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Cryptocurrency Trading Using Machine Learning
16 references·4 citing·58 second hopsampled
Cryptocurrency Trading Using Machine Learning (2020)Cryptocurrency Trading Using Machine Lear…Sentiment-Induced Bubbles in the Cryptocurrency Market (2019)Sentiment-Induced Bubbles in …Momentum trading in cryptocurrencies: Short-term returns and diversification benefits (2019)Momentum trading in cryptocur…Market risk and Bitcoin returns (2019)Market risk and Bitcoin retur…Literature review: Machine learning techniques applied to financial market prediction (2019)Literature review: Machine le…Large data sets and machine learning: Applications to statistical arbitrage (2019)Large data sets and machine l…Cryptocurrencies and momentum (2019)Cryptocurrencies and momentumTrading and Arbitrage in Cryptocurrency Markets (2018)Trading and Arbitrage in Cryp…Reinforcement learning applied to Forex trading (2018)Reinforcement learning applie…Price discovery of cryptocurrencies: Bitcoin and beyond (2018)Price discovery of cryptocurr…Liquidity uncertainty and Bitcoin’s market microstructure (2018)Liquidity uncertainty and Bit…Forecasting cryptocurrencies under model and parameter instability (2018)Forecasting cryptocurrencies …Cryptocurrency forecasting with deep learning chaotic neural networks (2018)Cryptocurrency forecasting wi…Asymmetric Volatility in Cryptocurrencies (2018)Asymmetric Volatility in Cryp…A new look at Cryptocurrencies (2017)A new look at CryptocurrenciesFX trading via recurrent reinforcement learning (2003)FX trading via recurrent rein…Learning to trade via direct reinforcement (2001)Learning to trade via direct …The great crypto crash in September 2018: why did the cryptocurrency market collapse? (2023)The great crypto crash in Sep…Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning (2022)Can investors’ informed tradi…Applying Artificial Intelligence in Cryptocurrency Markets: A Survey (2022)Applying Artificial Intellige…Cryptocurrency Trading: A Comprehensive Survey (2020)Cryptocurrency Trading: A Com…Portfolio Selection: Efficient Diversification of Investments (1959)Optimum consumption and portfolio rules in a continuous-time model (1971)Option pricing: A simplified approach (1979)A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem (2017)Cryptocurrency portfolio management with deep reinforcement learning (2017)DeepLOB: Deep Convolutional Neural Networks for Limit Order Books (2019)Fractional Differencing (1981)Modelling Financial Time Series (2007)Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin (2015)Regime changes in Bitcoin GARCH volatility dynamics (2018)Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios (2019)Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis (2019)Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test (1988)A test for independence based on the correlation dimension (1996)Illiquidity and stock returns: cross-section and time-series effects (2002)The Role of Bitcoin in Well Diversified Portfolios: A Comparative Global Study (2018)Information interdependence among energy, cryptocurrency and major commodity markets (2019)Continuous Auctions and Insider Trading (1985)Noise Trader Risk in Financial Markets (1990)The Limits of Arbitrage (1995)Should Investors Include Bitcoin in Their Portfolios? A Portfolio Theory Approach (2018)Common Risk Factors in Cryptocurrency (2022)Cryptocurrency trading: a comprehensive survey (2022)Bid, ask and transaction prices in a specialist market with heterogeneously informed traders (1985)On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks (1993)Liquidity, Information, and Infrequently Traded Stocks (1996)High frequency volatility co-movements in cryptocurrency markets (2019)Tail dependence between bitcoin and green financial assets (2021)Sentiment analysis on social media for stock movement prediction (2015)Volatility estimation for Bitcoin: A comparison of GARCH models (2017)Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance (2018)Price Movement Prediction of Cryptocurrencies Using Sentiment Analysis and Machine Learning (2019)Forecasting and trading cryptocurrencies with machine learning under changing market conditions (2021)Quantile connectedness in the cryptocurrency market (2021)Comparing Predictive Accuracy (1994)Comparing Predictive Accuracy (1995)Predictive regressions (1999)Forecasting the volatility of Bitcoin: The importance of jumps and structural breaks (2019)Intelligent forecasting with machine learning trading systems in chaotic intraday Bitcoin market (2020)Which factors drive Bitcoin volatility: Macroeconomic, technical, or both? (2022)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Generalized autoregressive conditional heteroskedasticity (1986)Theory building with big data-driven research – Moving away from the “What” towards the “Why” (2020)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Machine learning techniques and data for stock market forecasting: A literature review (2022)Evidence of Predictable Behavior of Security Returns (1990)Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency (1993)Value and Momentum Everywhere (2013)Does investor sentiment on social media provide robust information for Bitcoin returns predictability? (2020)Time-frequency co-movement of cryptocurrency return and volatility: Evidence from wavelet coherence analysis (2020)Speculation and lottery-like demand in cryptocurrency markets (2021)Common risk factors in the returns on stocks and bonds (1993)On Persistence in Mutual Fund Performance (1997)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting (2019)Forex exchange rate forecasting using deep recurrent neural networks (2020)Forecasting mid-price movement of Bitcoin futures using machine learning (2021)
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References

  • 2018Trading and Arbitrage in Cryptocurrency Markets903 cited
  • 2019Literature review: Machine learning techniques applied to financial market prediction560 cited
  • 2001Learning to trade via direct reinforcement548 cited
  • 2018Cryptocurrency forecasting with deep learning chaotic neural networks376 cited
  • 2018Asymmetric Volatility in Cryptocurrencies372 cited
  • 2017A new look at Cryptocurrencies344 cited
  • 2018Price discovery of cryptocurrencies: Bitcoin and beyond326 cited
  • 2018Forecasting cryptocurrencies under model and parameter instability153 cited
  • 2019Cryptocurrencies and momentum139 cited
  • 2019Large data sets and machine learning: Applications to statistical arbitrage118 cited
  • 2018Reinforcement learning applied to Forex trading114 cited
  • 2019Market risk and Bitcoin returns92 cited
  • 2019Sentiment-Induced Bubbles in the Cryptocurrency Market89 cited
  • 2019Momentum trading in cryptocurrencies: Short-term returns and diversification benefits74 cited
  • 2003FX trading via recurrent reinforcement learning66 cited
  • 2018Liquidity uncertainty and Bitcoin’s market microstructure

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Cited by

  • 2022Applying Artificial Intelligence in Cryptocurrency Markets: A Survey42 cited
  • 2020Cryptocurrency Trading: A Comprehensive Survey30 cited
  • 2023The great crypto crash in September 2018: why did the cryptocurrency market collapse?29 cited
  • 2022Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning27 cited