Scale-function characterizations of pre-infimum paths under two decompositions for spectrally negative Lévy processes give Doob h-transform laws and explicit drawdown distributions on components.
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Neural networks outperform traditional econometric models in yield curve forecasting accuracy and simulated bond trading performance for US and European markets.
citing papers explorer
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Conditional Path Decomposition at the Infimum and Maximum Drawdowns for Spectrally Negative L\'{e}vy Processes
Scale-function characterizations of pre-infimum paths under two decompositions for spectrally negative Lévy processes give Doob h-transform laws and explicit drawdown distributions on components.
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Data-Driven Duration Management -- Term Structure Forecasting Using Machine Learning
Neural networks outperform traditional econometric models in yield curve forecasting accuracy and simulated bond trading performance for US and European markets.