Token Price Research Articles

CroCoDai : A Stablecoin for Cross-Chain Commerce

Decentralized Finance (DeFi), in which digital assets are exchanged without trusted intermediaries, has grown rapidly in value in recent years. Stablecoins , which are pegged to a non-volatile asset such as the US dollar, are a prominent feature of DeFi as they mitigate the risk associated with price fluctuations. However, existing stablecoin systems are tied to individual blockchain platforms, and trusted parties or complex protocols are needed to exchange stablecoin tokens between blockchains. Our goal is to design a practical stablecoin system for cross-chain commerce, and to do so we must overcome two main challenges. The first is to support a large and growing number of blockchains efficiently. The second is for the stablecoin to be resilient to blockchain platform failures and to price fluctuations that affect its collateral. We present CroCoDai to address these challenges. We demonstrate CroCoDai 's efficiency by comparing the performance of a prototype implementation to related baselines, and its resilience through an empirical analysis of historical token price data.

Blockchain Tokens, Price Volatility, and Active User Base: An Empirical Analysis Based on Tokenomics

Blockchain tokens have accumulated tremendous market value but remain highly controversial, given their price volatility and seemingly speculative nature. Ironically, this very characteristic can foster token retention as users wait for occasions of appreciation. In this paper, we conduct an empirical analysis with 58 tokens in two steps: first, an investigation of the drivers of user activity and token price volatility using a new blockchain token classification framework, searching for possible tokenomics links. Our findings suggest that there is an intrinsic relationship between the way tokens are used as a means of exchange and how token usage dynamics influence user engagement oppositely to market stability. Only some features, such as earning potential and voting rights, foster token-holding strategies, while only Ethereum ecosystem membership has positive effects on price volatility. Second, we analyze the direct relationship between price volatility and active users. Results show that, on average, a 10% increase in volatility is related to a decrease in active addresses ranging between 3.96% and 5.88%. The finding is supportive of the hypothesis that token price volatility may be treated as an opportunity to increase token retention.

A robust financing theory of ICOs under demand uncertainty of products of token platforms

PurposeThe market products produced by Initial Coin Offerings (ICO) platforms are often relatively new and have no previous transaction records and therefore are hard to estimate for its demand. The purpose is to study the impacts of the degree of ambiguity aversion of entrepreneurs to demand uncertainty on the ICO financing ratio, the optimal expected output, the optimal efforts and the token price.Design/methodology/approachIn an optimal ICO design, we introduce demand uncertainty of the product and establish a robust optimization method to solve the ICO optimal design. We compare ICO financing and the general venture capital (VC) financing model. We analyze the impact of demand uncertainty on the optimal ICO financing ratio.FindingsFindings include that the ICO financing ratio is positively related to the degree of ambiguity aversion, the token price is negatively related to the degree of ambiguity aversion and the “ambiguity premium” exists in the ICO market, the optimal effort levels are negatively related with the ICO financing ratio, but positively related with token price, and in the environment of high production cost, VC financing is not as good as ICO financing.Originality/valueWe develop a robust ICO financing model by assuming that the entrepreneur is ambiguity aversive to the demand uncertainty. Analyze the impact of the degree of ambiguity aversion on the ICO financing ratio in theory and find that the entrepreneur can raise funds with the higher ICO token ratio when she has a larger degree of ambiguity aversion to the demand uncertainty. Extend the impact analysis of the degree of ambiguity aversion on the expected token price and find a negative relationship between the expected token price and the degree of ambiguity aversion of the entrepreneur to the demand uncertainty.

Quantum Neural Network model for Token allocation for Course Bidding

Quantum computer has shown the advantage over the classical computer to solve some problems using the laws of quantum mechanics. With a combination of knowledge of machine learning and quantum computing, Quantum neural networks adapted the concept from classical neural networks and apply parameterized quantum gates as neural network weights. In this paper, we present an application of quantum neural networks with real-world data to predict token price used in a course bidding system. The experiments were carried out on the Qiskit quantum simulator. The result shows that quantum neural networks can achieve a good prediction result compared to the classical neural network. The best model configuration has the lowest RMSE 6.38%. This approach opens an opportunity to explore the benefit of quantum machine learning in many research fields in the future.

