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Forecasting US consumer price index: does nonlinearity matter?
16 references·0 citing·42 second hop
Forecasting US consumer price index: does nonlinearity matter? (2016)Forecasting US consumer price index: does…Forecasting Inflation (2013)Forecasting InflationForecast comparisons in unstable environments (2010)Forecast comparisons in unsta…Introduction to time series analysis and forecasting (2008)Introduction to time series a…Another look at measures of forecast accuracy (2006)Another look at measures of f…LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power (2001)LAG Length Selection and the …GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics (2001)GARCH 101: The Use of ARCH/GA…Using genetic algorithms to find technical trading rules (1999)Using genetic algorithms to f…Forecasting with artificial neural networks: (1998)Forecasting with artificial n…Testing the equality of prediction mean squared errors (1997)Testing the equality of predi…Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach (1997)Is Technical Analysis in the …Designing a neural network for forecasting financial and economic time series (1996)Designing a neural network fo…A test for independence based on the correlation dimension (1996)A test for independence based…Comparing Predictive Accuracy (1995)Comparing Predictive AccuracyComparing Predictive Accuracy (1994)Comparing Predictive AccuracySeasonal integration and cointegration (1990)Seasonal integration and coin…Industrial and business forecasting methods (1982)Industrial and business forec…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)ARCH modeling in finance (1992)Introductory Econometrics for Finance (2008)Book Review: Time Series Analysis: Forecasting and Control (1977)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)Financial time series forecasting using support vector machines (2003)Time series forecasting using a hybrid ARIMA and neural network model (2003)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Forecasting Economic Time Series (2000)25 years of time series forecasting (2006)Tests of Conditional Predictive Ability (2006)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Forecasting methods and applications (1993)Principles of Forecasting (2001)Analysis of Financial Time Series (2006)Automatic Time Series Forecasting: The forecast Package for R (2008)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)New frontiers for arch models (2002)Systemic Risk Measurement: Multivariate GARCH Estimation of CoVaR (2012)Short-Term Traffic Flow Forecasting: An Experimental Comparison of Time-Series Analysis and Supervised Learning (2013)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data (1993)Likelihood-Based Inference in Cointegrated Vector Autoregressive Models (1995)Testing for a Unit Root in Time Series Regression (1988)Efficient Tests for an Autoregressive Unit Root (1996)A PANIC Attack on Unit Roots and Cointegration (2004)Energy consumption, income, and carbon emissions in the United States (2006)Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia (2013)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation (1991)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Combining forecasts: A review and annotated bibliography (1989)Consumption, Aggregate Wealth, and Expected Stock Returns (2001)Deep learning with long short-term memory networks for financial market predictions (2017)Predictions of Freeway Traffic Speeds and Volumes Using Vector Autoregressive Models (2009)Neural-Network-Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm (2011)Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model (2019)
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References

  • 2006Another look at measures of forecast accuracy5,980 cited
  • 1994Comparing Predictive Accuracy5,578 cited
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  • 1998Forecasting with artificial neural networks:4,282 cited
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  • 1996A test for independence based on the correlation dimension3,573 cited
  • 1997Testing the equality of prediction mean squared errors2,123 cited
  • 1990Seasonal integration and cointegration1,475 cited
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  • 2001GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics1,279 cited
  • 1996Designing a neural network for forecasting financial and economic time series1,092 cited
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  • 2013

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Forecasting Inflation
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