156 citations · 391 across the 43 of their papers we have counts for
4 papers · 1 filter
Global Neural Networks and The Data Scaling Effect in Financial Time Series Forecasting
Chen Liu, Minh-Ngoc Tran, Chao Wang +2
Neural networks have revolutionized many empirical fields, yet their application to financial time series forecasting remains controversial. In this study, we demonstrate that the…
Deep Learning Enhanced Realized GARCH
Chen Liu, Chao Wang, Minh-Ngoc Tran +1
We propose a new approach to volatility modeling by combining deep learning (LSTM) and realized volatility measures. This LSTM-enhanced realized GARCH framework incorporates and di…
Recurrent Conditional Heteroskedasticity
T. -N. Nguyen, M. -N. Tran, R. Kohn
We propose a new class of financial volatility models, called the REcurrent Conditional Heteroskedastic (RECH) models, to improve both in-sample analysis and out-ofsample forecasti…
A Statistical Recurrent Stochastic Volatility Model for Stock Markets
Trong-Nghia Nguyen, Minh-Ngoc Tran, David Gunawan +1
The Stochastic Volatility (SV) model and its variants are widely used in the financial sector while recurrent neural network (RNN) models are successfully used in many large-scale…