Metaverse token price forecasting using artificial neural networks (ANNs) and Adaptive neural fuzzy inference system (ANFIS)

Metaverse token price forecasting using artificial neural networks (ANNs) and Adaptive neural fuzzy inference system (ANFIS)

Pool competition and centralization in PoS blockchain network

ABSTRACT In Proof-of-Stake (PoS) blockchain network, stakeholders spend tokens for consumption while competing for network transaction fee with unspent tokens. Stakeholders are incentivized to form staking pools to compete with each other, but continued staking pool merge does not occur given fixed pool operating cost. Unlike other blockchain networks and traditional payment systems, token price in PoS blockchain network is a direct result of competition among service providers (staking pools) and is strongly positively correlated with network decentralization level. As an extension, we show that uneven wealth distribution or biased validator selection function enhances stake centralization and sabotage token price.

Robust adoption and valuation in tokenomics

This paper incorporates model uncertainty into the dynamic token-based platform adoption and valuation theory. We find that ambiguity slows down the tokenized platform adoption since users with the belief distortion tend to prevent the perturbation of the platform productivity, thus weakening the appreciation of the expected token price and the decline of the token carry cost due to the user-base growth. Moreover, as concerns regarding model uncertainty induce a trade-off between token price appreciation expectation and ambiguity hesitation, comparing the adoption speeds in the robust tokenized economy and the tokenless economy depends on the severity of the ambiguity aversion. Finally, ambiguity amplifies the user-base volatility of the tokenized economy, which, however, is still lower than that of the tokenless economy.

Development Trajectory of Blockchain Platforms: The Role of Multirole

Understanding the development trajectory of digital platforms is central to digital platform management. We develop a parametric model that investigates the development trajectories of blockchain platforms, accounting for the feedback between blockchains’ utility change and people’s adoption and abandonment behavior. We consider a typical blockchain participant to simultaneously play three roles on the platform, user, investor, and laborer, each contributing to blockchains’ multi-faceted utility: providing service for transaction/interaction, providing a medium for digital investment, and providing workspace for online labor. The model describes a three-phase development trajectory for blockchain platforms: a chaotic initial stage, a rapid growth stage, and a mature stage of stable market cycles. The model was used to match 112 token price series, demonstrating robust performance across different fitting setups and outperforming existing models. The study identifies two temporal parameters, the time delay in quitting the platform and the holding time of the platform’s token, that significantly differentiate blockchains’ development trajectories. We extend the model to study forking events; results suggest that fork launch time is more important than forking amplitude in influencing the main chain’s subsequent development and that forking can increase the exposure of the forked platform.

A Model of Cryptocurrencies

We model cryptocurrencies as utility tokens used by a decentralized digital platform to facilitate transactions between users of certain goods or services. The network effect governing user participation, in conjunction with the nonneutrality of the token price, can cause the token market to break down. We show that token retradeability mitigates this risk of breakdown on younger platforms by harnessing user optimism but worsens this fragility when sentiment trading by speculators crowds out users. Elastic token issuance mitigates this fragility, but strategic attacks by miners exacerbate it because users’ anticipation of future losses depresses the token’s resale value. This paper was accepted by Agostino Capponi, Special Section of Management Science: Blockchains and Crypto Economics.

Token Incentives in a Volatile Crypto Market: The Effects of Token Price Volatility on User Contribution

ABSTRACT Crypto tokens, issued and managed via smart contracts, function as rewards in blockchain systems to encourage user participation. Distinct from monetary incentives, token incentives are uncertain in reward magnitude due to the large swings in token prices on crypto markets. By focusing on token price volatility, this study investigates how the reward uncertainty affects user contribution in a tokenized digital platform. Our empirical setting is Steemit, a platform where bloggers write posts and share token rewards based on their posts’ popularity. We find that while high token price volatility induces a large volume of blog posts, it diminishes post quality. The dichotomous effects are explained via two mechanisms: users’ direct reactions to reward uncertainties and their indirect reactions, mediated by altered token preference amid volatility shocks. Deeply exploring this dynamic process, our results reveal that token price volatility facilitates a platform’s network short-term effect but impairs long-term user creativity. Our empirical findings thus extend the literature on blockchain economics and cryptocurrencies and have practical implications for the design of incentive mechanisms on tokenized digital platforms.

