Central bank research hub - Papers by Marián Vávra
https://www.bis.org/cbhub/list/author/author_15857/index.rss
Research hub papers by author Marián VávraenBootstrap Assisted Tests of Symmetry for Dependent Data
https://www.nbs.sk/_img/Documents/PUBLIK/WP_5_2018_Vavra_Bootstrap_Tests_Symmetry.pdf
National Bank of Slovakia Working Papers by Zacharias Psaradakis and Marián VávraBootstrap Assisted Tests of Symmetry for Dependent Data2018-10-01T00:00:05ZThe paper considers the problem of testing for symmetry (about an unknown centre) of the marginal distribution of a strictly stationary and weakly dependent stochastic process. The possibility of using the autoregressive sieve bootstrap and stationary bootstrap procedures to obtain critical values and P-values for symmetry tests is explored. Bootstrap-assisted tests for symmetry are straightforward to implement and require no prior estimation of asymptotic variances. The small-sample properties of a wide variety of tests are investigated using Monte Carlo experiments. A bootstrap-assisted version of the triples test is found to have the best overall performance.Bootstrap Assisted Tests of Symmetry for Dependent DataFull texthttps://www.nbs.sk/_img/Documents/PUBLIK/WP_5_2018_Vavra_Bootstrap_Tests_Symmetry.pdfZacharias PsaradakisMarián VávraZacharias Psaradakis and Marián Vávra2018-10National Bank of Slovakia Working PapersC12C15C22Assessing Distributional Properties of Forecast Errors
https://www.nbs.sk/_img/Documents/PUBLIK/WP_3_2018_Vavra_Forecast_Errors_EN.pdf
National Bank of Slovakia Working Papers by Marián VávraAssessing Distributional Properties of Forecast Errors2018-03-01T01:00:03ZThis paper considers the problem of assessing the distributional properties (normality and symmetry) of macroeconomic forecast errors of G7 countries for the purpose of fan-chart modelling. Test statistics based on a Cramer von-Mises distance are used with critical values obtained via a bootstrap. Our results indicate that the assumption of symmetry of the marginal distribution of forecast errors is reasonable whereas the assumption of normality is not.Assessing Distributional Properties of Forecast ErrorsFull texthttps://www.nbs.sk/_img/Documents/PUBLIK/WP_3_2018_Vavra_Forecast_Errors_EN.pdfMarián VávraMarián Vávra2018-03National Bank of Slovakia Working PapersC12C15C22C53Normality Tests for Dependent Data
https://www.nbs.sk/_img/Documents/PUBLIK/WP_12_2017_Vavra_Normality_Tests_EN.pdf
National Bank of Slovakia Working Papers by Zacharias Psaradakis and Marián VávraNormality Tests for Dependent Data2017-12-01T00:00:12ZThe paper considers the problem of testing for normality of the one-dimensional marginal distribution of a strictly stationary and weakly dependent stochastic process. The possibility of using an autoregressive sieve bootstrap procedure to obtain critical values and P-values for normality tests is explored. The small-sample properties of a variety of tests are investigated in an extensive set of Monte Carlo experiments. The bootstrap version of the classical skewness-kurtosis test is shown to have the best overall performance in small samples.Normality Tests for Dependent DataFull texthttps://www.nbs.sk/_img/Documents/PUBLIK/WP_12_2017_Vavra_Normality_Tests_EN.pdfZacharias PsaradakisMarián VávraZacharias Psaradakis and Marián Vávra2017-12National Bank of Slovakia Working PapersC12C15C32Testing the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle Decompositions
http://www.nbs.sk/_img/Documents/PUBLIK/WP_4_2016_Vavra_Testing_Validity_UC-ARIMA_Models.pdf
National Bank of Slovakia Working Papers by Marián VávraTesting the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle Decompositions2016-09-01T00:00:00ZThis article tests the validity of underlying assumptions (i.e. linearity and normality) of UC-ARIMA models for trend-cycle decompositions using macroeconomic variables from 16 OECD countries. Clear and overwhelming evidence of non-normality and non-linearity is found. Our results thus cast doubts on the adequacy of the filtered cyclical component from this type of model.Testing the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle DecompositionsFull texthttp://www.nbs.sk/_img/Documents/PUBLIK/WP_4_2016_Vavra_Testing_Validity_UC-ARIMA_Models.pdfMarián VávraMarián Vávra2016-09National Bank of Slovakia Working PapersC12C22E32Portmanteau Tests for Linearity of Stationary Time Series
http://www.nbs.sk/_img/Documents/PUBLIK/WP_1_2016_Vavra_Psaradakis_Portmanteau_tests.pdf
National Bank of Slovakia Working Papers by Zacharias Psaradakis and Marián VávraPortmanteau Tests for Linearity of Stationary Time Series2016-05-01T00:00:00ZThis paper considers the problem of testing for linearity of stationary time series. Portmanteau tests are discussed which are based on generalized correlations of residuals from a linear model (that is, autocorrelations and cross-correlations of different powers of the residuals). The finite-sample properties of the tests are assessed by means of Monte Carlo experiments. The tests are applied to 100 time series of stock returns.Portmanteau Tests for Linearity of Stationary Time SeriesFull texthttp://www.nbs.sk/_img/Documents/PUBLIK/WP_1_2016_Vavra_Psaradakis_Portmanteau_tests.pdfZacharias PsaradakisMarián VávraZacharias Psaradakis and Marián Vávra2016-05National Bank of Slovakia Working PapersC12C22C52