Are the leading indicators really leading? Evidence from mixed-frequency spillover approach
Author
Abstract
Suggested Citation
DOI: 10.1016/j.frl.2024.106233
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Feng, Haoyuan & Liu, Yue & Wu, Jie & Guo, Kun, 2023. "Financial market spillovers and macroeconomic shocks: Evidence from China," Research in International Business and Finance, Elsevier, vol. 65(C).
- Lyu, Yongjian & Qin, Fanshu & Ke, Rui & Wei, Yu & Kong, Mengzhen, 2024. "Does mixed frequency variables help to forecast value at risk in the crude oil market?," Resources Policy, Elsevier, vol. 88(C).
- Diebold, Francis X. & Yilmaz, Kamil, 2012.
"Better to give than to receive: Predictive directional measurement of volatility spillovers,"
International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
- Francis X. Diebold & Kamil Yilmaz, 2010. "Better to Give than to Receive: Predictive Directional Measurement of Volatility Spillovers," Koç University-TUSIAD Economic Research Forum Working Papers 1001, Koc University-TUSIAD Economic Research Forum, revised Mar 2010.
- Tom Doan, 2025. "DIEBOLDYILMAZ_IJF2012: RATS program to replicate Diebold and Yilmaz(2012) spillover calculations," Statistical Software Components RTZ00199, Boston College Department of Economics.
- Xie, Wenhao & Cao, Guangxi, 2024. "Volatility and returns connectedness between cryptocurrency and China’s financial markets: A TVP-VAR extended joint connectedness approach," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
- Xu, Qifa & Xu, Mengnan & Jiang, Cuixia & Fu, Weizhong, 2023. "Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China," Economic Systems, Elsevier, vol. 47(4).
- Chen, Shiu-Sheng, 2009. "Predicting the bear stock market: Macroeconomic variables as leading indicators," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 211-223, February.
- Chao Liang & Yu Wei & Xiafei Li & Xuhui Zhang & Yifeng Zhang, 2020. "Uncertainty and crude oil market volatility: new evidence," Applied Economics, Taylor & Francis Journals, vol. 52(27), pages 2945-2959, May.
- Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
- Chang, Tsangyao & Hsu, Chen-Min & Chen, Sheng-Tung & Wang, Mei-Chih & Wu, Cheng-Feng, 2023. "Revisiting economic growth and CO2 emissions nexus in Taiwan using a mixed-frequency VAR model," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 319-342.
- Zhou, Wen, 2023. "Did Donald Trump's tweets on Sino–U.S. Trade affect the offshore RMB exchange rate?," Finance Research Letters, Elsevier, vol. 58(PA).
- Zhu, Lin & Jiang, Fuwei & Tang, Guohao & Jin, Fujing, 2024. "From macro to micro: Sparse macroeconomic risks and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PB).
- Cotter, John & Hallam, Mark & Yilmaz, Kamil, 2023.
"Macro-financial spillovers,"
Journal of International Money and Finance, Elsevier, vol. 133(C).
- John Cotter & Mark Hallam & Kamil Yilmaz, 2020. "Macro-Financial Spillovers," Working Papers 202005, Geary Institute, University College Dublin.
- Bai, Lan & Wei, Yu & Zhang, Jiahao & Wang, Yizhi & Lucey, Brian M., 2023. "Diversification effects of China's carbon neutral bond on renewable energy stock markets: A minimum connectedness portfolio approach," Energy Economics, Elsevier, vol. 123(C).
- Xie, Qichang & Bai, Yu & Jia, Nanfei & Xu, Xin, 2024. "Do macroprudential policies reduce risk spillovers between energy markets?: Evidence from time-frequency domain and mixed-frequency methods," Energy Economics, Elsevier, vol. 134(C).
- Wei, Yu & Wang, Yizhi & Lucey, Brian M. & Vigne, Samuel A., 2023. "Cryptocurrency uncertainty and volatility forecasting of precious metal futures markets," Journal of Commodity Markets, Elsevier, vol. 29(C).
- Wang, Yizhi & Wei, Yu & Lucey, Brian M. & Su, Yang, 2023. "Return spillover analysis across central bank digital currency attention and cryptocurrency markets," Research in International Business and Finance, Elsevier, vol. 64(C).
- Haase, Felix & Neuenkirch, Matthias, 2023.
"Predictability of bull and bear markets: A new look at forecasting stock market regimes (and returns) in the US,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 587-605.
- Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Research Papers in Economics 2020-01, University of Trier, Department of Economics.
