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Wavelets in Economics and Finance: Past and Future

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References

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1998DECOMPOSITION OF ECONOMIC RELATIONSHIPS BY TIMESCALE USING WAVELETS347 cited
1999The contribution of wavelets to the analysis of economic and financial data247 cited
2001Scaling properties of foreign exchange volatility201 cited
2001Differentiating intraday seasonalities through wavelet multi-scaling175 cited
1979Analysis of Economic Time Series161 cited
1998Wavelet-based feature extraction and decomposition strategies for financial forecasting160 cited
1999Using wavelets to obtain a consistent ordinary least squares estimator of the long-memory parameter156 cited

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2019

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Dynamic spillovers and connectedness between stock, commodities, bonds, and VIX markets

102 cited

2018Oil price and automobile stock return co-movement: A wavelet coherence analysis96 cited

2021Oil prices volatility and economic performance during COVID-19 and financial crises of 2007–200888 cited

2017Long-Term Stock Market Volatility and the Influence of Terrorist Attacks in Europe86 cited

2015Investment horizon heterogeneity and wavelet: Overview and further research directions84 cited

2015Correlations between oil and stock markets: A wavelet-based approach83 cited

2005On the relationship between changes in stock prices and bond yields in the G7 countries: Wavelet analysis80 cited

2017U.S. shale oil production and WTI prices behaviour77 cited

2021On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis76 cited

2007The war on terror and its impact on the long-term volatility of financial markets74 cited

2021Evidence of Stock Market Contagion during the COVID-19 Pandemic: A Wavelet-Copula-GARCH Approach48 cited

2006The impact of major global events on volatility shifts: Evidence from the Asian crisis and 9/1148 cited

2009Estimating VaR in crude oil market: A novel multi-scale non-linear ensemble approach incorporating wavelet analysis and neural network47 cited

2019The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data40 cited