3 citations · 5 across the 2 of their papers we have counts for
3 papers
q-fin.ST2022★ 2 cited
Variational Heteroscedastic Volatility Model
Zexuan Yin, Paolo Barucca
We propose Variational Heteroscedastic Volatility Model (VHVM) -- an end-to-end neural network architecture capable of modelling heteroscedastic behaviour in multivariate financial…
cs.LG2022★ 3 cited
Neural Generalised AutoRegressive Conditional Heteroskedasticity
Zexuan Yin, Paolo Barucca
We propose Neural GARCH, a class of methods to model conditional heteroskedasticity in financial time series. Neural GARCH is a neural network adaptation of the GARCH 1,1 model in…
cs.LG2021
Stochastic Recurrent Neural Network for Multistep Time Series Forecasting
Zexuan Yin, Paolo Barucca
Time series forecasting based on deep architectures has been gaining popularity in recent years due to their ability to model complex non-linear temporal dynamics. The recurrent ne…