The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Better to give than to receive: Predictive directional measurement of volatility spillovers
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Citations
Cites
Engle, R. (2002) · Journal of Business & Economic Statistics · doi:10.1198/073500102288618487 · Cited by 7,133
Cited by
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Baruník, J., & Křehlík, T. (2018) · Journal of Financial Econometrics · doi:10.1093/jjfinec/nby001 · Cited by 1,766
Dynamic connectedness and integration in cryptocurrency markets
Ji, Q., Bouri, E., Lau, C. K. M., & Roubaud, D. (2019) · International Review of Financial Analysis · doi:10.1016/j.irfa.2018.12.002 · Cited by 624
A model of financialization of commodities
BASAK, S., & PAVLOVA, A. (2016) · The Journal of Finance · doi:10.1111/jofi.12408 · Cited by 595
Is non-fungible token pricing driven by cryptocurrencies?
Dowling, M. (2022) · Finance Research Letters · doi:10.1016/j.frl.2021.102097 · Cited by 550
Geopolitical risk and dynamic connectedness between commodity markets
Gong, X., & Xu, J. (2022) · Energy Economics · doi:10.1016/j.eneco.2022.106028 · Cited by 354
Metadata
- Authors
- Diebold, F. X., & Yilmaz, K.
- Venue
- International Journal of Forecasting
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 28
- Issue
- 1
- Pages
- 57-66
- ISSN
- 0169-2070 (ISSN-L)
- OpenAlex
- W2039734130
- Cited by
- 5,756
- References
- 1
- FWCI
- 74.17
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Better to give than to receive: Predictive directional measurement of volatility spillovers. https://app.cochat.ai/papers/10.1016/j.ijforecast.2011.02.006
- The paper
- Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting. https://doi.org/10.1016/j.ijforecast.2011.02.006
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
