Network interconnections among DeFi, NFTs, AI tokens, and renewable energy: driving factors, measurements, and portfolio implications

PurposeThis study aims to investigate the interconnectedness of sustainability-linked and AI-based cryptocurrencies returns and volatility over five years (2018–2024). It aims to uncover the dynamic relationships between these two sectors under various market conditions, providing insights into their behavior and influence within the broader cryptocurrency market.Design/methodology/approachThe research employs a Time-Varying Parameter Vector Autoregression (TVP-VAR) model to analyze key cryptocurrencies associated with AI and sustainability. This approach is complemented by a quantile-based perspective, allowing for an in-depth examination of return and volatility spillovers across different market conditions. Thus, facilitating an understanding of the intricate dynamics between sustainability-linked and AI-based cryptocurrencies.FindingsThe findings reveal distinct market dynamics with the Sustainable sector consistently acting as a net transmitter, while the AI sector predominantly as a net receiver, indicating its reactive nature. In bearish markets, both sectors display high interconnectedness, with the Sustainable sector shaping dynamics. In bullish markets, the Sustainable sector maintains influence, while the AI sector adopts a more proactive role, influencing the market more than in bearish conditions. Post-Chat GPT 3 the Sustainable sector decreases influence, becoming a net receiver in bullish markets. In contrast, the AI sector strengthens as a net transmitter, signaling growing investor confidence and prominence.Originality/valueThis study explores the interconnectedness of sustainability-linked and AI-based cryptocurrencies through a TVP-VAR model and a quantile-based analysis. It provides insights into how these sectors interact and influence each other across different market conditions, especially highlighting the significant shifts in dynamics following the advent of advanced technologies like Chat GPT 3. This contributes to a deeper understanding of the evolving landscape of the cryptocurrency market in the context of sustainability and AI.

ABSTRACTThis paper examines differences in the connectedness between exchange rates and stock prices for companies with different asset currencies on the Hong Kong stock market, and it seeks to explain those differences by proposing a hypothesis on asset-denominated currency difference. Under a framework of investor heterogeneity, we establish a dynamic, discrete theoretical model to analyse the connectedness between exchange rates, the stocks of local Hong Kong companies, the stocks of companies from the mainland and foreign exchange interventions. Using monthly data from January 2000 to August 2018, we adopt the time-varying parameter vector auto-regression (TVP-VAR) model to empirically study the dynamic relationships between exchange rates and the prices of both Hong Kong-based and mainland-based stocks. The results show significant differences in the ways that exchange rates and prices for the two types of stocks are linked. The exchange rates are positively correlated with mainland stocks and negatively correlated with Hong Kong stocks. Moreover, foreign exchange intervention is found to be an effective means for stabilising exchange rates, although such intervention tends to increase stock volatility.Abbreviations: TVP-VAR - time-varying parameter vector auto-regression model; MCMC - Monte Carlo-Markov Chain method.

In order to better demonstrate the relationship between agricultural economic structure growth and environmental pollution, an autoregressive model based on time-varying parameter vector was proposed. In the process of developing the research, this paper introduces the LDMI method, based on the time-varying parameter vector autoregression model, with the help of sampling formula calculation and other methods. Efforts were made to obtain credible conclusions. The experiment result shows that in this study, a total of 10,000 samples were taken. According to this value, 10000/116.15 = 86, which means that at least 86 unrelated samples can be obtained. Therefore, we can determine that each indicator mentioned in this paper has valid samples when it is introduced into the time-varying parameter vector autoregression (TVP-VAR) model for parameter estimation. After sampling detection image analysis and data calculation, the effect of energy structure, energy intensity industrial structure, and scale effect on the emission scale of environmental pollutants was obtained. It is proved that through the research of this paper, two main conclusions are finally obtained, and the influence of the five factors mentioned above is summarized.

This paper examines price discovery between bitcoin spot and futures using static measures, namely information share (IS), component share (CS), modified information share (MIS), information leadership share (ILS), impulse response, and a time-varying parameter vector autoregressive (TVP-VAR) model with stochastic volatility and Markov Chain Monte Carlo (MCMC) sampling algorithm. Our one-minute and daily datasets cover 16 months before and 16 months during the Covid-19 pandemic (November 2018 to June 2021). Our IS, CS, MIS and impulse response results indicate a stronger bitcoin spot leadership, whereas our ILS results point to a weaker bitcoin futures dominance, during the Covid-19 pandemic. We construe this, as far as microstructure noise is concerned, as meaning that the bitcoin price is discovered in the spot market, and its dominance appears to have strengthened during the pandemic. However, as far as ‘pure speed’ is concerned, price discovery takes place in the bitcoin futures market, and its leadership seems to have weakened during the Covid-19 pandemic. The results of the time-varying measure (TVP-VAR) imply that, before the pandemic, price discovery took place within bitcoin futures but, during the pandemic, price discovery leadership has changed course, to occur within bitcoin spot.

