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Investigating the Problem of Cryptocurrency Price Prediction: A Deep Learning Approach
6 references·6 citing·43 second hop
Investigating the Problem of Cryptocurrency Price Prediction: A Deep Learning Approach (2020)Investigating the Problem of Cryptocurren…A CNN–LSTM model for gold price time-series forecasting (2020)A CNN–LSTM model for gold pri…Trend Prediction Classification for High Frequency Bitcoin Time Series with Deep Learning (2019)Trend Prediction Classificati…A Comparative Study of Bitcoin Price Prediction Using Deep Learning (2019)A Comparative Study of Bitcoi…Predicting bitcoin returns using high-dimensional technical indicators (2018)Predicting bitcoin returns us…A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)A Comparison of ARIMA and LST…Introduction to time series analysis and forecasting (2008)Introduction to time series a…Forecasting Bitcoin returns using machine learning algorithms: impact of investor sentiment (2023)Forecasting Bitcoin returns u…A survey of deep learning applications in cryptocurrency (2023)A survey of deep learning app…Investors Behavioural Intention of Cryptocurrency Adoption – A Review based Research Agenda (2022)Investors Behavioural Intenti…Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic (2022)Effect of twitter investor en…Cryptocurrency Price Prediction with Convolutional Neural Network and Stacked Gated Recurrent Unit (2022)Cryptocurrency Price Predicti…RMSE calculation of LSTM models for predicting prices of different cryptocurrencies (2021)RMSE calculation of LSTM mode…Simple Technical Trading Rules and the Stochastic Properties of Stock Returns (1992)Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation (2000)Corporate Governance and Blockchains (2016)Crude oil price and cryptocurrencies: Evidence of volatility connectedness and hedging strategy (2020)Short-term bitcoin market prediction via machine learning (2021)Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction (2022)Forecasting principles and practiceTime Series Analysis: Forecasting and Control (1977)Deep learning with long short-term memory networks for financial market predictions (2017)Stock price prediction using deep learning and frequency decomposition (2020)Applications of deep learning in stock market prediction: Recent progress (2021)A Review of ARIMA vs. Machine Learning Approaches for Time Series Forecasting in Data Driven Networks (2023)Some stylized facts of the Bitcoin market (2017)An application of extreme value theory to cryptocurrencies (2018)DeepLOB: Deep Convolutional Neural Networks for Limit Order Books (2019)A Labeling Method for Financial Time Series Prediction Based on Trends (2020)Cryptocurrencies and Artificial Intelligence: Challenges and Opportunities (2020)LSTM-ReGAT: A network-centric approach for cryptocurrency price trend prediction (2023)The Proof and Measurement of Association between Two Things (1904)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)CLSTM: Deep Feature-Based Speech Emotion Recognition Using the Hierarchical ConvLSTM Network (2020)Ensemble Deep Learning Models for Forecasting Cryptocurrency Time-Series (2020)Cryptocurrency price prediction using traditional statistical and machine‐learning techniques: A survey (2021)Is gold a safe haven? International evidence (2010)A CNN-BiLSTM-AM method for stock price prediction (2020)Cryptocurrency trading: a comprehensive survey (2022)Introduction to Time Series and Forecasting (2002)Introduction to Time Series and Forecasting (2016)Predicting the Price of Bitcoin Using Machine Learning (2018)A Deep Learning-based Cryptocurrency Price Prediction Scheme for Financial Institutions (2020)Forecasting and trading cryptocurrencies with machine learning under changing market conditions (2021)Evaluating the Performance of Metaheuristic Based Artificial Neural Networks for Cryptocurrency Forecasting (2023)1D-CapsNet-LSTM: A deep learning-based model for multi-step stock index forecasting (2024)MFB: A Generalized Multimodal Fusion Approach for Bitcoin Price Prediction Using Time-Lagged Sentiment and Indicator Features (2024)Better to give than to receive: Predictive directional measurement of volatility spillovers (2011)Does twitter predict Bitcoin? (2018)The predictive power of public Twitter sentiment for forecasting cryptocurrency prices (2020)Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Deep learning and NLP in cryptocurrency forecasting: Integrating financial, blockchain, and social media data (2025)A comparison of three different approaches to tourist arrival forecasting (2003)Evaluation of statistical and machine learning models for time series prediction: Identifying the state-of-the-art and the best conditions for the use of each model (2019)Bayesian optimization based dynamic ensemble for time series forecasting (2022)
this work references cited by second hop

References

  • 2008Introduction to time series analysis and forecasting1,405 cited
  • 2018A Comparison of ARIMA and LSTM in Forecasting Time Series1,382 cited
  • 2020A CNN–LSTM model for gold price time-series forecasting869 cited
  • 2019A Comparative Study of Bitcoin Price Prediction Using Deep Learning213 cited
  • 2018Predicting bitcoin returns using high-dimensional technical indicators177 cited
  • 2019Trend Prediction Classification for High Frequency Bitcoin Time Series with Deep Learning84 cited

Cited by

  • 2023A survey of deep learning applications in cryptocurrency53 cited
  • 2022Cryptocurrency Price Prediction with Convolutional Neural Network and Stacked Gated Recurrent Unit46 cited
  • 2022Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic31 cited
  • 2021RMSE calculation of LSTM models for predicting prices of different cryptocurrencies31 cited
  • 2023Forecasting Bitcoin returns using machine learning algorithms: impact of investor sentiment27 cited
  • 2022Investors Behavioural Intention of Cryptocurrency Adoption – A Review based Research Agenda16 cited

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