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Forecasting Bitcoin with technical analysis: A not-so-random forest?
16 references·2 citing·41 second hop
Forecasting Bitcoin with technical analysis: A not-so-random forest? (2021)Forecasting Bitcoin with technical analys…Empirical Asset Pricing via Machine Learning (2020)Empirical Asset Pricing via M…Deep learning with long short-term memory networks for financial market predictions (2017)Deep learning with long short…Can volume predict Bitcoin returns and volatility? A quantiles-based approach (2017)Can volume predict Bitcoin re…Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Deep neural networks, gradien…What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis (2015)What Are the Main Drivers of …Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin (2015)Speculative bubbles in Bitcoi…Bitcoin, gold and the dollar – A GARCH volatility analysis (2015)Bitcoin, gold and the dollar …Forecasting the Equity Risk Premium: The Role of Technical Indicators (2014)Forecasting the Equity Risk P…Why Has U.S. Inflation Become Harder to Forecast? (2007)Why Has U.S. Inflation Become…The Adaptive Markets Hypothesis (2004)The Adaptive Markets Hypothes…Neural network forecasting for seasonal and trend time series (2003)Neural network forecasting fo…Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis (2002)Further Evidence on the Great…Comparing Predictive Accuracy (1995)Comparing Predictive AccuracyComparing Predictive Accuracy (1994)Comparing Predictive AccuracyThe use of technical analysis in the foreign exchange market (1992)The use of technical analysis…Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis (1992)Further Evidence on the Great…Major Issues in High-Frequency Financial Data Analysis: A Survey of Solutions (2025)Major Issues in High-Frequenc…MLP-based Learnable Window Size for Bitcoin price prediction (2022)MLP-based Learnable Window Si…A test for independence based on the correlation dimension (1996)The Econometrics of Financial Markets (1997)The Econometrics of Financial Markets (2012)The Inefficiency of Bitcoin (2016)Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial Assets (2017)Volatility estimation for Bitcoin: A comparison of GARCH models (2017)Distribution of the Estimators for Autoregressive Time Series with a Unit Root (1979)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis (1989)The saving and investment nexus for China: evidence from cointegration tests (2005)Introductory Econometrics for Finance (2008)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)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Tests for Parameter Instability and Structural Change With Unknown Change Point (1993)Has the Business Cycle Changed and Why? (2002)Risk Matters: The Real Effects of Volatility Shocks (2011)Risk Premiums in Dynamic Term Structure Models with Unspanned Macro Risks (2013)Government Spending Multipliers in Good Times and in Bad: Evidence from US Historical Data (2017)Prospect Theory: An Analysis of Decision under Risk (1979)An Evolutionary Theory of Economic Change. (1983)Prospect theory: An analysis of decision under risk (1988)Institutional Investors and the Informational Efficiency of Prices (2009)Sustainable Development and Financial Markets (2015)Machine learning techniques and data for stock market forecasting: A literature review (2022)Residual-based tests for cointegration in models with regime shifts (1996)Economic growth, energy consumption, financial development, international trade and CO2 emissions in Indonesia (2013)The Quarterly Journal of Economics (2024)Common risk factors in the returns on stocks and bonds (1993)A five-factor asset pricing model (2014)Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis (2021)Machine learning advances for time series forecasting (2021)Machine learning in the Chinese stock market (2021)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Testing the equality of prediction mean squared errors (1997)Consumption, Aggregate Wealth, and Expected Stock Returns (2001)
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References

  • 2002Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis5,745 cited
  • 1994Comparing Predictive Accuracy5,495 cited
  • 1995Comparing Predictive Accuracy5,214 cited
  • 1992Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis3,283 cited
  • 2017Deep learning with long short-term memory networks for financial market predictions2,827 cited
  • 2020Empirical Asset Pricing via Machine Learning2,528 cited
  • 2007Why Has U.S. Inflation Become Harder to Forecast?1,719 cited
  • 2004The Adaptive Markets Hypothesis1,708 cited
  • 2015Bitcoin, gold and the dollar – A GARCH volatility analysis1,552 cited
  • 2015Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin1,386 cited
  • 1992The use of technical analysis in the foreign exchange market1,071 cited
  • 2014Forecasting the Equity Risk Premium: The Role of Technical Indicators1,001 cited
  • 2015What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis989 cited
  • 2003Neural network forecasting for seasonal and trend time series987 cited
  • 2016Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500

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749 cited
  • 2017Can volume predict Bitcoin returns and volatility? A quantiles-based approach718 cited
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    • 2022MLP-based Learnable Window Size for Bitcoin price prediction62 cited
    • 2025Major Issues in High-Frequency Financial Data Analysis: A Survey of Solutions28 cited