[HTML][HTML] Forecasting: theory and practice

F Petropoulos, D Apiletti, V Assimakopoulos… - International Journal of …, 2022 - Elsevier
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics

X Tan, K Sirichand, A Vivian, X Wang - Energy Economics, 2020 - Elsevier
Carbon allowances are a new class of financial instrument which aim to assist in limiting the
extent and impact of global warming and climate change. The feedback mechanism in the …

Which sentiment index is more informative to forecast stock market volatility? Evidence from China

C Liang, L Tang, Y Li, Y Wei - International Review of Financial Analysis, 2020 - Elsevier
In this paper, we investigate the predictive ability of three sentiment indices constructed by
social media, newspaper, and Internet media news to forecast the realized volatility (RV) of …

How is machine learning useful for macroeconomic forecasting?

P Goulet Coulombe, M Leroux… - Journal of Applied …, 2022 - Wiley Online Library
Summary We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by
adding the how. The current forecasting literature has focused on matching specific …

[HTML][HTML] Global financial stress index and long-term volatility forecast for international stock markets

C Liang, Q Luo, Y Li, LDT Huynh - Journal of International Financial …, 2023 - Elsevier
In this study, we examine the long-term predictive role of the global financial stress index
(GFSI) on equity market volatility and provide a comprehensive analysis using GFSI for the …

Uncertainty and crude oil market volatility: new evidence

C Liang, Y Wei, X Li, X Zhang, Y Zhang - Applied Economics, 2020 - Taylor & Francis
The main goal of this paper is to investigate the predictability of five economic uncertainty
indices for oil price volatility in a changing world. We employ the standard predictive …

Forecasting oil price volatility: Forecast combination versus shrinkage method

Y Zhang, Y Wei, Y Zhang, D Jin - Energy Economics, 2019 - Elsevier
In this paper, we compare the predictive ability between forecast combination and shrinkage
method in the prediction of oil price volatility. Our investigation is based on the …

Is implied volatility more informative for forecasting realized volatility: An international perspective

C Liang, Y Wei, Y Zhang - Journal of Forecasting, 2020 - Wiley Online Library
Inspired by the commonly held view that international stock market volatility is equivalent to
cross‐market information flow, we propose various ways of constructing two types of …

Which uncertainty is powerful to forecast crude oil market volatility? New evidence

X Li, Y Wei, X Chen, F Ma, C Liang… - International Journal of …, 2022 - Wiley Online Library
This paper focuses on distinguishing the predictive power of five newly developed
uncertainty indices, that is, global and US economic policy uncertainty (GEPU and US EPU) …

Global equity market volatilities forecasting: a comparison of leverage effects, jumps, and overnight information

C Liang, Y Li, F Ma, Y Wei - International Review of Financial Analysis, 2021 - Elsevier
This study extends the HAR-RV model to detailedly compare the role of leverage effects,
jumps, and overnight information in predicting the realized volatilities (RV) of 21 …