The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance

This paper discusses the asymptotic and finite-sample properties of CUSUM-based tests for detecting structural breaks in volatility in the presence of stochastic contamination, such as additive outliers or measurement errors. This analysis is particularly relevant for financial data, on which these tests are commonly used to detect variance breaks. In particular, we focus on the tests by Inclán and Tiao [IT] (1994) and Kokoszka and Leipus [KL] (1998, 2000), which have been intensively used in the applied literature. Our results are extensible to related procedures. We show that the asymptotic distribution of the IT test can largely be affected by sample contamination, whereas the distribution of the KL test remains invariant. Furthermore, the break-point estimator of the KL test renders consistent estimates. In spite of the good large-sample properties of this test, large additive outliers tend to generate power distortions or wrong break-date estimates in small samples.

ON THE SMALL SAMPLE PROPERTIES OF DICKEY FULLER AND MAXIMUM LIKELIHOOD UNIT ROOT TESTS ON DISCRETE-SAMPLED SHORT-TERM INTEREST RATES

Testing for unit roots in short-term interest rates plays a key role in the empirical modelling of these series. It is widely assumed that the volatility of interest rates follows some time-varying function which is dependent of the level of the series. This may cause distortions in the performance of conventional tests for unit root nonstationarity since these are typically derived under the assumption of homoskedasticity. Given the relative unfamiliarity on the issue, we conducted an extensive Monte Carlo investigation in order to assess the performance of the DF unit root tests, and examined the effects on the limiting distributions of test procedures (t- and likelihood ratio tests) based on maximum likelihood estimation of models for short-term rates with a linear drift.Unit root, interest rates, CKLS model.

Efficient Tests of the Seasonal Unit Root Hypothesis*

In this paper we derive, under the assumption of Gaussian errors with known error covariance matrix, asymptotic local power bounds for seasonal unit root tests for both known and unknown deterministic scenarios and for an arbitrary seasonal aspect. We demonstrate that the optimal test of a unit root at a given spectral frequency behaves asymptotically independently of whether unit roots exist at other frequencies or not. We also develop modified versions of the optimal tests which attain the asymptotic Gaussian power bounds under much weaker conditions. We further propose near-efficient regression-based seasonal unit root tests using pseudo-GLS de-trending and show that these have limiting null distributions and asymptotic local power functions of a known form. Monte Carlo experiments indicate that the regression-based tests perform well in finite samples.Point optimal invariant (seasonal) unit root tests, asymptotic local power bounds, near seasonal integration

Calendar Effects in Daily ATM Withdrawals

This paper analyses the calendar effects present in Automated Teller Machines (ATM) withdrawals of residents, using daily data for Portugal for the period from January 1st 2001 to December 31st 2008. The results presented may allow for a better understanding of consumer habits and for adjusting the original series for calendar effects. Considering the Quarterly National Accounts’ procedure of adjusting data for seasonality and working days effects, this correction is important to ensure the use of the ATM series as an instrument to nowcast private consumption.

The behaviour of seasonal unit root tests under neglected local drifts

This paper analyses the limit distributions of the seasonal unit root test procedures proposed by Dickey, Hasza and Fuller (1984) and Hylleberg, Engle, Granger and Yoo (1990), when local trends at different frequencies are present in data generation processes, but ignored in the test regressions used. The findings presented explicitly show that neglected deterministic trends have negative effects on the distributions of the test statistics. Analytical observations and Monte Carlo simulations reveal that seasonal unit root test statistics become severely undersized as the values of standardized local trends increase. Hence, failure to consider local trends may often bear the undesirable effect of biasing decisions towards non-rejection of unit roots.info:eu-repo/semantics/publishedVersio

3D Point Cloud Data and Triangle Face Compression by a Novel Geometry Minimization Algorithm and Comparison with other 3D Formats

Polygonal meshes remain the primary representation for visualization of 3D data in a wide range of industries including manufacturing, architecture, geographic information systems, medical imaging, robotics, entertainment, and military applications. Because of its widespread use, it is desirable to compress polygonal meshes stored in file servers and exchanged over computer networks to reduce storage and transmission time requirements. 3D files encoded by OBJ format are commonly used to share models due to its clear simple design. Normally each OBJ file contains a large amount of data (e.g. vertices and triangulated faces) describing the mesh surface. In this research we introduce a novel algorithm to compress vertices and triangle faces called Geometry Minimization Algorithm (GM-Algorithm). First, each vertex consists of (x, y, z) coordinates that are encoded into a single value by the GM-Algorithm. Second, triangle faces are encoded by computing the differences between two adjacent vertex locations, and then coded by the GM-Algorithm followed by arithmetic coding. We tested the method on large data sets achieving high compression ratios over 90% while keeping the same number of vertices and triangle faces as the original mesh. The decompression step is based on a Parallel Fast Matching Search Algorithm (Parallel-FMS) to recover the structure of the 3D mesh. A comparative analysis of compression ratios is provided with a number of commonly used 3D file formats such as MATLAB, VRML, OpenCTM and STL showing the advantages and effectiveness of our approach

