On fractionally integrated autoregressive moving-average time series models with conditional heteroscedasticity

Business & Economics

• Autoregressive Fractionally Integrated Moving Average 96%
• Conditional Heteroscedasticity 88%
• Time Series Models 65%
• Autocorrelation 65%
• ARMA Model 63%
• Maximum Likelihood Estimation 57%
• Fractional Differencing 49%
• Portmanteau Test 49%
• Ergodicity 46%
• Model Checking 45%
• Higher Order Moments 43%
• Asymptotic Normality 41%
• Asymptotic Properties 38%
• Maximum Likelihood Estimator 37%
• Stationarity 34%
• Test Statistic 33%
• Unit Root 32%
• Adequacy 31%
• Hong Kong 28%
• Simulation 20%

Mathematics

• Residual Autocorrelation 100%
• Conditional Heteroscedasticity 93%
• Moving Average Model 85%
• Autoregressive Moving Average 73%
• Time Series Models 70%
• Fractional Differencing 51%
• Portmanteau Test 48%
• Higher Order Moments 41%
• ARMA Model 40%
• Unit Root 39%
• Model Checking 35%
• Ergodicity 32%
• Asymptotic Normality 29%
• Maximum Likelihood Estimation 29%
• Maximum Likelihood Estimator 27%
• Test Statistic 27%
• Asymptotic Properties 26%
• Fractional 22%
• Model 20%
• Simulation 19%
• Sufficient Conditions 15%