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Machine learning approaches to forecasting cryptocurrency volatility: Considering internal and external determinants
16 references·2 citing·50 second hopsampled
Machine learning approaches to forecasting cryptocurrency volatility: Considering internal and external determinants (2023)Machine learning approaches to forecastin…Common Risk Factors in Cryptocurrency (2022)Common Risk Factors in Crypto…Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Prediction of stock price dir…Machine learning advances for time series forecasting (2021)Machine learning advances for…Risks and Returns of Cryptocurrency (2020)Risks and Returns of Cryptocu…Deep learning for financial applications : A survey (2020)Deep learning for financial a…Bond Risk Premiums with Machine Learning (2020)Bond Risk Premiums with Machi…Bitcoin price prediction using machine learning: An approach to sample dimension engineering (2019)Bitcoin price prediction usin…A systematic review of fundamental and technical analysis of stock market predictions (2019)A systematic review of fundam…Predicting the Price of Bitcoin Using Machine Learning (2018)Predicting the Price of Bitco…Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis (2018)Long- and Short-Term Cryptocu…Genetic Algorithm-Optimized Long Short-Term Memory Network for Stock Market Prediction (2018)Genetic Algorithm-Optimized L…RETRACTED: Datestamping the Bitcoin and Ethereum bubbles (2017)RETRACTED: Datestamping the B…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…Measuring Economic Policy Uncertainty* (2016)Measuring Economic Policy Unc…Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models (2008)Volatility in crude oil futur…Generalized autoregressive conditional heteroskedasticity (1986)Generalized autoregressive co…Deep learning for financial forecasting: A review of recent trends (2025)Deep learning for financial f…Enhancing cryptocurrency market volatility forecasting with daily dynamic tuning strategy (2024)Enhancing cryptocurrency mark…Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Conditional Heteroskedasticity in Asset Returns: A New Approach (1991)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)Multivariate Simultaneous Generalized ARCH (1995)Designing a neural network for forecasting financial and economic time series (1996)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Practical Bayesian Optimization of Machine Learning Algorithms (2012)An Empirical Study on Modeling and Prediction of Bitcoin Prices With Bayesian Neural Networks Based on Blockchain Information (2017)An innovative neural network approach for stock market prediction (2018)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)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Twitter mood predicts the stock market (2011)A comprehensive evaluation of ensemble learning for stock-market prediction (2020)Cryptocurrency trading: a comprehensive survey (2022)Textual Analysis in Accounting and Finance: A Survey (2016)A novel graph convolutional feature based convolutional neural network for stock trend prediction (2020)Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions (2020)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Financial applications of machine learning: A literature review (2023)Comparing Predictive Accuracy (1994)A Simple Approximate Long-Memory Model of Realized Volatility (2008)Empirical Asset Pricing via Machine Learning (2020)Machine learning-based time series models for effective CO2 emission prediction in India (2022)Machine learning sentiment analysis, COVID-19 news and stock market reactions (2023)Data-driven stock forecasting models based on neural networks: A review (2024)Stock Prices and Social Dynamics (1984)Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin (2015)Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial Assets (2017)Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation (2018)Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic (2020)Safe haven or risky hazard? Bitcoin during the Covid-19 bear market (2020)Common risk factors in the returns on stocks and bonds (1993)Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency (1993)A Novel Cryptocurrency Price Prediction Model Using GRU, LSTM and bi-LSTM Machine Learning Algorithms (2021)Equilibrium Bitcoin Pricing (2023)The Role of Monetary Policy (1995)The Impact of Uncertainty Shocks (2009)Measuring Uncertainty (2015)COVID-19 pandemic, oil prices, stock market, geopolitical risk and policy uncertainty nexus in the US economy: Fresh evidence from the wavelet-based approach (2020)The Unprecedented Stock Market Reaction to COVID-19 (2020)Measuring Geopolitical Risk (2022)Risk, Return, and Equilibrium: Empirical Tests (1973)The Cross-Section of Expected Stock Returns (1992)Risks and Returns of Cryptocurrency (2018)Bitcoin: A safe haven asset and a winner amid political and economic uncertainties in the US? (2021)
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References

  • 1986Generalized autoregressive conditional heteroskedasticity22,329 cited
  • 2016Measuring Economic Policy Uncertainty*12,311 cited
  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 2020Risks and Returns of Cryptocurrency962 cited
  • 2018Predicting the Price of Bitcoin Using Machine Learning690 cited
  • 2017RETRACTED: Datestamping the Bitcoin and Ethereum bubbles655 cited
  • 2022Common Risk Factors in Cryptocurrency623 cited
  • 2020Deep learning for financial applications : A survey550 cited
  • 2019A systematic review of fundamental and technical analysis of stock market predictions545 cited
  • 2021Machine learning advances for time series forecasting529 cited
  • 2019Bitcoin price prediction using machine learning: An approach to sample dimension engineering420 cited
  • 2020Bond Risk Premiums with Machine Learning416 cited
  • 2018Genetic Algorithm-Optimized Long Short-Term Memory Network for Stock Market Prediction311 cited
  • 2018Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis306 cited
  • 2008Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models

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304 cited
  • 2021Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process292 cited
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    • 2025Deep learning for financial forecasting: A review of recent trends61 cited
    • 2024Enhancing cryptocurrency market volatility forecasting with daily dynamic tuning strategy25 cited