Purpose This study aims to examine the static and dynamic return and volatility spillovers between four main segments of nonfungible tokens (NFTs) (XTZ-Tezos, ENJ-EnjinCoin, MANA-Decentraland and THETA-Theta) and other assets [S&P Green Bond Index (GB), S&P Global Clean Energy Index (CEI), WTI-West Texas Intermediate-crude oil and Krane Shares Global Carbon Strategy ETF price (Krbn)]. Design/methodology/approach The time-varying parameter vector autoregression model is used to capture the time-varying relationships within these markets; the BEKK-GARCH model is used to calculate the hedge ratios, optimal weights and hedging effectiveness for portfolios pairing segments CEI/NFTs, Krbn/NFTs, GB/NFTs and WTI/NFTs. For robustness checks, the authors use Long Short-Term Memory (LSTM) networks to forecast the performance of both hedged and unhedged portfolios. Findings This static study reveals weak total connectedness among the markets. CEI is identified as a primary shock transmitter of return in the system, whereas ENJ, XTZ and THETA are receivers of volatility spillovers. According to the results of optimal weights, hedge ratios and hedging effectiveness, portfolio managers should add NFTs to portfolios to reap the diversification benefits; LSTM confirms the results. Originality/value This study is innovative in that it combines Krbn, GB, CEI, WTI and NFTs into a single, thorough analysis. However, the effects of these assets individually with NFTs have been examined in earlier studies. This study offers fresh perspectives on how NFTs might improve the financial portfolios’ effectiveness. It offers useful implications for investors and policymakers looking to advance sustainable financial practices.

The CEE stock markets are more and more integrated in the European financial markets. The growth of the integration of financial markets favours the volatility and return spillover between them. The current study analyses the volatility spillover among the stock markets in the countries from Central and East Europe (CEE) and Germany and France with the aim to identify the possibilities of reduction of a portfolio risk. A special attention is granted to the analysis during the pandemic caused by COVID-19. The time-varying parameter vector autoregressive (TVP-VAR) model on which is based the methodology proposed by Antonakakis and Gabauer (2017) is used to estimate the evolution in time of volatility spillover. The empirical results obtained for the period January 2001 – September 2021 highlight the increase in volatility spillover between the countries analysed when the pandemic caused by COVID-19 was confirmed. The lack of volatility integration of the markets analysed enables the making of arbitrages in order to reduce the risk of a portfolio. The results obtained are important in the management of financial asset portfolios.

This paper employs the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to analyze return and volatility spillovers, along with portfolio implications, across Green Bonds (GB), ESG stocks, the clean energy index (SP_CE), green cryptocurrencies (ADA, IOTA, XRP), Bitcoin (BTC), and gold. The study covers the COVID-19 pandemic and the Russia-Ukraine war. Results show a significant rise in total return and volatility connectedness during these crises, suggesting that global shocks heighten market interdependence. ESG stocks emerge as net transmitters of both return and volatility spillovers, while green cryptocurrencies (excluding ADA) are net receivers of volatility. Bitcoin exhibits asymmetric behavior—acting as a return transmitter but becoming a volatility receiver in crisis periods. Traditional assets such as gold, green bonds, and clean energy stocks remain net receivers in both return and volatility channels, underlining their defensive nature and potential role as hedging instruments during periods of turmoil.

Risk transmissions between bitcoin and traditional financial assets during the COVID-19 era: The role of global uncertainties

Time-varying impact of oil shocks on trade balances: Evidence using the TVP-VAR model

Economic policy uncertainty and stock market sector time-varying spillover effect: Evidence from China

