Study characterizes Uniswap v3 liquidity pools using transaction graphs and identifies ideal trading conditions.
problem Computational expense in analyzing the full Uniswap v3 ecosystem.
method Extracted and analyzed a sub-universe of liquidity pools, using transaction graphs and graph2vec algorithm.
result Identified seven clusters of liquidity takers with similar trading preferences and introduced an ideal crypto law.
Study laws of cosines and sines for hyperbolic shapes with ideal vertices.
problem Formulating trigonometric laws for shapes with ideal vertices in hyperbolic geometry.
method Using hyperboloid model and Lorentzian geometry, establishing laws for quadrilaterals, pentagons, and partially truncated tetrahedra.
result Transversal lengths of partially truncated tetrahedra depend only on internal edge lengths at ideal vertices.
This paper explains tax policy for crypto assets in a rapidly evolving tech landscape.
problem Rapid technological changes in crypto assets create regulatory and tax policy blind spots.
method Explains principles of crypto assets, their technology, and tax issues.
result Tax policies are lagging behind innovation in blockchain and crypto.
Algorithm recommends trades based on crypto asset prices and market conditions.
problem Optimizing trades in volatile crypto markets to minimize gas fees and slippage.
method Cascading Waterfall Round Robin Mechanism considering gas fees and slippage.
result Algorithmic approach reduces market noise and ensures sound trade execution.
Despite being described as a medium of exchange, cryptocurrencies do not have the typical attributes of a medium of exchange. Consequently, cryptocurrencies are more appropriately described as crypto assets. A common investment attribute shared by the more than 2,500 crypto assets is that they are highly volatile. An i…
Formulates Hilbert reciprocity law on 3-manifolds.
problem Developing arithmetic topology on 3-manifolds.
method Formulated an analogue of Hilbert reciprocity law using intersection forms and Kummer extensions.
result Cyclic covers of links are analogues of Kummer extensions.
Investors prioritize ESG in crypto-assets, showing higher exposure than traditional assets.
problem Understanding ESG preferences in crypto-assets and their investment behavior.
method A representative household finance survey in Austria to examine ESG preferences and crypto-investment exposure.
result ESG-conscious investors have higher exposure to crypto-assets compared to traditional asset classes.
The DAO Report led to a significant shift of ICO activity to Europe.
problem The impact of U.S. regulatory changes on global ICO activity.
method Analysis of a global dataset of ICOs from 2014 to 2021, focusing on the DAO Report's effects.
result A substantial and persistent reallocation of ICO activity to Europe following the DAO Report.
This study links blockchain design to cryptos' distributional characteristics.
problem Understanding the relationship between blockchain design and cryptos' distributional characteristics.
method Used spectral clustering to cluster cryptos based on their blockchain mechanisms and operational features.
result Clusters of cryptos share similar blockchain mechanisms, supporting the hypothesis.
Estimates crypto risk premia using hidden factors and finds significant integration with traditional markets.
problem Estimating risk premia in cryptocurrency returns.
method Giglio-Xiu (2021) three-pass approach, controlling for latent factors and non-tradable state variables.
result Latent factors significantly impact crypto returns, highlighting the importance of controlling for unobserved risks.
Analyzes intrinsic time in financial markets, linking it to physical time.
problem Understanding the intrinsic nature of time in financial data.
method Presented an analytic relationship linking intrinsic and physical time, using empirical scaling laws.
result A novel empirical scaling law relating intrinsic time variability to overshoots.
We show that there is a common mode of origin for the power laws observed in two different models: (i) the Pareto law for the distribution of money among the agents with random saving propensities in an ideal gas-like market model and (ii) the Gutenberg-Richter law for the distribution of overlaps in a fractal-overlap …
This paper analyzes crypto white papers under MiCAR, highlighting NLP's role.
problem Regulatory changes in crypto white papers under MiCAR.
method Survey of existing NLP applications, analysis of MiCAR changes.
result NLP can assist in regulatory compliance and white paper analysis.
We propose a modelling framework for the optimal selection of crypto assets. Crypto assets differ by two essential features: security (technological) and stability (governance). Investors make choices over crypto assets similarly to how they make choices by using a recommender app: the app presents each investor with a…
Study shows SEC crypto classification led to significant market reactions.
problem Impact of SEC classification of crypto assets as securities.
method Event study methodology focusing on explicitly named crypto assets.
result Significant adverse market reactions, with returns plummeting 12% over one week.
