6 papers
Distributional Off-Policy Evaluation with Deep Quantile Process Regression
Qi Kuang, Chao Wang, Yuling Jiao +1
This paper investigates the off-policy evaluation (OPE) problem from a distributional perspective. Rather than focusing solely on the expectation of the total return, as in most ex…
Deep Learning Enhanced Multivariate GARCH
Haoyuan Wang, Chen Liu, Minh-Ngoc Tran +1
This paper introduces a novel multivariate volatility modeling framework, named Long Short-Term Memory enhanced BEKK (LSTM-BEKK), that integrates deep learning into multivariate GA…
Financial Volatility and Risk Forecasting Incorporating a Larger Number of Realized Measures
Qianli Zhao, Chao Wang, Richard Gerlach +2
Realised volatility has become increasingly prominent in volatility forecasting due to its ability to capture intraday price fluctuations. With a growing variety of realised volati…
Loss-based Bayesian Sequential Prediction of Value at Risk with a Long-Memory and Non-linear Realized Volatility Model
Rangika Peiris, Minh-Ngoc Tran, Chao Wang +1
A long memory and non-linear realized volatility model class is proposed for direct Value at Risk (VaR) forecasting. This model, referred to as RNN-HAR, extends the heterogeneous a…
Semi-parametric financial risk forecasting incorporating multiple realized measures
Rangika Peiris, Chao Wang, Richard Gerlach +1
A semi-parametric joint Value-at-Risk (VaR) and Expected Shortfall (ES) forecasting framework employing multiple realized measures is developed. The proposed framework extends the…
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…