UNVERSITY OF ECONOMICS AND BUSINESS VIETNAM NATIONAL UNIVERSITY HANOI __000__ Sy GRADUATION THESIS EXAMINING THE CO-MOVEMENT BETWEEN CRYPTO POLICY UNCERTAINTY AND CBDC UNCERTAINTY Lecturer : PhD. Le Hong Thai Student : Nguyen Anh Duc ID Card : 20050424 Class : QH-2020-E TCNH CLC 1 Ha Noi - 2023 UNVERSITY OF ECONOMICS AND BUSINESS VIETNAM NATIONAL UNIVERSITY HANOI — = ` Co GRADUATION THESIS EXAMINING THE CO-MOVEMENT BETWEEN CRYPTO POLICY UNCERTAINTY AND CBDC UNCERTAINTY Lecturer : PhD. Le Hong Thai Student : Nguyen Anh Duc ID Card : 20050424 Class : QH-2020-E TCNH CLC 1 Ha Noi - 2023 DECLARATION I hereby declare that the thesis essay " Examining the co-movement between crypto policy uncertainty and CBDC uncertainty " is my own work. For the views that the thesis inherits from the preceding authors, it is extracted to clearly state the origin and the name of the author who made that thesis.
Ha Noi, October 31, 2023. Supervisor’s Approval Student Ph. Le Hong Thai Nguyen Anh Duc ii ACKNOWLEDGEMENTS To complete this graduate thesis, I would like to express my sincere gratitude to The University of Economics & Business - Vietnam National University, which has facilitated installations for information study with a modern library system and diverse books and documents. The Faculty of Finance and Banking teachers devoted themselves to teaching subjects connected to the topic, so I am well-informed and can effectively apply these ideas in my essay.
Foremost, I would like to express my sincere gratitude to my supervisor, PhD. Le Hong Thai, for his continuous support of my research, for his patience, motivation, enthusiasm, and immense knowledge. His guidance acknowledged and supported me in all the time of research and writing of this paper. I could not have imagined finishing this paper without having a better supervisor and mentor like PhD.
Le Hong Thai. There still needs to be more research experience and knowledge that constrains shortcomings in the thesis. I am looking for feedback, suggestions, and criticism from the teachers for the research to be improved. Lastly, I wish you good health, success, and happiness! Sincerely, Nguyen Anh Duc iii TABLE OF CONTENTS DECLARATION vt li ACKNOWLEDGEMENTS .cscssssssescsrsresesssesnsrsnenescessnsnsnsesnensessesnsesnsnsnencensesnsnenensessninsnsnsensnneninnnstsnennnnnnien Hi LIST OF FIGURES & TABLES ussssssssscsssesesesssseensesnsrscscsesessssnvscsssnseseseseusiessesnsnssnsesnseseenensensnsnseseiiene vi LIST OF ABBREVTA TÍN S.seseeneehshhhhnirrderkkieiirirsksrirarrsrsrxEsririitrrxrsrsrsrrrr vii 7;¬yy.
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THEORETICAL BASIS AND LITERATURE RE VTIE WW. Central Bank Digital Currency (CBDC). The Index of Cryptocurrency Environmental Attention (ICE. RESEARCH METHODOLOGY AND DATA uterine 22 3.
Research method - Biwavelet analySis. chanh” 23 iv CHAPTER 4. EMPIRICAL RESULTS AND DISCUSSION 001i 28 4. Results of the biwavelet aïnaÌYSÌS.
Summary Of Key fÏndÏngS. Policy and Investment implications. Research limitations and directions for future Studies.nesccsesssssssescncsesssssesessrensnsnsscssnensnensevssnsnsnenescscensesnensnenesvssnscsneneecevsnssnsesnsnsevsnnnsesnsnsnennanns 56 LIST OF FIGURES & TABLES Figure Page Figure 4. The movement of UCRY_Policy index from 2017 to 2022 28 Figure 4.
The movement of UCRY_Price index from 2017 to 2022 29 Figure 4. The movement of CBDC Uncertainty index from 2017 to 2022 30 Figure 4. The movement of CBDC Attention index from 2017 to 2022 31 Figure 4. The movement of ICEA index from 2017 to 2022 32 Figure 4.
The movement of NFT Attention index from 2017 to 2022 33 Figure 4. Wavelet coherence: UCRY Policy and CBDC Uncertainty 37 Figure 4. Wavelet coherence: UCRY Policy and CBDC Attention 39 Figure 4. Wavelet coherence: UCRY Price and CBDC Uncertainty 41 Figure 4.
