Skip to main navigation
Skip to search
Skip to main content
University of Nottingham Ningbo China Home
Home
Profiles
Research units
Research output
Projects
Prizes
Activities
Press/Media
Impacts
Student theses
Search by expertise, name or affiliation
A neural network enhanced volatility component model
Jia Zhai, Yi Cao,
Xiaoquan Liu
Department of Finance, Accounting and Economics
Research output
:
Journal Publication
›
Article
›
peer-review
7
Citations (Scopus)
156
Downloads (Pure)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'A neural network enhanced volatility component model'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
ARMA Process
50%
Artificial Neural Network
50%
Chinese Stock Index
50%
Component Model
100%
Component Volatility
50%
Computational Methods
50%
Data Science
50%
Economic Gain
50%
Exchange Rate
50%
Financial Econometrics
50%
Forecast Horizon
50%
Forecasting Precision
50%
Intraday Data
50%
Mean-variance Utility
50%
Neural Network
100%
Nonparametric
50%
Out-of-sample Performance
50%
Portfolio Returns
50%
Realized Volatility
100%
Return Ratio
50%
Science Literature
50%
Sharpe Ratio
50%
Statistical Measures
50%
Two-component
50%
Volatility Components
100%
Volatility Forecast
100%
Volatility Modelling
50%
Volatility Prediction
50%
Computer Science
Alternative Model
100%
Artificial Neural Network
100%
Component Model
100%
Computational Method
100%
Neural Network
100%
Portfolio Return
100%
Mathematics
Artificial Neural Network
100%
Mean-Variance
100%
Neural Network
100%
Sharpe Ratio
100%
Economics, Econometrics and Finance
Exchange Rate
14%
Financial Econometrics
14%
Investors
14%
Stock Index
14%
Volatility
100%