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A novel hybrid model on the prediction of time series and its application for the gold price analysis and forecasting
10 references·1 citing·53 second hop
A novel hybrid model on the prediction of time series and its application for the gold price analysis and forecasting (2019)A novel hybrid model on the prediction of…Dynamic linkages among the gold market, US dollar and crude oil market (2017)Dynamic linkages among the go…Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis (2017)Crude oil price analysis and …Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model (2016)Investigation of market effic…A variational mode decompoisition approach for analysis and forecasting of economic and financial time series (2016)A variational mode decompoisi…Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling (2011)Crude oil price forecasting: …An overview of global gold market and gold price forecasting (2010)An overview of global gold ma…Forecasting Gold Prices Using Multiple Linear Regression Method (2009)Forecasting Gold Prices Using…Forecasting gold price changes: Rolling and recursive neural network models (2008)Forecasting gold price change…Forecasting S&P and gold futures prices: An application of neural networks (1993)Forecasting S&P and gold futu…The inflation rate of the price of gold, expected prices and interest rates (1987)The inflation rate of the pri…Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine (2021)Optimal hybrid framework for …THE PERFORMANCE OF MUTUAL FUNDS IN THE PERIOD 1945–1964 (1968)Economic prediction using neural networks: the case of IBM daily stock returns (1988)Measuring the Strangeness of Gold and Silver Rates of Return (1989)Applications of Artificial Neural Networks in Financial Economics: A Survey (2010)Stock market value prediction using neural networks (2010)Forecasting stock index returns using ARIMA-SVM, ARIMA-ANN, and ARIMA-random forest hybrid models (2014)Designing a neural network for forecasting financial and economic time series (1996)Forecasting with artificial neural networks: (1998)Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Wavelet-based evidence of the impact of oil prices on stock returns (2013)A novel hybrid method for crude oil price forecasting (2015)Improved EEMD-based crude oil price forecasting using LSTM networks (2018)A Simple Nonparametric Test of Predictive Performance (1992)Predicting U.S. Recessions: Financial Variables as Leading Indicators (1998)Forecasting Copper Prices Using Hybrid Adaptive Neuro-Fuzzy Inference System and Genetic Algorithms (2019)Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility (2019)The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning (2021)Output Fluctuations and Gradual Price Adjustment (1981)Expectations and the Structure of Share Prices (1982)Price Inertia and Policy Ineffectiveness in the United States, 1890-1980 (1982)Gold as an inflation hedge in a time-varying coefficient framework (2012)Relationship between gold and stock markets during the global financial crisis: Evidence from nonlinear causality tests (2015)Is gold a hedge against inflation? New evidence from a nonlinear ARDL approach (2016)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)The Stock Market: Theories and Evidence. (1974)Modeling Gold Price via Artificial Neural Network (2014)Forecasting the price of gold using dynamic model averaging (2015)Bayesian analysis of dynamic linkages among gold price, stock prices, exchange rate and interest rate in Pakistan (2019)A new approach for crude oil price analysis based on Empirical Mode Decomposition (2007)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)A new financial data forecasting model using genetic algorithm and long short-term memory network (2020)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Another look at measures of forecast accuracy (2006)Analysis of temporal pattern, causal interaction and predictive modeling of financial markets using nonlinear dynamics, econometric models and machine learning algorithms (2019)Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model (2022)Forecasting price in a new hybrid neural network model with machine learning (2024)ARIMA forecasting of primary energy demand by fuel in Turkey (2006)Monthly crude oil spot price forecasting using variational mode decomposition (2019)The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm (2020)Forecasting crude oil prices based on variational mode decomposition and random sparse Bayesian learning (2021)A long memory property of stock market returns and a new model (1993)Gaussian Semiparametric Estimation of Long Range Dependence (1995)Dynamic Conditional Correlation (2002)Period specific volatility spillover based connectedness between oil and other commodity prices and their portfolio implications (2019)Does economic policy uncertainty drive the dynamic connectedness between oil price shocks and gold price? (2020)Risk spillover effects from global crude oil market to China’s commodity sectors (2020)
this work references cited by second hop

References

  • 2010An overview of global gold market and gold price forecasting372 cited
  • 2011Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling282 cited
  • 2016A variational mode decompoisition approach for analysis and forecasting of economic and financial time series214 cited
  • 1993Forecasting S&P and gold futures prices: An application of neural networks175 cited
  • 2009Forecasting Gold Prices Using Multiple Linear Regression Method129 cited
  • 2017Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis109 cited
  • 2017Dynamic linkages among the gold market, US dollar and crude oil market109 cited
  • 2016Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model108 cited
  • 2008Forecasting gold price changes: Rolling and recursive neural network models105 cited
  • 1987The inflation rate of the price of gold, expected prices and interest rates77 cited

Cited by

  • 2021Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine53 cited

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