Wavelet coherence: UCRY Price and CBDC Attention 43 Figure 4. Wavelet coherence: NFTs Attention and CBDC Uncertainty 45 Figure 4. Wavelet coherence: NFTs Attention and CBDC Attention 47 Figure 4. Wavelet coherence: ICEA and CBDC Uncertainty 49 Figure 4.
Wavelet coherence: ICEA and CBDC Attention 51 Table Page Table 4. Summary Statistics 34 Table 4. Correlation matrix 36 vi LIST OF ABBREVIATIONS CBDC Central Bank Digital Currency NFT Non-fungible tokens ICEA Index of Cryptocurrency Environmental Attention UCRY Uncertainty Cryptocurrency CBDCUI Central Bank Digital Currency Uncertainty index CBDCAI Central Bank Digital Currency Attention index vii ABSTRACT The aim of this paper is to investigate the dynamic co-movement between the cryptocurrency uncertainty indices (including UCRY Policy, UCRY Price, NFTs Attention, ICEA) and the CBDC uncertainty indices (i., CBDC Uncertainty and CBDC Attention). In doing so, we apply the wavelet coherence framework using daily data over the period from January 13, 2017, to December 30, 2022.
The empirical results reveal the co-movement between each cryptocurrency uncertainty indices with the attention for CBDC uncertainty indices. Overall, our findings suggest that the UCRY Policy is highly correlated with the CBDC Uncertainty in the medium and long-term, CBDC Attention in the short term. Which indicates that UCRY Policy can be used to predict the CBDC Uncertainty news. On the other hand, ICEA is shown to have relationships with CBDC Uncertainty indices historically in the long frequency.
Key words: UCRY Policy, UCRY Price, CBDC Uncertainty, CBDC Attention, ICEA, NFTs Attention, wavelet coherence. Research background We are living in a world marked by unpredictability. Over the past twenty years, numerous financial and political incidents have rocked the globe. These include the 2007 US financial crisis, the Eurozone’s sovereign debt crisis from 2010 to 2013, terrorist attacks in 2015, and Brexit in 2016.
More recently, global events such as the COVID-19 pandemic, the conflict in Ukraine, and the war between Palestine and Iran have direct global impacts. These successive events have underscored the significance of uncertainty as a critical factor in today’s economies, influencing the implementation of fiscal and monetary policies in financial markets and subsequently affecting the real economy. Given the close links between the various world markets (countries), there are many kinds of connections through which uncertainties in one market (country) can spread to others (Kang & Yoon, 2019). For example, several types of research show that the economic policy uncertainty index (EPU), which is developed by Baker et al.
(2016), has an impact on stock markets (Guo et al., 2018; Phan et al., 2020; Dai et al., 2021; Yuan et al., 2022), on commodities markets (You et al., 2017; Mokni et al., 2020; Chiang, 2021; Chiang, 2022), on real estate market (Xia et al., 2020) and countries economics (Jiang et al. For the past few years, the focus of researchers has shifted to the connectedness between Economic Policy Uncertainty and Cryptocurrency. A stream of research is how cryptocurrencies can act as diversifiers and hedging assets for Economic Policy Uncertainty (Demir et ai, 2018; Wu et al. On the other hand, periods of significant volatility in the cryptocurrency markets during critical events in the cryptocurrency area, e., the DeFi boom and attacks on cryptocurrency exchanges, also increase the attention and uncertainty in cryptocurrency markets (Lucey et al.
In addition to traditional financial assets, there is evidence that Economic Policy Uncertainty (EPU) significantly influences cryptocurrency volatility. Yen 2 and Cheng (2021) discover a negative correlation between Chinas EPU and cryptocurrency volatility, suggesting that Cryptocurrency could hedge against EPU risk. Mokni (2021) investigate the quantile causality in the EPU-cryptocurrency relationship and consider EPU a strong predictor in a bullish market. Rather than focusing on the EPU of a single country, Fang et al.
(2020) and Wu et al. (2022) study the impact of global EPU on cryptocurrency volatility, but their findings are inconclusive. Despite extensive research, there are gaps in the current literature on the EPU-cryptocurrency relationship. First of all, most studies have focused on the in- sample effects of EPU on cryptocurrency volatility.
