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Bitcoin Price Prediction Based on Other Cryptocurrencies Using Machine Learning and Time Series Analysis
16 references·0 citing·45 second hop
Bitcoin Price Prediction Based on Other Cryptocurrencies Using Machine Learning and Time Series Analysis (2020)Bitcoin Price Prediction Based on Other C…Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm (2019)Forecasting gold price fluctu…Bitcoin price forecasting with neuro-fuzzy techniques (2019)Bitcoin price forecasting wit…Predicting the direction, maximum, minimum and closing prices of daily Bitcoin exchange rate using machine learning techniques (2018)Predicting the direction, max…Herding behaviour in cryptocurrencies (2018)Herding behaviour in cryptocu…Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models (2018)Forecasting the volatility of…Financial time series forecasting model based on CEEMDAN and LSTM (2018)Financial time series forecas…Dynamic connectedness and integration in cryptocurrency markets (2018)Dynamic connectedness and int…Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018)Algorithmic financial trading…Forecasting financial time series volatility using Particle Swarm Optimization trained Quantile Regression Neural Network (2017)Forecasting financial time se…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…Maximum and minimum stock price forecasting of Brazilian power distribution companies based on artificial neural networks (2015)Maximum and minimum stock pri…Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500 (2013)Testing for Multiple Bubbles:…A novel hybridization of artificial neural networks and ARIMA models for time series forecasting (2010)A novel hybridization of arti…An artificial neural network (p,d,q) model for timeseries forecasting (2009)An artificial neural network …ARIMA forecasting of primary energy demand by fuel in Turkey (2006)ARIMA forecasting of primary …An assessment of time series methods in metal price forecasting (2005)An assessment of time series …Book Review: 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)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Energy consumption and GDP: causality relationship in G-7 countries and emerging markets (2002)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)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)On Persistence in Mutual Fund Performance (1997)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)A CNN-LSTM-Based Model to Forecast Stock Prices (2020)A Survey of Forex and Stock Price Prediction Using Deep Learning (2021)Time Series Analysis, Forecasting and Control. 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(2019)Application of support vector machines in financial time series forecasting (2001)Introduction to Time Series and Forecasting (2002)Forecasting Volatility in Financial Markets: A Review (2003)Stock price prediction using deep learning and frequency decomposition (2020)Carbon price forecasting based on CEEMDAN and LSTM (2022)Impulse response analysis in nonlinear multivariate models (1996)Generalized impulse response analysis in linear multivariate models (1998)Better to give than to receive: Predictive directional measurement of volatility spillovers (2011)Stock markets and the COVID-19 fractal contagion effects (2020)Quantile connectedness in the cryptocurrency market (2021)Cryptocurrency trading: a comprehensive survey (2022)Datestamping the Bitcoin and Ethereum Bubbles (2017)The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks (2018)Cryptocurrency reaction to FOMC Announcements: Evidence of heterogeneity based on blockchain stack position (2019)
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References

  • 2017Deep learning with long short-term memory networks for financial market predictions3,010 cited
  • 2010A novel hybridization of artificial neural networks and ARIMA models for time series forecasting849 cited
  • 2018Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models807 cited
  • 2009An artificial neural network (p,d,q) model for timeseries forecasting797 cited
  • 2018Financial time series forecasting model based on CEEMDAN and LSTM718 cited
  • 2018Dynamic connectedness and integration in cryptocurrency markets640 cited
  • 2006ARIMA forecasting of primary energy demand by fuel in Turkey626 cited
  • 2018Herding behaviour in cryptocurrencies547 cited
  • 2018Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach448 cited
  • 2013Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500257 cited
  • 2018Predicting the direction, maximum, minimum and closing prices of daily Bitcoin exchange rate using machine learning techniques253 cited
  • 2019Bitcoin price forecasting with neuro-fuzzy techniques229 cited
  • 2017Forecasting financial time series volatility using Particle Swarm Optimization trained Quantile Regression Neural Network189 cited
  • 2019Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm

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189 cited
  • 2015Maximum and minimum stock price forecasting of Brazilian power distribution companies based on artificial neural networks165 cited
  • 2005An assessment of time series methods in metal price forecasting121 cited
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