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DAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINES
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DAILY CRUDE OIL PRICE FORECASTING MODEL USING ARIMA, GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTIC AND SUPPORT VECTOR MACHINES (2014)DAILY CRUDE OIL PRICE FORECASTING MODEL U…A nonparametric GARCH model of crude oil price return volatility (2011)A nonparametric GARCH model o…Time series analysis forecasting and control (2009)Time series analysis forecast…Extreme Value Theory and Value at Risk: Application to oil market (2009)Extreme Value Theory and Valu…Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models (2008)Volatility in crude oil futur…Modeling and forecasting petroleum futures volatility (2006)Modeling and forecasting petr…Forecasting stock market movement direction with support vector machine (2004)Forecasting stock market move…Financial time series forecasting using support vector machines (2003)Financial time series forecas…Modified support vector machines in financial time series forecasting (2002)Modified support vector machi…Application of support vector machines in financial time series forecasting (2001)Application of support vector…A semiparametric approach to short-term oil price forecasting (2001)A semiparametric approach to …Oil price shocks and stock market activity (1999)Oil price shocks and stock ma…ARCH modeling in finance (1992)ARCH modeling in financeGeneralized autoregressive conditional heteroskedasticity (1986)Generalized autoregressive co…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Autoregressive Conditional He…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecas…Deep learning systems for forecasting the prices of crude oil and precious metals (2024)Deep learning systems for for…The Use of GARCH Autoregressive Models in Estimating and Forecasting the Crude Oil Volatility (2022)The Use of GARCH Autoregressi…A novel dynamic time-delay grey model of energy prices and its application in crude oil price forecasting (2022)A novel dynamic time-delay gr…Forecasting Crude Oil Price Using Event Extraction (2021)Forecasting Crude Oil Price U…An option pricing model based on a renewable energy price index (2021)An option pricing model based…A novel hybrid approach to forecast crude oil futures using intraday data (2020)A novel hybrid approach to fo…Forecasting the WTI crude oil price by a hybrid-refined method (2018)Forecasting the WTI crude oil…Forecasting Crude Oil Prices Using Ensemble Empirical Mode Decomposition and Sparse Bayesian Learning (2018)Forecasting Crude Oil Prices …Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach (2015)Selecting dynamic moving aver…Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model (2014)Daily Crude Oil Price Forecas…The Pricing of Options and Corporate Liabilities (1973)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)Multivariate Simultaneous Generalized ARCH (1995)Dynamic Conditional Correlation (2002)Forecasting with artificial neural networks: (1998)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock market's price movement prediction with LSTM neural networks (2017)The Cross-Section of Expected Stock Returns (1992)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Testing for a Unit Root in Time Series Regression (1988)Oil price shocks and stock markets in the U.S. and 13 European countries (2008)THE IMPACT OF OIL PRICE SHOCKS ON THE U.S. STOCK MARKET* (2009)Oil prices, US stock return, and the dependence between their quantiles (2015)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)Econometric Analysis of Cross Section and Panel Data (2001)Support vector machine with adaptive parameters in financial time series forecasting (2003)Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2009)The predictive power of online chatter (2005)Quantile regression for dynamic panel data with fixed effects (2011)Tourism demand forecasting: A deep learning approach (2019)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Exponential smoothing: The state of the art (1985)Using daily stock returns (1985)
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References

  • 1986Generalized autoregressive conditional heteroskedasticity22,329 cited
  • 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation20,684 cited
  • 1977Time Series Analysis: Forecasting and Control19,200 cited
  • 1977Time Series Analysis: Forecasting and Control6,446 cited
  • 1992ARCH modeling in finance4,288 cited
  • 2009Time series analysis forecasting and control2,585 cited
  • 1999Oil price shocks and stock market activity1,798 cited
  • 2003Financial time series forecasting using support vector machines1,734 cited
  • 2001Application of support vector machines in financial time series forecasting1,270 cited
  • 2004Forecasting stock market movement direction with support vector machine1,119 cited
  • 2006Modeling and forecasting petroleum futures volatility479 cited
  • 2002Modified support vector machines in financial time series forecasting372 cited
  • 2008Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models304 cited
  • 2001A semiparametric approach to short-term oil price forecasting253 cited
  • 2009Extreme Value Theory and Value at Risk: Application to oil market

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213 cited
  • 2011A nonparametric GARCH model of crude oil price return volatility183 cited
  • Cited by

    • 2018Forecasting the WTI crude oil price by a hybrid-refined method97 cited
    • 2024Deep learning systems for forecasting the prices of crude oil and precious metals68 cited
    • 2020A novel hybrid approach to forecast crude oil futures using intraday data60 cited
    • 2022A novel dynamic time-delay grey model of energy prices and its application in crude oil price forecasting54 cited
    • 2014Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model53 cited
    • 2018Forecasting Crude Oil Prices Using Ensemble Empirical Mode Decomposition and Sparse Bayesian Learning50 cited
    • 2021Forecasting Crude Oil Price Using Event Extraction41 cited
    • 2015Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach37 cited
    • 2021An option pricing model based on a renewable energy price index35 cited
    • 2022The Use of GARCH Autoregressive Models in Estimating and Forecasting the Crude Oil Volatility20 cited