Using wavelets to decompose the time–frequency effects of monetary policy

By Luís Aguiar-Conraria, Nuno Azevedo, Maria Joana Soares. 2008

606 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e883689fd69fe24ec9ecdcb7f15bea32b9164569

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In Economics and Econometrics

Citations in the corpus

Co-movement between sharia stocks and sukuk in the GCC markets: A time-frequency analysis (2015, neutral): “386 Aguiar-Conraria et al. (2008).”
What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis (2014, background): “From a wide range of wavelets, we opt for the Morlet wavelet which provides a good balance between time and frequency localization [12, 14].”
Oil and the macroeconomy: using wavelets to analyze old issues (2011, methodology): “1 2 , (4) where S denotes a smoothing operator in both time and scale — see Aguiar-Conraria et al. (2008) for details.”
The continuous wavelet transform : a primer (2011, positive): “Raihan, Wen and Zeng [35], Jagrič and Ovin [27], Crowley and Mayes [10], Aguiar-Conraria, Azevedo and Soares [1], Baubeau and Cazelles [3], Rua and Nunes [41], Rua [40] and Aguiar-Conraria and Soares [2]; provide some examples of useful economic applications of these tools.”
The Yield Curve and the Macro-economy across Time and Frequencies" (Cef.up Working Paper nº. 2010-04, July 2010) (2012, methodology): “When using a discretized version of formula (2), a periodization of the data is assumed.”
THE CONTINUOUS WAVELET TRANSFORM: MOVING BEYOND UNI‐ AND BIVARIATE ANALYSIS (2014, positive): “Formula (1) tells us that the time series yt is the sum of two periodic components.”
Business Cycle Synchronization and the Euro: a Wavelet Analysis ∗ (2011, methodology): “This means that (1) the contribution of cycles at each frequency to the total variance is similar between both countries, (2) this contribution happens at the same time in both countries and, finally, (3) the ups and downs of each cycle occur simultaneously in both countries.”
Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis (2012, methodology): “We set ω0=6, which is often used in economic applications — see for example (Aguiar-Conraria et al., 2008; Rua and Nunes, 2009).”
Analyzing time–frequency relationship between oil price and exchange rate in Pakistan through wavelets (2015, methodology): “Aguiar-Conraria and Soares [2, p. 646] Wavelet transformation works within the spectral framework for analysis of the time series and it is a function of time.”