All Stories

  1. The Effect of the North Atlantic Oscillation on Monthly Precipitation in Selected European Locations: A Non‐Linear Time Series Approach
  2. Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model
  3. Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model
  4. Long monthly European temperature series and the North Atlantic Oscillation
  5. Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks
  6. A Parsimonious Test of Constancy of a Positive Definite Correlation Matrix in a Multivariate Time-Varying GARCH Model
  7. Comprehensively testing linearity hypothesis using the smooth transition autoregressive model
  8. Transition from the Taylor rule to the zero lower bound
  9. Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model
  10. Global hemispheric temperatures and co-shifting: A vector shifting-mean autoregressive analysis
  11. The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016
  12. Nonlinear Models in Macroeconometrics
  13. A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model
  14. Terms-of-trade shocks and macroeconomic volatility in developing countries: panel smooth transition regression models
  15. testing volatility models
  16. Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques
  17. A Smooth Transition Logit Model of The Effects of Deregulation in the Electricity Market
  18. GARCH models with time-varying parameters
  19. Changes in Conditional Correlations of Asset Returns
  20. Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009
  21. Conditional Correlation Models of Autoregressive Conditional Heteroscedasticity With Nonstationary GARCH Equations
  22. Modelling changes in the unconditional variance of long stock return series
  23. Thresholds and Smooth Transitions in Vector Autoregressive Models
  24. Modelling volatility by variance decomposition
  25. Testing the Granger Noncausality Hypothesis in Stationary Nonlinear Models of Unknown Functional Form
  26. Forecasting With Nonlinear Time Series Models
  27. Nonlinear Models for Autoregressive Conditional Heteroskedasticity
  28. Modelling Nonlinear Economic Time Series
  29. Stylized facts of return series, robust estimates and three popular models of volatility
  30. Sir Clive William John Granger, 1934–2009
  31. Garch Models
  32. Working With Clive Granger: Two Short Memories
  33. Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model
  34. Testing for volatility interactions in the Constant Conditional Correlation GARCH model
  35. Multivariate GARCH Models
  36. An Introduction to Univariate GARCH Models
  37. Testing Parameter Constancy in Stationary Vector Autoregressive Models Against Continuous Change
  38. Positivity constraints on the conditional variances in the family of conditional correlation GARCH models
  39. Modelling Autoregressive Processes with a Shifting Mean
  40. Parameterizing Unconditional Skewness in Models for Financial Time Series
  41. Testing constancy of the error covariance matrix in vector models
  42. Simulation-based Finite Sample Linearity Test against Smooth Transition Models*
  43. A sequential procedure for determining the number of regimes in a threshold autoregressive model
  44. Common factors in conditional distributions for bivariate time series
  45. A time series model for an exchange rate in a target zone with applications
  46. Chapter 8 Forecasting economic variables with nonlinear models
  47. Evaluating Models of Autoregressive Conditional Duration
  48. Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination
  49. Reply
  50. Building neural network models for time series: a statistical approach
  51. AN EXTENDED CONSTANT CONDITIONAL CORRELATION GARCH MODEL AND ITS FOURTH-MOMENT STRUCTURE
  52. Smooth Transition Regression Modeling
  53. The net barter terms of trade: A smooth transition approach
  54. Time-Varying Smooth Transition Autoregressive Models
  55. Evaluating GARCH models
  56. Long memory and nonlinear time series
  57. MOMENT STRUCTURE OF A FAMILY OF FIRST-ORDER EXPONENTIAL GARCH MODELS
  58. MODELING ASYMMETRIES AND MOVING EQUILIBRIA IN UNEMPLOYMENT RATES
  59. SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS
  60. Non-linear error correction and the UK demand for broad money, 1878-1993
  61. A nonlinear time series model of El Niño
  62. Properties of moments of a family of GARCH processes
  63. Testing parameter constancy in linear models against stochastic stationary parameters
  64. Short-term forecasting of industrial production with business survey data: experience from Finland's great depression 1990–1993
  65. Testing the adequacy of smooth transition autoregressive models
  66. Power Properties of Linearity Tests for Time Series
  67. Modelling nonlinearity in U.S. Gross national product 1889?1987
  68. Testing the constancy of regression parameters against continuous structural change
  69. The combination of forecasts using changing weights
  70. Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models
  71. Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models
  72. Chapter 48 Aspects of modelling nonlinear time series
  73. Use of preliminary values in forecasting industrial production
  74. Testing Linearity Against Smooth Transition Autoregressive Models
  75. Superiority comparisons between mixed regression estimators
  76. Testing linearity against smooth transition autoregressive models
  77. Usefulness of proxy variables in linear models with stochastic regressors
  78. The extended Stein procedure for simultaneous model selection and parameter estimation
  79. Superiority comparisons of heterogeneous linear estimators
  80. MINK AND MUSKRAT INTERACTION:A STRUCTURAL ANALYSIS
  81. Underestimation of mean square error matrix in misspecified linear models
  82. A comparison of mixed and minimax estimators of linear models
  83. The polynomial distributed lag revisited
  84. Forecasting the consumption of alcoholic beverages in Finland
  85. Forecasting with Smooth Transition Autoregressive Models