In contrast, the out-of-sample predictive power of EPU on cryptocurrency volatility still needs to be verified. Secondly, the National EPU does not align with the super-sovereign nature of cryptocurrency as it may only affect a portion of cryptocurrency owners. This issue can be mitigated using global EPU, but the relationship between global EPU and cryptocurrency is unclear. Lastly, the EPU data is usually available at a relatively low frequency (i.
Lucey et al. (2021) recently present new indices for cryptocurrency policy and price uncertainty (UCRY Policy and UCRY Price) derived from an analysis of 726.9 million news articles. Lucey et al. (2021)’s research paper introduces a fresh perspective on the uncertainty in cryptocurrency markets.
They propose that the movements of UCRY indices differ from other risk and uncertainty indices such as the US Economic Policy Uncertainty (EPU), the Global EPU index, and the Volatility Index (VIX), potentially leading to distinct impacts on financial markets. Multiple studies have been conducted to test the effectiveness of Lucey et al. (2021) new indices for cryptocurrency policy and price uncertainty (UCRY Policy and UCRY Price) to predict the volatility of cryptocurrency. For example, Xia et al.
(2023) have used the new cryptocurrency uncertainty indices to predict the volatility of Bitcoin. The authors also compare the results of UCRY Uncertainty indices with EPU. They find out that the UCRY price index is the best-performing model, and forecasting models incorporating the UCRY indices outperform models with global and national EPUs in out-of-sample forecasting. Elsayed et al.
(2022) also adopt the 3 uncertainty indices to examine the dynamic connectedness of UCRY_Price and UCRY_Policy index with cryptocurrency returns and volatilities dynamics. The Crix data is adopted to test with uncertainty indices since it tracks the performance and volatility in the cryptocurrency market. The empirical findings show that the UCRY_Policy is the primary transmitter of return spillovers to other variables. This evidence shows the significant role of cryptocurrency policy uncertainty in cryptocurrency markets, highlighting the influence of the cryptocurrency policy uncertainty index.
In addition to research on the link between cryptocurrency uncertainty and other financial assets, another study considers the connectedness of CBDC Uncertainty with Cryptocurrency returns and volatility, as well as other uncertainty indices. Current research has regarded CBDC uncertainty as fully informative about future CBDC performance (Wang et al, 2022a). Uncertainty measures have become very popular in the literature because they can explain the risk premium of financial assets (Jurado et al., 2015) and their effects on the real economy (Bloom, 2009). The link between cryptocurrency uncertainty and central bank digital currency (CBDC) uncertainty has been examined in a study by Yousaf & Goodell (2023).
They find out that CBDC Uncertainty is a net recipient, while cryptocurrency policy uncertainty (UCRY Policy) and cryptocurrency price uncertainty (UCRY Price) are net transmitters. Most digital payment stocks are net recipients except for the three most significant: VISA, Mastercard, and American Express. Finally, net pairwise connectedness shows weak connectedness between uncertainties indices and digital payment stocks, consistent with the hedging capability of digital payment stocks against the uncertainties of CBDC and cryptocurrency markets. In another study, it is demonstrated that CBDC indices have a significant negative relationship with the volatilities of the MSCI World Banks Index, USEPU, and the FTSE All-World Index and cheerful with the volatilities of cryptocurrency markets, foreign exchange markets, bond markets, VIX, and gold.
These studies suggest a complex relationship between CBDC and cryptocurrency uncertainty, with implications for financial markets and digital payment stocks. Wang et al. (2022) develop CBDC uncertainty and attention indices using many news articles from the LexisNexis database. CBDC-related uncertainty and attention indices can have a strong relation with cryptocurrencies, and this could also have spillover effects on other asset classes.
Wang et al. (2022) adopt a dynamic conditional correlation (DCC) via AR (1)-GJR-GARCH (1,1) model find that CBDC uncertainty has a negative relationship with the MSCI World Banks Index, USEPU, and the FTSE All-World Index, and a positive relationship with cryptocurrency market volatility. Kamal et al. (2023) also used the CBDC Uncertainty.
In a world where cryptocurrency is becoming more globally recognized day by day, the focus is shifting to predicting the cryptocurrency uncertainty/volatility by indicators such as Geopolitical risk (Triki & Maatoug, 2022; Kamal et al., 2022) and Inflation (Batten et al., 2014; Wang et al, 2011; Gambarelli et al, 2023. However, the limitation in the connectedness research between Cryptocurrency Uncertainty and CBDC uncertainty still leaves us with questions.