- Felix Haase & Matthias Neuenkirch, 2021. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," CESifo Working Paper Series 8828, CESifo.
- Felix Haase & Matthias Neuenkirch, 2020. "Predictability of Bull and Bear Markets: A New Look at Forecasting Stock Market Regimes (and Returns) in the US," Working Paper Series 2020-03, University of Trier, Research Group Quantitative Finance and Risk Analysis.
- Xu, Yongdeng & Guan, Bo & Lu, Wenna & Heravi, Saeed, 2024.
"Macroeconomic shocks and volatility spillovers between stock, bond, gold and crude oil markets,"
Energy Economics, Elsevier, vol. 136(C).
- Xu, Yongdeng & Guan, Bo & Lu, Wenna & Heravi, Saeed, 2024. "Macroeconomic shocks and volatility spillovers between stock, bond, gold and crude oil markets," Cardiff Economics Working Papers E2024/15, Cardiff University, Cardiff Business School, Economics Section.
- Jiang, Cuixia & Gao, Haijing & Xu, Qifa, 2024. "China's risk contagion using the mixed-frequency macro-financial network," Economic Systems, Elsevier, vol. 48(4).
- Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
- Su, Chi-Wei & Wang, Dan & Mirza, Nawazish & Zhong, Yifan & Umar, Muhammad, 2023. "The impact of consumer confidence on oil prices," Energy Economics, Elsevier, vol. 124(C).
- Wei, Yu & Liu, Jing & Lai, Xiaodong & Hu, Yang, 2017. "Which determinant is the most informative in forecasting crude oil market volatility: Fundamental, speculation, or uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 141-150.
- Yang, Jianlei & Yang, Chunpeng, 2021. "The impact of mixed-frequency geopolitical risk on stock market returns," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 226-240.
- Liang, Chao & Yang, Jinyu & Shen, Lihua & Dong, Dayong, 2024. "The role of biodiversity risk in stock price crashes," Finance Research Letters, Elsevier, vol. 67(PA).
- Yu Wei & Lan Bai & Kun Yang & Guiwu Wei, 2021. "Are industry‐level indicators more helpful to forecast industrial stock volatility? Evidence from Chinese manufacturing purchasing managers index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 17-39, January.
- Long, Huaigang & Zaremba, Adam & Zhou, Wenyu & Bouri, Elie, 2022. "Macroeconomics matter: Leading economic indicators and the cross-section of global stock returns," Journal of Financial Markets, Elsevier, vol. 61(C).
- Liang, Chao & Goodell, John W. & Li, Xiafei, 2024. "Impacts of carbon market and climate policy uncertainties on financial and economic stability: Evidence from connectedness network analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
- Albulescu, Claudiu Tiberiu & Demirer, Riza & Raheem, Ibrahim D. & Tiwari, Aviral Kumar, 2019. "Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies," Energy Economics, Elsevier, vol. 83(C), pages 375-388.
- Liu, Jing & Chen, Zhonglu, 2023. "How do stock prices respond to the leading economic indicators? Analysis of large and small shocks," Finance Research Letters, Elsevier, vol. 51(C).
- Zhang, Yu & Kappou, Konstantina & Urquhart, Andrew, 2024. "Macroeconomic momentum and cross-sectional equity market indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 92(C).
- Athanasios Triantafyllou & Dimitrios Bakas & Marilou Ioakimidis, 2023. "Commodity price uncertainty as a leading indicator of economic activity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4194-4219, October.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Wang, Zhuo & Wei, Yu & Shang, Yue & Wang, Qian & Zhao, Cheng, 2025. "Do economic policy uncertainties matter for economic growth? Evidence from MIDAS approaches," Research in International Business and Finance, Elsevier, vol. 74(C).
- Mengting Li & Yu Wei & Rangan Gupta & Oguzhan Cepni, 2025. "Carbon Price Uncertainty-Macroeconomy Mixed-Frequency Spillovers: Evidence from the Frequency-Domain," Working Papers 202527, University of Pretoria, Department of Economics.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ye Chen & Yu Wei & Chunyan Zhou, 2026. "Climate Risk Transmissions to Commodity Markets: Evidence From a Mixed-Frequency Spillover Approach," Evaluation Review, , vol. 50(3), pages 346-383, June.
- Wang, Zhuo & Wei, Yu & Shang, Yue & Wang, Qian & Zhao, Cheng, 2025. "Do economic policy uncertainties matter for economic growth? Evidence from MIDAS approaches," Research in International Business and Finance, Elsevier, vol. 74(C).
