International comovement of stock market returns: a wavelet analysis
By Antonio Rúa, L. Nunes. 2009
804 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/d72d9f436a2ba6834ce98e263e0a2a9e8a43125f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Ladislav Kristoufek
- C. Aloui
- Lukáš Vácha
- David Zilberman
- Karel Janda
- Besma Hkiri
- L. Nunes
- Antonio Rúa
In Finance
- C. Aloui
- Ladislav Kristoufek
- L. Nunes
- Antonio Rúa
- Lukáš Vácha
- Maria Joana Soares
- Jussi Nikkinen
- L. Aguiar
Citations in the corpus
- Testing the Conventional and Islamic Financial Market Contagion: Evidence from Wavelet Analysis (2016, neutral): “This particular feature of the Japanese stock index has been documented by others, for example Rua and Nunes (2009).”
- Time-Frequency Dynamics of Biofuels-Fuels-Food System (2012, methodology): “In our analysis, we set ω0 = 6, which is the value often used in the economic applications as it provides an optimal time-frequency balance (Rua and Nunes, 2009; Aguiar-Conraria et al., 2012).”
- International diversification with frontier markets (2011, background): “Recently, Rua and Nunes (2009) use wavelets to study cross-market correlations within developed markets and find that the US and UK stock markets exhibit the highest comovement across time while the Japanese market shows a low degree of comovement with other major stock markets.”
- Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis (2012, methodology): “t) = 1 ˇ1=4 ei! 0te t 2=2: (3) Parameter ! 0 denotes the central frequency of the wavelet. We set ! 0 = 6, which is often used in economic applications { see for example AguiarConraria et al. (2008); Rua and Nunes (2009). The Morlet wavelet belongs to the family of complex or analytic wavelets, henc”
- An empirical analysis of dynamic multiscale hedging using wavelet decomposition (2011, methodology): “me-scales, (Galagedera and Maharaj, 2008), the scale dependence of hedge fund market risk and correlation, (Conlon et al., 2008) and international diversification benefits at differ ent time horizons, (Rua and Nunes, 2009) have been studied using the wavelet transform. 3 combinedwith wavelet multiscal”