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A Machine learning framework for forecasting portfolios of green bond returns

https://doi.org/10.2139/ssrn.5732508
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Beyond carbon pricing: The role of banking and monetary policy in financing the transition to a low-carbon economy
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Green bond and financial markets: Co-movement, diversification and price spillover effects
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Time-varying relation between black and green bond price benchmarks: Macroeconomic determinants for the first decade
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Factors behind the performance of green bond markets
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Improving trading technical analysis with TensorFlow Long Short-Term Memory (LSTM) Neural Network
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Is it risky to go green? A volatility analysis of the green bond market
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The Extreme Value Method for Estimating the Variance of the Rate of Return
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Realized Volatility Forecasting with Neural Networks
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Intraday Market Predictability: A Machine Learning Approach
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A Machine Learning Approach to Volatility Forecasting
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Volatility Forecasting with Machine Learning and Intraday Commonality
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Learning long-term dependencies with gradient descent is difficult
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Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects
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Forecasting Volatility in Financial Markets: A Review
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The Distributed Lag Between Capital Appropriations and Expenditures
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Green Bond: A Systematic Literature Review for Future Research Agendas
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Volatility Spillovers between Equity and Green Bond Markets
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