The Flash Loan Attack Analysis (FAA) Framework—A Case Study of the Warp Finance Exploitation

Decentralized finance (DeFi) has exploded in popularity with a billion-dollar market cap. While uncollateralized lending, known as a flash loan, emerged from DeFi, it has become a primary tool used by attackers to drain investment tokens from DeFi networks. The existing countermeasures seem practical, but no comprehensive quantitative analysis framework was available to test them. This paper proposes the Flash loan Attack Analysis (FAA) framework, which aids security practitioners in understanding the DeFi system’s effects on preventative methods when various factors change. The quantitative predictions can help security professionals in identifying hidden dangers and more efficiently adopting countermeasure strategies. The simulation predicts that the existing strategy, fair reserves, can fully protect the platform in a typical market environment; however, in a highly volatile market where the token price drops by 60% in a single hour, it will be broken, causing more than $8 million in damage.

What do institutional investors bring to initial coin offerings (ICOs)?

Blockchain technology has attracted global attention for its ability to protect data security and traceability. It has driven the development of practical applications in various fields, namely management science, transport and logistics, and supply chain management. Initial coin offerings (ICOs), an emerging start-up fundraising method developed with blockchain technology, are now popular among start-ups that issue initial tokens as the sole exchange medium for their planned products. In addition to the public offering stage and market stage, the pre-ICO stage is an important phase for many ICO projects.In this paper, we establish an initial coin offering (ICO) model with network effects, a common phenomenon in ICOs, to study the effect of institutional investors’ participation in the pre-ICO stage of offerings made by cash-strapped entrepreneurs. We find that introducing institutional investors significantly increases the equilibrium price of tokens during the public offering stage as well as the price fluctuation of tokens over time. Meanwhile, entrepreneurs will over-issue tokens when the intensity of network externality is relatively high. Interestingly, when institutional investors’ required rate of return decreases, the change in the optimal issuance is not monotonic. Under some circumstances, the lower the rate of return required by institutional investors is, the less the optimal issuance to them is, even if the network externality is high. A higher issuance in the pre-ICO stage is thus a mixed blessing that can increase the price during public offerings and reduce the equilibrium price in other stages. The negative impact is even greater when network externality is high.

Optimal initial coin offering under speculative token trading

Initial Coin Offering (ICO) is a new form of financing instrument for start-up firms. The firm issues tokens (or coins) in the ICO phase to raise capital to build capacity for its project. If the project is successful, the firm will provide product in subsequent periods and this product can only be accessed via tokens which can be traded over an exchange market. In this paper, we propose a model to study the firm’s optimal ICO strategy and the equilibrium token price dynamics when there is a multi-period trading market for tokens. We find that the ICO will be successful if and only if the capacity-cost-to-customer-valuation ratio is low. There may also exist multiple equivalent ICO decisions that yield the same revenue for the firm. We also compared the ICO mechanism with the traditional bank-financing mechanism. We find that when the capacity cost is low, the ICO mechanism is better than the bank-financing mechanism. We also explore the impact of the speculator’s risk attitude on the firm’s profitability. In general, the firm will be better-off when the speculator (those who participates in the ICO and trades tokens) is more risk-seeking.

Valor y precio de los Non-Fungible Tokens (NFTs) un estudio bibliométrico

Propósito. Esta investigación tiene como objetivo identificar la literatura científica existente en torno al valor y precio de los NFTs.
 Metodología. La metodología utilizada en el presente artículo consta de un análisis bibliométrico, se usa la base de datos Scopus desde la primera aparicion de un artículo hasta la actualidad.
 Hallazgos. Los resultados muestran que existe muy poca literatura científica entorno al valor y precio de los NFTs, se logró identificar ocho artículos, en donde solamente tres contribuyen en su totalidad a la descripción de las variables valor y precio, además se encuentran variables incidentes en el valor y precio de los NFTs lo que llevaría a tener el potencial de generar nuevo conocimiento en este ámbito, realizar propuestas teóricas en modelos de valuación y precio para estos activos. Originalidad.La investigación se realizó considerando solamente a la base de datos Scopus utilizando el software VosViewr, se recomienda para futuras investigaciones tomar en cuenta otras bases de datos.

Token-based platform finance

We develop a dynamic model of a platform economy where tokens serve as a means of payment among platform users and are issued to finance investment in platform productivity. Tokens are optimally rewarded to platform owners when token supply (normalized by productivity) is low and burnt to boost franchise value when the normalized supply is high. Although token price is determined in a liquid market, the platform’s financial constraint generates an endogenous token issuance cost that causes underinvestment through the conflict of interest between insiders (owners) and outsiders (users). Blockchain technology mitigates underinvestment by addressing the owners’ time inconsistency problem.

