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An adaptive forecasting approach for copper price volatility through hybrid and non-hybrid models
16 references·15 citing·43 second hop
An adaptive forecasting approach for copper price volatility through hybrid and non-hybrid models (2018)An adaptive forecasting approach for copp…Risk Everywhere: Modeling and Managing Volatility (2018)Risk Everywhere: Modeling and…“Options, Futures, and Other Derivatives” (2016)“Options, Futures, and Other …Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH (2015)Hedging emerging market stock…A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data (2014)A moving-average filter based…Using artificial neural network models in stock market index prediction (2011)Using artificial neural netwo…Volatility forecast comparison using imperfect volatility proxies (2010)Volatility forecast compariso…An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange (2010)An Adaptive Network-Based Fuz…Forecasting stock market short-term trends using a neuro-fuzzy based methodology (2009)Forecasting stock market shor…Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Surveying stock market foreca…A TSK type fuzzy rule based system for stock price prediction (2006)A TSK type fuzzy rule based s…A power GARCH examination of the gold market (2006)A power GARCH examination of …A dynamic artificial neural network model for forecasting time series events (2004)A dynamic artificial neural n…The Long-Run Behavior of Commodity Prices: Small Trends and Big Variability (2002)The Long-Run Behavior of Comm…Modified support vector machines in financial time series forecasting (2002)Modified support vector machi…Generalized autoregressive conditional heteroskedasticity (1986)Generalized autoregressive co…Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Autoregressive Conditional He…Enhancing multilayer perceptron neural network using archive-based harris hawks optimizer to predict gold prices (2023)Enhancing multilayer perceptr…What do the AI methods tell us about predicting price volatility of key natural resources: Evidence from hyperparameter tuning (2022)What do the AI methods tell u…Hodrick–Prescott filter-based hybrid ARIMA–SLFNs model with residual decomposition scheme for carbon price forecasting (2022)Hodrick–Prescott filter-based…Fuzzy Rule-Based Prediction of Gold Prices using News Affect (2022)Fuzzy Rule-Based Prediction o…Copper and Aluminium as Economically Imperfect Substitutes, Production and Price Development (2022)Copper and Aluminium as Econo…Multi-step metal prices forecasting based on a data preprocessing method and an optimized extreme learning machine by marine predators algorithm (2021)Multi-step metal prices forec…Forecasting monthly copper price: A comparative study of various machine learning-based methods (2021)Forecasting monthly copper pr…Forecasting Foreign Exchange Volatility Using Deep Learning Autoencoder‐LSTM Techniques (2021)Forecasting Foreign Exchange …Forecasting copper price by application of robust artificial intelligence techniques (2021)Forecasting copper price by a…Development of copper price from July 1959 and predicted development till the end of year 2022 (2021)Development of copper price f…A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities (2021)A Review of the Applications …Copper Price Prediction Using Support Vector Regression Technique (2020)Copper Price Prediction Using…A random walk through the trees: Forecasting copper prices using decision learning methods (2020)A random walk through the tre…Predictive analytics of the copper spot price by utilizing complex network and artificial neural network techniques (2019)Predictive analytics of the c…Multi-Objective Ensemble Model for Short-Term Price Forecasting in Corn Price Time Series (2019)Multi-Objective Ensemble Mode…Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)The distribution of realized stock return volatility (2001)Modeling and Forecasting Realized Volatility (2003)Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes (2012)The VIX, the variance premium and stock market volatility (2014)Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility (2015)Dividend yields and expected stock returns (1988)Business conditions and expected returns on stocks and bonds (1989)Common risk factors in the returns on stocks and bonds (1993)A new accuracy measure based on bounded relative error for time series forecasting (2017)Systematic analysis and review of stock market prediction techniques (2019)Stock market movement forecast: A Systematic review (2020)Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control. 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this work references cited by second hop

References

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  • 2011Using artificial neural network models in stock market index prediction787 cited
  • 2015Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH547 cited
  • 2014A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data505 cited
  • 2010An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange426 cited
  • 2006A power GARCH examination of the gold market386 cited
  • 2002Modified support vector machines in financial time series forecasting372 cited
  • 2018Risk Everywhere: Modeling and Managing Volatility357 cited
  • 2006A TSK type fuzzy rule based system for stock price prediction319 cited
  • 2009Forecasting stock market short-term trends using a neuro-fuzzy based methodology307 cited

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  • 2002The Long-Run Behavior of Commodity Prices: Small Trends and Big Variability260 cited
  • 2004A dynamic artificial neural network model for forecasting time series events257 cited
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    • 2021Multi-step metal prices forecasting based on a data preprocessing method and an optimized extreme learning machine by marine predators algorithm42 cited
    • 2021Forecasting copper price by application of robust artificial intelligence techniques41 cited
    • 2021Development of copper price from July 1959 and predicted development till the end of year 202240 cited
    • 2023Enhancing multilayer perceptron neural network using archive-based harris hawks optimizer to predict gold prices39 cited
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