Oil prices, policy uncertainty and travel and leisure stocks in China

There are spells in the world: incantations that can transform reality through the power of procedural utterances. The marriage vow, the courtroom sentence, the shaman’s curse: these words are codes that change reality. (Finn 90) Introduction As a child, stories on magic were “opportunities to escape from reality” (Brugué and Llompart 1), or what Rosengren and Hickling describe as being part of a set of “causal belief systems” (77). As an adult, magic is typically seen as being “pure fantasy” (Rosengren and Hickling 75), while Bever argues that magic is something lost to time and materialism, and alternatively a skill that Yeats believed that anyone could develop with practice. The etymology of the word magic originates from magein, a Greek word used to describe “the science and religion of the priests of Zoroaster”, or, according to philologist Skeat, from Greek megas (great), thus signifying "the great science” (Melton 956). Not to be confused with sleight of hand or illusion, magic is traditionally associated with learned people, held in high esteem, who use supernatural or unseen forces to cause change in people and affect events. To use magic these people perform rituals and ceremonies associated with religion and spirituality and include people who may identify as Priests, Witches, Magicians, Wiccans, and Druids (Otto and Stausberg). Magic as Technology and Technology as Magic Although written accounts of the rituals and ceremonies performed by the Druids are rare, because they followed an oral tradition and didn’t record knowledge in a written form (Aldhouse-Green 19), they are believed to have considered magic as a practical technology to be used for such purposes as repelling enemies and divining lost items. They curse and blight humans and districts, raise storms and fogs, cause glamour and delusion, confer invisibility, inflict thirst and confusion on enemy warriors, transform people into animal shape or into stone, subdue and bind them with incantations, and raise magical barriers to halt attackers. (Hutton 33) Similarly, a common theme in The History of Magic by Chris Gosden is that magic is akin to science or mathematics—something to be utilised as a tool when there is a need, as well as being used to perform important rituals and ceremonies. In TechGnosis: Myth, Magic & Mysticism in the Age of Information, Davis discusses ideas on Technomysticism, and Thacker says that “the history of technology—from hieroglyphics to computer code—is itself inseparable from the often ambiguous exchanges with something nonhuman, something otherworldly, something divine. Technology, it seems, is religion by other means, then as now” (159). Written language, communication, speech, and instruction has always been used to transform the ordinary in people’s lives. In TechGnosis, Davis (32) cites Couliano (104): historians have been wrong in concluding that magic disappeared with the advent of 'quantitative science.’ The latter has simply substituted itself for a part of magic while extending its dreams and its goals by means of technology. Electricity, rapid transport, radio and television, the airplane, and the computer have merely carried into effect the promises first formulated by magic, resulting from the supernatural processes of the magician: to produce light, to move instantaneously from one point in space to another, to communicate with faraway regions of space, to fly through the air, and to have an infallible memory at one’s disposal. Non-Fungible Tokens (NFTs) In early 2021, at the height of the pandemic meta-crisis, blockchain and NFTs became well known (Umar et al. 1) and Crypto Art became the hot new money-making scheme for a small percentage of ‘artists’ and tech-bros alike. The popularity of Crypto Art continued until initial interest waned and Ether (ETH) started disappearing in the manner of a classic disappearing coin magic trick. In short, ETH is a type of cryptocurrency similar to Bitcoin. NFT is an acronym for Non-Fungible Token. An NFT is “a cryptographic digital asset that can be uniquely identified within its smart contract” (Myers, Proof of Work 316). The word Non-Fungible indicates that this token is unique and therefore cannot be substituted for a similar token. An example of something being fungible is being able to swap coins of the same denomination. The coins are different tokens but can be easily swapped and are worth the same as each other. Hackl, Lueth, and Bartolo define an NFT as “a digital asset that is unique and singular, backed by blockchain technology to ensure authenticity and ownership. An NFT can be bought, sold, traded, or collected” (7). Blockchain For the newcomer, blockchain can seem impenetrable and based on a type of esoterica or secret knowledge known only to an initiate of a certain type of programming (Cassino 22). The origins of blockchain can be found in the research article “How to Time-Stamp a Digital Document”, published by the Journal of Cryptology in 1991 by Haber, a cryptographer, and Stornetta, a physicist. They were attempting to answer “epistemological problems of how we trust what we believe to be true in a digital age” (Franceschet 310). Subsequently, in 2008, Satoshi Nakamoto wrote The White Paper, a document that describes the radical idea of Bitcoin or “Magic Internet Money” (Droitcour). As defined by Myers (Proof of Work 314), a blockchain is “a series of blocks of validated transactions, each linked to its predecessor by its cryptographic hash”. They go on to say that “Bitcoin’s innovation was not to produce a blockchain, which is essentially just a Merkle list, it was to produce a blockchain in a securely decentralised way”. In other words, blockchain is essentially a permanent record and secure database of information. The secure and permanent nature of blockchain is comparable to a chapter of the Akashic records: a metaphysical idea described as an infinite database where information on everything that has ever happened is stored. It is a mental plane where information is recorded and immutable for all time (Nash). The information stored in this infinite database is available to people who are familiar with the correct rituals and spells to access this knowledge. Blockchain Smart Contracts Blockchain smart contracts are written by a developer and stored on the blockchain. They contain the metadata required to set out the terms of the contract. IBM describes a smart contract as “programs stored on a blockchain that run when predetermined conditions are met”. There are several advantages of using a smart contract. Blockchain is a permanent and transparent record, archived using decentralised peer-to-peer Distributed Ledger Technology (DLT). This technology safeguards the security of a decentralised digital database because it eliminates the intermediary and reduces the chance of fraud, gives hackers fewer opportunities to access the information, and increases the stability of the system (Srivastava). They go on to say that “it is an emerging and revolutionary technology that is attracting a lot of public attention due to its capability to reduce risks and fraud in a scalable manner”. Despite being a dry subject, blockchain is frequently associated with magic. One example is Faustino, Maria, and Marques describing a “quasi-religious romanticism of the crypto-community towards blockchain technologies” (67), with Satoshi represented as King Arthur. The set of instructions that make up the blockchain smart contracts and NFTs tell the program, database, or computer what needs to happen. These instructions are similar to a recipe or spell. This “sourcery” is what Chun (19) describes when talking about the technological magic that mere mortals are unable to comprehend. “We believe in the power of code as a set of magical symbols linking the invisible and visible, echoing our long cultural tradition of logos, or language as an underlying system of order and reason, and its power as a kind of sourcery” (Finn 714). NFTs as a Conceptual Medium In a “massively distributed electronic ritual” (Myers, Proof of Work 100), NFTs became better-known with the sale of Beeple’s Everydays: The First 5000 Days by Christie’s for US$69,346,250. Because of the “thousandfold return” (Wang et al. 1) on the rapidly expanding market in October 2021, most people at that time viewed NFTs and cryptocurrencies as the latest cash cow; some artists saw them as a method to become financially independent, cut out the gallery intermediary, and be compensated on resales (Belk 5). In addition to the financial considerations, a small number of artists saw the conceptual potential of NFTs. Rhea Myers, a conceptual artist, has been using the blockchain as a conceptual medium for over 10 years. Myers describes themselves as “an artist, hacker and writer” (Myers, Bio). A recent work by Myers, titled Is Art (Token), made in 2023 as an Ethereum ERC-721 Token (NFT), is made using a digital image with text that says “this token is art”. The word ‘is’ is emphasised in a maroon colour that differentiates it from the rest in dark grey. The following is the didactic for the artwork. Own the creative power of a crypto artist. Is Art (Token) takes the artist’s power of nomination, of naming something as art, and delegates it to the artwork’s owner. Their assertion of its art or non-art status is secured and guaranteed by the power of the blockchain. Based on a common and understandable misunderstanding of how Is Art (2014) works, this is the first in a series of editions that inscribe ongoing and contemporary concerns onto this exemplar of a past or perhaps not yet realized blockchain artworld. (Myers, is art editions). This is a simple example of their work. A lot of Myers’s work appears to be uncomplicated but hides subtle levels of sophistication that use all the tools available to conceptual artists by questioning the notion of what art is—a hallmark of conceptual art (Goldie