A new 2D image compression technique for 3D surface reconstruction

Image compression is one of the important techniques used today for image and video transmission. There are many types of image compression techniques are used these days; one of them is JPEG technique. In this research, we introduce a new idea for applying the JPEG technique with Discrete Wavelet Transform (DWT) for high-resolution images. Our image compression algorithm consists of; firstly, transform an image by single level DWT. Secondly, JPEG algorithm applied on "LL" sub-band this process is called JPEG Transformation. Thirdly, separate the final transformed matrix into DC-Array and AC-Matrix contains DC values and AC coefficients respectively. Finally, the minimize-matrix-size algorithm applied on AC-Matrix followed by arithmetic coding. The novel decompression algorithm used in this research is Parallel Sequential Search Algorithm, which is represented inverse minimize-matrix-size algorithm. The searching algorithm consist of a P pointers, all these pointers are working in parallel to find the original AC-coefficients. Thereafter, combines all decoded DC-values with the decoded ACcoefficients in one matrix followed by apply inverse JPEG transformed and inverse DWT. the technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm by using 2D and 3D RMS

Finite Sample Performance of Frequency and Time Domain Tests for Seasonal Fractional Integration

Testing the order of integration of economic and financial time series has become a conventional procedure prior to any modelling exercise. In this paper, we investigate and compare the finite sample properties of the frequency domain tests proposed by Robinson (1994) and the time domain procedure proposed by Hassler, Rodrigues and Rubia (2008) when applied to seasonal data.

Necessidade de adaptar e ajustar a IAS 41 ao sector agrícola português

O sector agrícola, não obstante representar em Portugal uma parte com algum significado na formação do PIB e de já ter sido o principal sector da actividade económica do país, consequência da forma como sempre foram estruturadas as suas explorações e de nem sempre ter sido sensível aos sinais do mercado, nunca mereceu uma atenção especial no domínio da estruturação da sua informação financeira. Entrados no século XXI, num mundo globalizado e onde as questões relacionadas com a normalização da informação financeira estão na ordem do dia, os problemas relacionados com a discussão do tratamento contabilístico dos fenómenos ligados às actividades inseridas no sector agrícola reivindicam a necessidade da existência de um quadro normativo que favoreça o cumprimento dos objectivos e das características da informação financeira. É nessa medida que o nosso trabalho discute os critérios valorimétricos que devem ser adoptados para a mensuração dos factos patrimoniais no âmbito destas actividades, designadamente quanto ao reconhecimento e mensuração dos activos biológicos e dos produtos agrícolas, na base dos conceitos explicitados na IAS 41. Tomando como ponto de partida essa norma procuramos verificar em que condições é que pode ser adaptável a valorimetria proposta ao caso das empresas agrícolas portuguesas, distinguimos as condições de aplicação em face da estrutura e dimensão das unidades produtivas. Ao desenvolvermos esta abordagem relacionamo-la, também, com o tratamento contabilístico que deve ser dado aos activos biológicos, nas suas diferentes fases, e aos produtos agrícolas, tomando como referência o plano de contas inserto no POC. A especificidade do sector obriga-nos a considerar determinadas componentes dos custos e dos proveitos que deverão ter um tratamento dedicado, ou seja, e que tem a ver com os riscos associados à actividade agrícola (ordinários e extraordinários), os custos ambientais a jusante das explorações agrícolas, e, bem assim, a sua repercussão na formação dos resultados e os subsídios destinados ao apoio das actividades agrícolas, no seu sentido mais lato, nos quais distinguimos os diferentes tipos de subsídios existentes e do seu efeito ao nível do tratamento contabilístico que deverão ter

O efeito da aplicação do SNC no capital próprio – evidência em 50 empresas sujeitas a revisão legal de contas

With the approval of the Sistema Normalização Contabilística (SNC), will come into force after 1st January of 2010, the purpose of this study is to analyze and evaluate the impact of SNC application on equity value. Select for this purpose 50 companies audited. The results indicate a considerable part is which (66%) had not impacts. That some items of the balance show some impacts. We emphasize the item of government subsidies and intangible assets. Additionally, the study does not suggest a significant impact in the quality of financial reports, especially in disclosures