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Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility
16 references·5 citing·53 second hopsampled
Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility (2019)Improving multilayer perceptron neural ne…Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm (2019)Forecasting gold price fluctu…A hybrid volatility forecasting framework integrating GARCH, artificial neural network, technical analysis and principal components analysis (2018)A hybrid volatility forecasti…Does One Belt One Road initiative promote Chinese overseas direct investment? (2017)Does One Belt One Road initia…Forecasting the COMEX copper spot price by means of neural networks and ARIMA models (2015)Forecasting the COMEX copper …Speculators, commodities and cross-market linkages (2013)Speculators, commodities and …An improved wavelet–ARIMA approach for forecasting metal prices (2013)An improved wavelet–ARIMA app…Can Exchange Rates Forecast Commodity Prices? * (2010)Can Exchange Rates Forecast C…An overview of global gold market and gold price forecasting (2010)An overview of global gold ma…A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)A novel hybridization of arti…Global economic activity and crude oil prices: A cointegration analysis (2009)Global economic activity and …An artificial neural network (p,d,q) model for timeseries forecasting (2009)An artificial neural network …Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries (2007)Oil prices, inflation and int…An investigation and comparison of artificial neural network and time series models for Chinese food grain price forecasting (2007)An investigation and comparis…Oil prices and economic activity: An asymmetric cointegration approach (2006)Oil prices and economic activ…ARIMA forecasting of primary energy demand by fuel in Turkey (2006)ARIMA forecasting of primary …Using neural networks for forecasting volatility of S&P 500 Index futures prices (2003)Using neural networks for for…Chinese energy security index price forecasting through the neural network (2025)Chinese energy security index…Forecasting monthly copper price: A comparative study of various machine learning-based methods (2021)Forecasting monthly copper pr…Deep learning models for forecasting aviation demand time series (2021)Deep learning models for fore…A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities (2021)A Review of the Applications …Forecasting the monthly iron ore import of China using a model combining empirical mode decomposition, non-linear autoregressive neural network, and autoregressive integrated moving average (2020)Forecasting the monthly iron …Statistical analysis of cointegration vectors (1988)MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY (1990)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)On the influence of oil prices on economic activity and other macroeconomic and financial variables* (2008)Cross-country differences in the effects of oil shocks (2011)OIL PRICES AND STOCK MARKETS IN GCC COUNTRIES: EMPIRICAL EVIDENCE FROM PANEL ANALYSIS (2011)Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models (1991)Understanding Crude Oil Prices (2008)Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market (2009)What drives natural gas prices? — A structural VAR approach (2014)Extreme risk spillovers between crude oil and stock markets (2015)Nonlinear effects of climate policy uncertainty and financial speculation on the global prices of oil and gas (2022)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)Time series forecasting using a hybrid ARIMA and neural network model (2003)A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data (2014)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)An optimized model using LSTM network for demand forecasting (2020)Energy consumption and GDP: causality relationship in G-7 countries and emerging markets (2002)Forecasting time series using a methodology based on autoregressive integrated moving average and genetic programming (2010)Modeling and forecasting of Turkey’s energy consumption using socio-economic and demographic variables (2010)Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition (2019)Forecasting with artificial neural networks: (1998)Using artificial neural network models in stock market index prediction (2011)Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)Recurrent neural network and a hybrid model for prediction of stock returns (2014)The Behavior of Stock-Market Prices (1965)The Pricing of Options and Corporate Liabilities (1973)Theory of Rational Option Pricing (1973)Dynamics of global oil prices, exchange rate and precious metal prices in India (2012)Gold price volatility: A forecasting approach using the Artificial Neural Network–GARCH model (2015)Hedging oil price risk with gold during COVID-19 pandemic (2020)Expectations and Exchange Rate Dynamics (1976)Tests for Parameter Instability and Structural Change With Unknown Change Point (1993)Comparing Predictive Accuracy (1994)Oil price fluctuations and U.S. dollar exchange rates (2009)Should Macroeconomic Forecasters Use Daily Financial Data and How? (2013)Forecasting gold price with the XGBoost algorithm and SHAP interaction values (2021)Multinational Enterprises and the Global Economy. (1995)Firm size and the gains from acquisitions (2004)The determinants of Chinese outward foreign direct investment (2007)Testing EKC hypothesis with energy and sustainable development challenges: a fresh evidence from belt and road initiative economies (2018)The dynamic links between CO2 emissions, energy consumption and economic development in the countries along “the Belt and Road” (2018)Nexus between green logistic operations and triple bottom line: evidence from infrastructure-led Chinese outward foreign direct investment in Belt and Road host countries (2021)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Crude oil and stock markets: Stability, instability, and bubbles (2009)Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade (2010)Dynamic spillovers of oil price shocks and economic policy uncertainty (2014)Dynamic Conditional Correlation (2002)No Contagion, Only Interdependence: Measuring Stock Market Comovements (2002)Investor Flows and the 2008 Boom/Bust in Oil Prices (2013)The Role of Speculation in Oil Markets: What Have We Learned So Far? (2013)A Model of Financialization of Commodities (2016)
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References

  • 2010A novel hybridization of artificial neural networks and ARIMA models for time series forecasting825 cited
  • 2009An artificial neural network (p,d,q) model for timeseries forecasting785 cited
  • 2007Oil prices, inflation and interest rates in a structural cointegrated VAR model for the G-7 countries650 cited
  • 2006ARIMA forecasting of primary energy demand by fuel in Turkey622 cited
  • 2013Speculators, commodities and cross-market linkages617 cited
  • 2010Can Exchange Rates Forecast Commodity Prices? *597 cited
  • 2017Does One Belt One Road initiative promote Chinese overseas direct investment?562 cited
  • 2006Oil prices and economic activity: An asymmetric cointegration approach401 cited
  • 2010An overview of global gold market and gold price forecasting372 cited
  • 2009Global economic activity and crude oil prices: A cointegration analysis230 cited
  • 2018A hybrid volatility forecasting framework integrating GARCH, artificial neural network, technical analysis and principal components analysis226 cited
  • 2007An investigation and comparison of artificial neural network and time series models for Chinese food grain price forecasting198 cited
  • 2003Using neural networks for forecasting volatility of S&P 500 Index futures prices195 cited
  • 2019Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm

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189 cited
  • 2013An improved wavelet–ARIMA approach for forecasting metal prices175 cited
  • 2015Forecasting the COMEX copper spot price by means of neural networks and ARIMA models151 cited
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    • 2021Deep learning models for forecasting aviation demand time series68 cited
    • 2021Forecasting monthly copper price: A comparative study of various machine learning-based methods57 cited
    • 2021A Review of the Applications of Genetic Algorithms to Forecasting Prices of Commodities55 cited