This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens (NFTs) and conventional currencies using the time-varying parameter vector autoregressions approach. We reveal that the total connectedness between these markets is weak, implying that investors may increase the diversification benefits of their multicurrency portfolios by adding NFTs. We also find that NFTs are net transmitters of both return and volatility spillovers; however, in the case of return spillovers, the influence of NFTs on conventional currencies is more pronounced than that of volatility shock transmissions. The dynamic exercise reveals that the returns and volatility spillovers vary over time, largely increasing during the onset of the Covid-19 crisis, which deeply affected the relationship between NFTs and the conventional currencies markets. Our findings are useful for currency traders and NFT investors seeking to build effective cross-currency and cross-asset hedge strategies during systemic crises.

This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens (NFTs) and conventional currencies using the time-varying parameter vector autoregressions approach. We reveal that the total connectedness between these markets is weak, implying that investors may increase the diversification benefits of their multicurrency portfolios by adding NFTs. We also find that NFTs are net transmitters of both return and volatility spillovers; however, in the case of return spillovers, the influence of NFTs on conventional currencies is more pronounced than that of volatility shock transmissions. The dynamic exercise reveals that the returns and volatility spillovers vary over time, largely increasing during the onset of the Covid-19 crisis, which deeply affected the relationship between NFTs and the conventional currencies markets. Our findings are useful for currency traders and NFT investors seeking to build effective cross-currency and cross-asset hedge strategies during systemic crises.

In this study, the volatility spillover between metaverse tokens is investigated to guide investors. In the research, price data of Decentraland, StarLink, Axie Infinity, Radio Caca, The Sandbox, Internet Computer, My Neighbor Alice and Enjin Token, for the period 12.14.2021-10.22.2023 analyzes with the time-varying parameter vector autoregressive (TVP-VAR) model developed by Antonakakis et al. (2019). As a result of the research, it determine that Radio Caca and Axie Infinity only receive volatility; My Neighbor Alice and Enjin Token only spread volatility; StarLink, Decentraland and Internet Computer are metaverse tokens that both receive and spread volatility.