The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development
Abstract
The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of daily Foreign Exchange rates, Stock Market indices and fixed income instruments by using the generalized Hurst approach. We show that the scaling exponents are associated with characteristics of the specific markets and can be used to differentiate markets in their stage of development. The robustness of the results is tested by both Monte-Carlo studies and a computation of the scaling in the frequency-domain.
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Forbidden patterns, permutation entropy and stock market inefficiency
Zunino, L., Zanin, M., Tabak, B. M., Pérez, D. G., & Rosso, O. A. (2009) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2009.03.042 · Cited by 249
Metadata
- Authors
- Matteo, T. D., Aste, T., & Dacorogna, M. M.
- Venue
- Journal of Banking & Finance
- Publisher
- Elsevier BV
- Published
- 2005-04
- Volume
- 29
- Issue
- 4
- Pages
- 827-851
- ISSN
- 0378-4266 (ISSN-L)
- OpenAlex
- W2157702779
- Cited by
- 428
- References
- 24
- FWCI
- 34.77
- Type
- journal article
- Language
- en
- Open access
- closed
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- Matteo, T. D., Aste, T., & Dacorogna, M. M. (2005). Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development. Journal of Banking & Finance. https://doi.org/10.1016/j.jbankfin.2004.08.004
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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.