- Li, Xiafei & Li, Bo & Wei, Guiwu & Bai, Lan & Wei, Yu & Liang, Chao, 2021. "Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US," Resources Policy, Elsevier, vol. 73(C).
- Li, Mengting & Ma, Xiaofu & Jia, Junsheng & Zhu, Chen, 2025. "Risk spillovers between the financial market and macroeconomic sectors under mixed-frequency information: A frequency domain perspective," International Review of Economics & Finance, Elsevier, vol. 99(C).
- Wei, Yu & Wang, Yizhi & Vigne, Samuel A. & Ma, Zhenyu, 2023. "Alarming contagion effects: The dangerous ripple effect of extreme price spillovers across crude oil, carbon emission allowance, and agriculture futures markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
- Qian Wang & Yu Wei & Yifeng Zhang & Yuntong Liu, 2023. "Evaluating the Safe-Haven Abilities of Bitcoin and Gold for Crude Oil Market: Evidence During the COVID-19 Pandemic," Evaluation Review, , vol. 47(3), pages 391-432, June.
- Hu, Chunyang & Zhou, Yang, 2025. "Do domestic and US economic policy uncertainty increase China’s macro-financial risk connectedness?," Research in International Business and Finance, Elsevier, vol. 80(C).
- Xiao, Jihong & Zhang, Jingyu & Zheng, Yan, 2025. "Geopolitical risks and oil market fear: Country-specific spillover effects," Research in International Business and Finance, Elsevier, vol. 77(PB).
- Guo, Yangli & Ma, Feng & Li, Haibo & Lai, Xiaodong, 2022. "Oil price volatility predictability based on global economic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
- Xiafei Li & Chao Liang & Feng Ma, 2025. "Forecasting stock market volatility with a large number of predictors: New evidence from the MS-MIDAS-LASSO model," Annals of Operations Research, Springer, vol. 352(3), pages 613-652, September.
- Ramesh, Shietal & Low, Rand Kwong Yew & Faff, Robert, 2025.
"Corrigendum to “Modelling time-varying volatility spillovers across crises: Evidence from major commodity futures and the US stock market” [Energy Economics Volume 143, March 2025, 108225],"
Energy Economics, Elsevier, vol. 147(C).
- Ramesh, Shietal & Low, Rand Kwong Yew & Faff, Robert, 2025. "Modelling time-varying volatility spillovers across crises: Evidence from major commodity futures and the US stock market," Energy Economics, Elsevier, vol. 143(C).
- Wu, Zewen, 2024. "Are we in a bubble? Financial vulnerabilities in semiconductor, Web3, and genetic engineering markets," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 32-44.
- Wei, Yu & Hu, Rui & Zhang, Jiahao & Wang, Qian, 2024. "Does the carbon market signal the market efficiency of clean and dirty cryptocurrencies? An analysis of quantile directional dependence," Finance Research Letters, Elsevier, vol. 67(PB).
- Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).
- Liu, Yuntong & Wei, Yu & Wang, Qian & Liu, Yi, 2022. "International stock market risk contagion during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
- Yousaf, Imran & Ijaz, Muhammad Shahzad & Umar, Muhammad & Li, Yanshuang, 2024. "Exploring volatility interconnections between AI tokens, AI stocks, and fossil fuel markets: evidence from time and frequency-based connectedness analysis," Energy Economics, Elsevier, vol. 133(C).
- Wang, Jie & Hu, Jiukai & Yu, Bo, 2025. "Risk spillover effects among Chinese policy, economy and financial markets: Evidence from mixed-frequency data," Economic Analysis and Policy, Elsevier, vol. 86(C), pages 2263-2277.
- Pham, Son D. & Nguyen, Thao T.T. & Do, Hung X., 2024. "Impact of climate policy uncertainty on return spillover among green assets and portfolio implications," Energy Economics, Elsevier, vol. 134(C).
- Assaf, Ata & Charif, Husni & Mokni, Khaled, 2021. "Dynamic connectedness between uncertainty and energy markets: Do investor sentiments matter?," Resources Policy, Elsevier, vol. 72(C).
- Shi, Chunpei & Wei, Yu & Li, Xiafei & Liu, Yuntong, 2023. "Combination forecasts of China's oil futures returns based on multiple uncertainties and their connectedness with oil," Energy Economics, Elsevier, vol. 126(C).
More about this item
Keywords
; ; ; ;JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit
- G1 - Financial Economics - - General Financial Markets
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:69:y:2024:i:pb:s1544612324012625. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/eee/finlet/v69y2024ipbs1544612324012625.html