Forecasting the aggregate stock market volatility in a data-rich world-Reference-Cited by-同舟云学术

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Forecasting the aggregate stock market volatility in a data-rich world

Published:2020-01-16 Issue:32 Volume:52 Page:3448-3463
ISSN:0003-6846
Container-title:Applied Economics
language:en
Short-container-title:Applied Economics

Author:

Liu Li¹,Ma Feng²,Zeng Qing²,Zhang Yaojie³^ORCID

Affiliation:

1. School of Finance, Nanjing Audit University , Nanjing, China

2. School of Economics and Management, Southwest Jiaotong University , Chengdu, China

3. School of Economics and Management, Nanjing University of Science and Technology , Nanjing, China

Publisher

Informa UK Limited

Subject

Economics and Econometrics

Link

https://www.tandfonline.com/doi/pdf/10.1080/00036846.2020.1713291

Reference47 articles.

1. Optimal Inattention to the Stock Market With Information Costs and Transactions Costs

2. Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility

3. Volatility Forecasting: Downside Risk, Jumps and Leverage Effect

4. Measuring Economic Policy Uncertainty*

5. Risk Everywhere: Modeling and Managing Volatility

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1. Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set;International Review of Economics & Finance;2024-06

2. A Literature Review on the Model of EGARCH-MIDAS, LMM, GBM for Stock Market Prediction;Applied Economics and Policy Studies;2024

3. The role of categorical EPU indices in predicting stock-market returns;International Review of Economics & Finance;2023-09

4. Macroeconomic attention, economic policy uncertainty, and stock volatility predictability;International Review of Financial Analysis;2022-11

5. A Novel Machine Learning Approach for Predicting the NIFTY50 Index in India;International Advances in Economic Research;2022-11

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