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Carbon trading and COVID-19: a hybrid machine learning approach for international carbon price forecasting
16 references·0 citing·44 second hop
Carbon trading and COVID-19: a hybrid machine learning approach for international carbon price forecasting (2023)Carbon trading and COVID-19: a hybrid mac…The impact of the Ukraine–Russia war on world stock market returns (2022)The impact of the Ukraine–Rus…Heterogeneous impacts of wars on global equity markets: Evidence from the invasion of Ukraine (2022)Heterogeneous impacts of wars…Machine learning in the Chinese stock market (2021)Machine learning in the Chine…COVID–19 media coverage and ESG leader indices (2021)COVID–19 media coverage and E…Carbon emissions determinants and forecasting: Evidence from G6 countries (2021)Carbon emissions determinants…Assessing the impact of emissions trading scheme on low-carbon technological innovation: Evidence from China (2021)Assessing the impact of emiss…Financial contagion during COVID–19 crisis (2020)Financial contagion during CO…Event study on the reaction of the developed and emerging stock markets to the 2019-nCoV outbreak (2020)Event study on the reaction o…COVID-19 and the march 2020 stock market crash. Evidence from S&P1500 (2020)COVID-19 and the march 2020 s…Carbon trading volume and price forecasting in China using multiple machine learning models (2019)Carbon trading volume and pri…Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? —Empirical analysis based on the PSM-DID method (2019)Can a carbon trading system p…Improved EEMD-based crude oil price forecasting using LSTM networks (2018)Improved EEMD-based crude oil…A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting (2018)A novel multiscale nonlinear …Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression (2017)Forecasting carbon price usin…Forecasting carbon futures volatility using GARCH models with energy volatilities (2013)Forecasting carbon futures vo…Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology (2012)Carbon price forecasting with…Comparing Predictive Accuracy (1994)Time series forecasting using a hybrid ARIMA and neural network model (2003)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)A hybrid model for carbon price forecastingusing GARCH and long short-term memory network (2021)Carbon price forecasting based on CEEMDAN and LSTM (2022)Generalized autoregressive conditional heteroskedasticity (1986)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)The dynamic volatility spillover between European carbon trading market and fossil energy market (2015)Comparing Predictive Accuracy (1995)Machine learning in energy economics and finance: A review (2019)Environmental Regulations and Productivity Growth: The Case of Fossil-fueled Electric Power Generation (1983)Toward a New Conception of the Environment-Competitiveness Relationship (1995)Green R&D for eco-innovation and its impact on carbon emissions and firm performance (2015)Environmental regulation and green innovation: Evidence from China’s new environmental protection law (2021)The policy outcomes of low-carbon city construction on urban green development: Evidence from a quasi-natural experiment conducted in China (2021)Digital economy: An innovation driving factor for low-carbon development (2022)The conformable fractional grey system model (2019)The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations (2021)The Ethics of Artificial Intelligence (2023)Dynamic Conditional Correlation (2002)No Contagion, Only Interdependence: Measuring Stock Market Comovements (2002)Better to give than to receive: Predictive directional measurement of volatility spillovers (2011)Deaths, Panic, Lockdowns and US Equity Markets: The Case of COVID-19 Pandemic (2020)Is Gold a Hedge or a Safe-Haven Asset in the COVID–19 Crisis? (2020)Why Does Stock Market Volatility Change Over Time? (1989)A Theory of Friendly Boards (2007)Financial markets under the global pandemic of COVID-19 (2020)Investor Rewards to Environmental Responsibility in the COVID-19 Crisis (2020)The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets (2021)The impact of COVID-19 on the stock market crash risk in China (2021)The Limits of Arbitrage (1995)Law, Finance, and Economic Growth in China (2003)Explainable artificial intelligence modeling to forecast bitcoin prices (2023)Option Return Predictability with Machine Learning and Big Data (2023)FinTech: a literature review of emerging financial technologies and applications (2025)Sentiment and stock prices: The case of aviation disasters (2009)Impact of Russian-Ukraine war on clean energy, conventional energy, and metal markets: Evidence from event study approach (2022)Russia–Ukraine crisis: The effects on the European stock market (2022)The impact of the Russia-Ukraine conflict on energy firms: A capital market perspective (2022)Using daily stock returns (1985)A nonparametric test for abnormal security-price performance in event studies (1989)The Unprecedented Stock Market Reaction to COVID-19 (2020)
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References

  • 2020Financial contagion during COVID–19 crisis1,000 cited
  • 2020COVID-19 and the march 2020 stock market crash. Evidence from S&P1500726 cited
  • 2021Machine learning in the Chinese stock market593 cited
  • 2022The impact of the Ukraine–Russia war on world stock market returns569 cited
  • 2022Heterogeneous impacts of wars on global equity markets: Evidence from the invasion of Ukraine522 cited
  • 2019Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? —Empirical analysis based on the PSM-DID method450 cited
  • 2012Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology385 cited
  • 2013Forecasting carbon futures volatility using GARCH models with energy volatilities354 cited
  • 2017Forecasting carbon price using empirical mode decomposition and evolutionary least squares support vector regression310 cited
  • 2019Carbon trading volume and price forecasting in China using multiple machine learning models294 cited
  • 2021Carbon emissions determinants and forecasting: Evidence from G6 countries241 cited
  • 2018A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting235 cited
  • 2018Improved EEMD-based crude oil price forecasting using LSTM networks220 cited
  • 2020Event study on the reaction of the developed and emerging stock markets to the 2019-nCoV outbreak

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214 cited
  • 2021Assessing the impact of emissions trading scheme on low-carbon technological innovation: Evidence from China210 cited
  • 2021COVID–19 media coverage and ESG leader indices206 cited
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