied to evaluate the effects that they can cause on the behavior of the unit root tests and to present a test that includes the correction of this difference. Finally, we examined the asymptotic robustness procedure HEGY in the presence of structural breaks (finite magnitude of change in seasonal average) and a more powerful test that incorporates a structural break is introduced. In order to illustrate and complement the presented theoretical analysis, some applications in real time series are developed. The data were obtained from the Instituto Brasileiro de Geografia e Estatística (IBGE) and the R software was used for the analysis.

No description available.

本研究利用ADF單根檢定以及新觀點的季節性單根檢定做為分析工具，去檢測期貨巿場與現貨巿場是否存在一長期均衡關係。研究對象共有十種，分別為：能源期貨－輕原油、煤油，外匯期貨－日圓、瑞士法郎（對美元），短期利率期貨－一個月期倫敦銀行拆款利率、90天期美國國庫券，公債期貨－2年的美國中期公債、15至30年的美國長期公債，S&P500指數期貨，金屬期貨－高等級銅期貨。 過去檢測長期均衡關係所使用的單根檢定觀點假設其他頻率的單根並不存在，因此當拒絕虛無假設時，我們無法確知拒絕的原因是資料真的沒有單根的存在，抑或是資料具有季節性現象，因此納入季節性考量的HEGY檢定法，將是比較一般化的檢定方法，而且因為HEGY能夠同時檢定季節性及某些非季節性單根的存在與否，而不必假設所有季節性頻率的單根皆同時存在，所以ADF單根檢定法可視為HEGY季節性單根檢定法之特例，因此一般來說，HEGY檢定法之檢定力較ADF單根檢定法為高。 而本文實證結果亦證明，ADF單根檢定法的確無法檢定出季節性單根的有無，當季節性因素存在時，使用ADF單根檢定將可能導致錯誤的推論。

The output of the National economy of the Czech Republic is conditioned by a sum of important factors. There are sectors, which increased power during the last two decades, mainly due to expansion of modern technologies and knowledge workers. One of this is Construction. Construction is specific to its position in the economy and in particular is characterized by the greatest seasonality ever. However, this is not a problem for statistical analysis, rather a benefit. Modern approaches allow us to analyze seasonal fluctuations. From selected data we are able to construct evolutionary forecasts. The work will be performed for the most important indicators in the Czech Construction. The outcome of the paper will be conditional forecasts of these indicators. It will also make analyze of the relationship between these indicators and other variables that might affected it. The work is practical application of stochastic modeling approach by Box and Jenkins, augmented by more modern approaches, such as verification of Granger causality and co-integration and testing of seasonal unit roots by Hylleberg et al.

In recent years, many research works such as Tiao and Tsay (1994), Stock and Watson (1999), Chen et al. (2001), Clements and Jeremy (2001), Marcellino (2002), Laurini and Vieira (2005) and others have described the dynamic features of many macroeconomic variables as nonlinear. Using the approach of Keenan (1985) and Tsay (1989) this study shown that Ghana inflation rates from January 1980 to December 2009 follow a threshold nonlinear process.  In order to take into account the nonlinearity in the inflation rates we then apply a two regime nonlinear SETAR model to the inflation rates and then study both in-sample and out-of-sample forecast performance of this model by comparing it with the linear SARIMA model. Based on the in-sample forecast assessment from the linear SARIMA and the nonlinear SETAR models, the forecast measure MAE and RMSE suggest that the nonlinear SETAR model outperform the linear SARIMA model. Also using multi-step-ahead forecast method we predicted and compared the out-of-sample forecast of the linear SARIMA and the nonlinear SETAR models over the forecast horizon of 12 months during the period of 2010:1 to 2010:12. From the results as suggested by MAE and RMSE, the forecast performance of the nonlinear SETAR models is superior to that of the linear SARIMA model in forecasting Ghana inflation rates. Thought the nonlinear SETAR model is superior to the SARIMA model according to MAE and RMSE measure but using Diebold-Mariano test, we found no significant difference in their forecast accuracy for both in-sample and out-of-sample.

Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates in Ghana. Using monthly inflation data from July 1991 to December 2009, we find that ARIMA (1,1,1)(0,0,1)12 can represent the data behavior of inflation rate in Ghana well. Based on the selected model, we forecast seven (7) months inflation rates of Ghana outside the sample period (i.e. from January 2010 to July 2010). The observed inflation rate from January to April which was published by Ghana Statistical Service Department fall within the 95% confidence interval obtained from the designed model. The forecasted results show a decreasing pattern and a turning point of Ghana inflation in the month of July.

Submitted by Bruno Rodrigues Domingues (xistaum@hotmail.com) on 2013-03-04T01:01:01Z No. of bitstreams: 1 Dissertação_Verificação_ciclos_v5.pdf: 974726 bytes, checksum: d8c2d7df3a1ea76b56106d878af8ede0 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-03-04T13:11:50Z (GMT) No. of bitstreams: 1 Dissertação_Verificação_ciclos_v5.pdf: 974726 bytes, checksum: d8c2d7df3a1ea76b56106d878af8ede0 (MD5) / Made available in DSpace on 2013-03-04T13:12:42Z (GMT). No. of bitstreams: 1 Dissertação_Verificação_ciclos_v5.pdf: 974726 bytes, checksum: d8c2d7df3a1ea76b56106d878af8ede0 (MD5) Previous issue date: 2013-02-05 / Este trabalho se propõe a avaliar a existência de ciclos de margem de subscrição no mercado segurador brasileiro para os grupos de ramos de automóvel, patrimonial, responsabilidade civil e transportes a partir de dados da SUSEP. É feita uma introdução em seguros, uma revisão dos artigos que foram realizados no mundo sobre o assunto assim como os estudos discorrendo sobre as possíveis causas para a existência destes ciclos. Em seguida são apresentadas as técnicas econométricas de séries de tempo estruturais e o teste HEGY utilizadas para a verificação dessa hipótese. Foram encontrados ciclos nos grupos de ramos de automóveis, patrimoniais e transportes e não encontramos evidências de ciclos para responsabilidade civil e nem para o agregado de ramos. Os resultados desse estudo sobre a existência, ou não dos ciclos, assim como sua duração considerando as particularidades de cada tipo de ramo, periodicidade das séries e utilização ou não da despesa de comercialização foram analisados para cada grupo de ramos, considerando suas particularidades. Finalmente se fez um comparativo dos resultados obtidos nesse estudo com o que está na literatura para diversos outros mercados de seguros de outros países. / This study examines the existence of underwriting cycles in the Brazilian insurance market for four lines of insurance: marine, property, motor and liability using data from SUSEP. An overview of insurance is given as well as a quick explanation of insurance accounting practices in Brazil. A review of the literature published over this subject and the possible causes of these cycles are provided as well. The econometrics techniques are presented and an alternative methodology for verifying cycles is proposed. The analyses of the results were made in two steps. First a comparison between the results per lines was made considering specificities of each line. The results were then compared with the results from other countries. Evidences of cycles were found for the automobile, marine and property lines, in contrast to liability and when the lines were aggregated.