Time-frequency co-movements between bank credit supply and economic growth in an emerging market: Does the bank ownership structure matter?

This study aims to shed some light on the causal link between bank credit supply and economic growth in Turkey for the banks with the different ownership structures between 1993Q4 and 2017Q3. Wavelet coherence test is used to obtain this objective and to answer the following questions: (i) does bank credit supply lead to economic growth in Turkey and vice versa, and (ii) does the bank ownership matters in this linkage? The findings from wavelet coherence reveal that between 1993 and 2003 in the short and medium term, economic growth leads credit supply but in the long run there is feedback causality between credit supply and economic growth for only public and private banks. However, in the long-run between 1993 and 2003 economic growth leads credit supply in the foreign banks in Turkey. Between 2004 and 2017, there is feedback causality between credit supply and economic growth. Moreover, our findings suggest that bank ownership affects the strength of the linkage between credit supply and economic growth in Turkey especially in the short and medium terms. More specially, within the three types of bank ownership, the findings imply that the strongest correlation among the variables is for the private banks while the weakest one is for foreign banks.     

Contagion of Capital Markets in CEE Countries: Evidence from Wavelet Analysis

We employed wavelets technology to investigate how and when contagion occurred on 10 Central and Eastern European financial markets in relation to Western European and US financial markets during 2000–2016 and their different reactions on the background of changes in their regulatory framework. We found that most of Central and Eastern European (CEE) capital markets showed contagion in relation to both Western European and US markets between 2005 and 2009, while Slovakian and Estonian markets showed no contagion. However, during 2010–2016, Croatian market showed de-contagion in relation to Western European market, while Bulgarian, Czech, Hungarian, and Polish markets showed de-contagion in relation to US market, increasing their independence.     

Wavelet coherence analysis of returns,volatility and interdependence of the US and the EU money markets: Pre & post crisis

This research analyse the US and the EU money markets interdependence from 2004 to 2018. The study explains to what extent the volatility of the chosen money markets instruments in two regions is inter-correlated before, during and after the financial crisis of 2008. We apply the econometric analysis and estimate time-series models of class GARCH to study the historical dynamics of interbank rates and bond returns. The study demonstrates that correlation between returns of analogous money market instruments in the EU and US is not stable over time. We find that correlation rises in periods when countries are exposed to the same external shocks as global financial crisis. Wavelet coherence analysis suggests that investors do not get any advantages of portfolio diversification investing only in US treasuries with different maturities for more than 256 days and do not get any advantages at all investing only in European bonds.     

Impact of the Covid-19 induced panic on the Environmental,Social and Governance leaders equity volatility: A time-frequency analysis

We apply wavelet analyses to study how the Covid-19 fueled panic influenced the volatility of ESG (environmental, social and governance) leaders’ indices encompassing the World, the USA, Europe, China, and the Emerging Markets. We document intervals of the low, medium, and high coherence between the Coronavirus Panic Index and the price moves of the ESG Leaders indices. The low coherence intervals signify the diversification potential of ESG investments during a systemic pandemic such as Covid-19. We document differences in the pattern exhibited by various geographical indices highlighting their potential role for designing cross-geography hedge strategies, both now and in the future.     

Investor attention and cryptocurrency: Evidence from wavelet-based quantile Granger causality analysis

This paper investigates the relationship between investor attention and the major cryptocurrency markets by wavelet-based quantile Granger causality. The wavelet analysis illustrates the interdependence between investor attention and the cryptocurrency returns. Multi-scale quantile Granger causality based on wavelet decomposition further demonstrates bidirectional Granger causality between investor attention and the returns of Bitcoin, Ethereum, Ripple and Litecoin for all quantiles, except for the medium. Among them, the Granger causality from investor attention to the returns is relatively very weak for Ethereum. In the short term, the Granger causality from these cryptocurrency returns to investor attention seems symmetric, but in the medium- and long- term, the causality shows some asymmetry. The Granger causality from investor attention to these cryptocurrency returns is asymmetric and varies across cryptocurrencies and time scales. Specifically, investor attention has a relatively stronger impact on the cryptocurrency returns in bearish markets than that in bullish markets in the short term.     

Impact of COVID-19 pandemic on stock markets: Conventional vs. Islamic indices using wavelet-based multi-timescales analysis

We empirically explore the effect of the COVID-19 pandemic on Islamic and conventional stock markets from a global perspective. We also explore the co-movement between Islamic and conventional stock markets. Two comparable pairs of conventional and Islamic stock indices – Dow Jones Index and FTSE Index are considered in this study. Employing Wavelet-based multi-timescales techniques on the daily data from 21st January to 27th November 2020, our findings indicate that the pandemic creates identical volatility in both stock markets. Our findings further suggest that both markets are strongly associated and tend to co-move highly during our sample period, rebutting the decoupling hypothesis of the Islamic stock market from the conventional market. However, the Shariah screening process fails to provide immunity to Islamic stock markets against financial crises. Our findings suggest that investors should be aware that Islamic stocks' conservative features do not present a superior investment alternative, especially in economic turmoil.     

Should Africa’s emerging markets still be considered as a separate asset class?

This article examines the correlation of Africa’s emerging markets regionally and globally using the Continuous Morlet Wavelet (CMW) transform. The superiority of this technique is that it is able to estimate correlation in a time-varying manner and derive all information about structural changes in the data through a phase difference technique. We find that Africa’s emerging equity markets are partially segmented regionally and globally. Although correlations may have increased over time, we suggest that emerging markets in Africa should still be considered as a separate asset class.     

The impact of investor sentiment on crude oil market risks: evidence from the wavelet approach

Investor sentiment has become an important factor affecting oil price volatility and extreme risk. Therefore, we utilise a VaR-GARCH model to detect the extreme risk of the crude oil market during 2007–2017, and then explore the causality between investor sentiment and extreme risk in the crude oil market, and their lead-lag and co-movement relationships in the time-frequency domain. The empirical results show that: firstly, investor sentiment leads downside risk but lags the upside risk in the crude oil market; secondly, in the time domain, there is a co-movement between investor sentiment and extreme risk in the crude oil market, in particular, investor sentiment may Granger cause extreme risk in the crude oil market at the 1% significance level but not vice versa; thirdly, in the frequency domain, weak coherence can be found in high-frequency bands but increases in low-frequency bands during the whole sample period, which indicates that the impact of investor sentiment on extreme risk in the crude oil market will last for a long time, although the affected period tends to decrease.     

中国创业板和主板市场间溢出效应研究——基于小波多分辨分析

运用小波多分辨分析及VAR-DCC-GARCH模型,研究了中国创业板与主板股票市场间的溢出效应。实证结果表明:从长期趋势看,中国创业板与主板市场之间存在双向的均值和波动溢出;从短期来看,在1～2天的短期交易周期中,两者之间不存在任何溢出效应;随着交易周期的增长,两者间的均值溢出效应是从无到单向,再到双向逐步体现出来的,而波动溢出效应的出现则没有规律性。     

Estimators of long-memory: Fourier versus wavelets

Semi-parametric estimation methods of the long-memory exponent of a time series have been studied in several papers, some applied, others theoretical, some using Fourier methods, others using a wavelet-based technique. In this paper, we compare the Fourier and wavelet approaches to the local regression method and to the local Whittle method. We provide an overview of these methods, describe what has been done and indicate the available results and the conditions under which they hold. We discuss their relative strengths and weaknesses both from a practical and a theoretical perspective. We also include a simulation-based comparison. The software written to support this work is available on demand and we illustrate its use at the end of the paper.