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Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions
11 references·3 citing·35 second hop
Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions (2014)Bootstrap prediction intervals for linear…GARCH Models: Structure, Statistical Inference and Financial Applications (2019)GARCH Models: Structure, Stat…GARCH Models: Structure, Statistical Inference and Financial Applications (2014)GARCH Models: Structure, Stat…Threshold models in time series analysis — 30 years on (2011)Threshold models in time seri…On the least squares estimation of multiple-regime threshold autoregressive models (2011)On the least squares estimati…Bootstrap predictive inference for ARIMA processes (2004)Bootstrap predictive inferenc…Forecasting time series with sieve bootstrap (2002)Forecasting time series with …Bootstrap prediction intervals for autoregressions (1990)Bootstrap prediction interval…Bootstrap Prediction Intervals for Autoregression (1990)Bootstrap Prediction Interval…Estimating Properties of Autoregressive Forecasts (1987)Estimating Properties of Auto…Bootstrap Prediction Intervals for Regression (1985)Bootstrap Prediction Interval…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Autoregressive Conditional He…Robust bootstrap forecast densities for GARCH returns and volatilities (2017)Robust bootstrap forecast den…Model-Free vs. Model-Based Volatility Prediction (2015)Model-Free vs. Model-Based Vo…Bootstrap Joint Prediction Regions (2014)Bootstrap Joint Prediction Re…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)Renewable energy and growth: Evidence from heterogeneous panel of G7 countries using Granger causality (2015)Does Globalisation Worsen Environmental Quality in Developed Economies? (2017)How strong is the causal relationship between globalization and energy consumption in developed economies? A country-specific time-series and panel analysis (2017)Determination of Sample Sizes for Setting Tolerance Limits (1941)The Predictive Sample Reuse Method with Applications (1975)Determinants of Trader Profits in Commodity Futures Markets (2012)Perceived Psychological Control and Anxiety in Early Adolescents: The Mediating Role of Attributional Style (2013)Natural language analyzed with AI-based transformers predict traditional subjective well-being measures approaching the theoretical upper limits in accuracy (2022)Properties of Predictors for Autoregressive Time Series (1981)Bootstrapping prediction intervals for autoregressive models (2001)Chapter 6 Forecasting with VARMA Models (2006)Time Series Analysis Forecasting and Control. (1971)A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle (1989)Economic growth and carbon emissions: Estimation of a panel threshold model for the transition process in China (2020)Time series analysis of intensive longitudinal data in psychosomatic research: A methodological overview (2020)Deep learning in predicting cryptocurrency volatility (2022)DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS (1983)Sample Splitting and Threshold Estimation (2000)Financial Modelling with Jump Processes (2003)On a Threshold Double Autoregressive Model (2015)Threshold autoregressive models for interval-valued time series data (2018)Dynamic evolution and driving forces of carbon emission efficiency in China: New evidence based on the RBM-ML model (2023)Generalized autoregressive conditional heteroskedasticity (1986)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Econometric Analysis of Cross Section and Panel Data (2001)Asymmetric density forecasts of inflation and the Bank of England's fan chart (1999)Detecting instability in the volatility of carbon prices (2010)The model confidence set package for R (2018)Forecasting Bitcoin risk measures: A robust approach (2019)Bootstrap prediction intervals in state–space models (2009)On the Modeling of Financial Time Series (2014)GARCH Modelling of Cryptocurrencies (2017)Deep learning for decision making and the optimization of socially responsible investments and portfolio (2019)
this work references cited by second hop

References

  • 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation20,684 cited
  • 2019GARCH Models: Structure, Statistical Inference and Financial Applications431 cited
  • 1990Bootstrap Prediction Intervals for Autoregression239 cited
  • 1987Estimating Properties of Autoregressive Forecasts202 cited
  • 2014GARCH Models: Structure, Statistical Inference and Financial Applications191 cited
  • 2011Threshold models in time series analysis — 30 years on187 cited
  • 1985Bootstrap Prediction Intervals for Regression178 cited
  • 2004Bootstrap predictive inference for ARIMA processes138 cited
  • 2011On the least squares estimation of multiple-regime threshold autoregressive models128 cited
  • 1990Bootstrap prediction intervals for autoregressions115 cited
  • 2002Forecasting time series with sieve bootstrap111 cited

Cited by

  • 2014Bootstrap Joint Prediction Regions55 cited
  • 2017Robust bootstrap forecast densities for GARCH returns and volatilities31 cited
  • 2015Model-Free vs. Model-Based Volatility Prediction26 cited

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