Value of Initial Coin Offerings in the Fashion Industry

In our model, a venture seeks capital through an initial coin offering (ICO). The ICO enables the venture to collect demand information from decentralized investors. The venture makes a tradeoff between ensuring the project’s success and forecasting market demand through token size and token price. We find that the higher the demand uncertainty and production cost, the greater the venture’s incentive to learn from its investors. To identify when the venture has an incentive to raise funds through an ICO, we compare it with traditional bank financing and analyze the venture’s preference between the two financing options. The results show that when demand uncertainty is high, an ICO can provide both financing and information benefits, whereas when demand uncertainty is low, although the venture does not collect information through an ICO, it can still get financing benefit. Only when demand uncertainty is intermediate, the venture prefers bank financing. In addition, we find that although the revenue sharing effect of the ICO results in an underinvestment issue, it can also alleviate the loss caused by the increased cost of production. Therefore, with high information accuracy, as production cost goes up, ICOs become more attractive than bank financing for the venture.

What Do Institutional Investors Bring to Initial Coin Offerings(ICOs)?

[Blockchain technology has attracted global attention due to its capabilities in protecting data security and traceability. This has driven the development of practical applications in various fields, particularly in management science, transport and logistics, and supply chain management. Initial coin offerings (ICOs), an emerging start-up fundraising method developed with blockchain technology, are now popular among start-ups that issue initial tokens as the sole exchange medium for their planned products. In addition to the general ICO, the pre-ICO stage is an important phase of many ICO projects. This paper establishes an ICO model with network effects, a common phenomenon in ICOs, to study the effect of institutional investors' participation in the pre-ICO stage of offerings made by cash-strapped entrepreneurs. We find that introducing institutional investors helps mitigate the financing pressure and maintain the total amount of tokens in circulation at a relatively stable level when the initial investment is relatively high. Meanwhile, introducing institutional investors significantly increases the equilibrium price of tokens during the public offering stage and increases the price fluctuation of tokens over time. In addition, we find that the entrepreneur will over-issue tokens when the intensity of network externality is relatively high. Furthermore, we investigate the effect of the entrepreneur's private quality information over the consumers. We find that an entrepreneur that expects high product quality in the future may give up public offering because signaling quality by introducing institutional investors may be inefficient.]

ITO: The Sponsored Token Technology

Blockchain technology can be made more efficient with an incentive mechanism using tokens. This paper proposes an innovative method of initial token offerings (ITO), allowing issuers such as the government to sponsor and implement policy targeted at specific products, projects or technology. Sponsor’s qualifications can gradually be relaxed and guided by a pre-determined process. With a combination of call auctioning and commanding price (CP) determination, the initial issue price is fixed by the sponsor and ultimately by the consensus of all stakeholders. This approach ensures that the initial token price is non-zero at launch and leaves room for revaluation in line with subsequent development of the project or technology. ITO can attract more enterprises, teams and individuals to participate in the innovation activities of critical projects or technological breakthroughs by reducing their economic costs and risks, thus accelerating project collaboration. It also combines a conducive regulatory environment and market forces to achieve flexibility and effective management of technological innovations.

Tokenomics and Platform Finance

We develop a dynamic model of platform economy where tokens serve as a means of payments among platform users and are issued to finance investment in platform productivity. Tokens are optimally issued to reward platform owners when the productivity-normalized token supply is low and burnt to boost the franchise value when the productivity-normalized normalized supply is high. Although token price is determined in a liquid market, the platform’s financial constraint generates an endogenous token issuance cost, causing underinvestment through the conflict of interest between insiders (platform owners) and outsiders (users). Blockchain technology mitigates underinvestment by addressing the platform’s time-inconsistency problem. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Tokenomics: Dynamic Adoption and Valuation

Abstract We develop a dynamic asset pricing model of cryptocurrencies/tokens that allow users to conduct peer-to-peer transactions on digital platforms. The equilibrium price of tokens is determined by aggregating heterogeneous users’ transactional demand, rather than discounting cash flows as is done in standard valuations models. Endogenous platform adoption builds on user network externality and exhibits an $S$-curve: it starts slow, becomes volatile, and eventually tapers off. The introduction of tokens lowers users’ transaction costs on the platform by allowing users to capitalize on platform growth. The resultant intertemporal feedback between user adoption and token price accelerates adoption and dampens user-base volatility.