This paper analyzes Ethereum blockchain using topology and geometry to uncover crypto-token price dynamics.
problem Lack of understanding on crypto-token price dynamics from blockchain data.
method Topological data analysis and functional data depth.
result Ethereum blockchain provides insights into crypto-token price dynamics not accessible with conventional methods.
New framework detects crypto wash trading using liquidity measures.
problem Detecting and monitoring wash trading in crypto assets.
method Developed a new framework to detect wash trading through real-time liquidity fluctuation measures.
result Joint elevation in liquidity jump and diffusion indicates wash trading in crypto assets.
Coding collaborations link crypto returns, revealing systemic transparency.
problem Cryptocurrencies' market behavior overlooked due to isolated code approach.
method Analyzed 4% of developers contributing to multiple cryptocurrencies.
result First coding event linking two cryptocurrencies synchronizes their returns.
ChatGPT launch boosted AI-related crypto assets by 10.7% to 15.6%.
problem Investor perception of AI assets after ChatGPT launch.
method Synthetic difference-in-difference methodology.
result AI-related crypto assets experienced significant returns after ChatGPT launch.
We explore inverse and quanto inverse crypto options, their pricing, and applications.
problem Market incompleteness in crypto options trading.
method Comparison of direct and inverse options, and introduction of currency-protected 'quanto' options.
result Pricing and hedging characteristics of inverse and quanto inverse options in a Black-Scholes framework.
Method tracks change-points in crypto-assets extremes.
problem Tracking change-points in multivariate extremes.
method Statistical method for modeling change-points on crypto-assets extremes.
result Developed a method to track crypto-assets extremes.
Study reveals jumps in crypto markets predict future prices.
problem Understanding jumps in high frequency digital asset markets.
method High frequency crypto data analysis, econometric modeling.
result Intra-day jumps significantly influence end of day returns.
Crypto-assets perform better than gold as safe-havens during market crashes.
problem Evaluating safe-haven properties of crypto-assets and gold during the 2020 market crash.
method Comparative analysis of Crypto-assets (Tether, Cardano, Dogecoin, Bitcoin, Ethereum, Litecoin, Ripple) and gold for European indices.
result Tether, Cardano, and Dogecoin exhibited hedging properties similar to gold, while gold was not more efficient as a safe-haven.
Study shows how crypto asset liquidity is affected by wash trading and proposes treatment to reduce liquidity diffusion.
problem Understanding and reducing crypto asset wash trading to improve liquidity.
method Proposed a two-component model for liquidity (jump and diffusion) and demonstrated the effectiveness of autoregressive models.
result Treatment on wash trading significantly reduces liquidity diffusion but not liquidity jump.
Argentum is a crypto coin for saving and investment in unstable countries.
problem Stable purchasing power for savings in unstable economies.
method Designing a crypto coin backed by investment instruments.
result Provides a stabilization instrument for savings in unstable economies.
SVAR-LiNGAM reveals causal order in crypto-asset markets.
problem Understanding the causal relationships between spot rates and crypto-assets.
method Applied SVAR-LiNGAM to analyze spot exchange rates and crypto-asset exchange rates.
result Causal order found: EUR_USD spot rate -> Bitcoin -> Ethereum -> Ripple.
Study models crypto markets using multi-agent reinforcement learning.
problem Emulating crypto market dynamics and behaviors.
method Multi-agent reinforcement learning (MARL) with RL techniques.
result Model accurately emulates crypto market microstructure and behaviors.
A computational model for the distribution of wealth among the members of an ideal society is presented. It is determined that a realistic distribution of wealth depends upon two mechanisms: an asymmetric flux of wealth in trading transactions that advantages the poorer of the two traders and a non-stationary creation …
Study finds strong link between crypto narratives and prices.
problem Understanding the impact of crypto narratives on prices.
method Topic modeling of Twitter data combined with sentiment analysis.
result Strong correlation between narratives and crypto prices.
We consider an ideal closed stock market, in which 100 traders have economic activities. The assets of the traders change through buying and selling stocks. We simulate the assets under conservation of both total currency and total number of stocks. If the traders are identical, then the assets are distributed as a sta…
Quantum crypto-economics models price risks in blockchain technology.
problem Quantum technology's potential to undermine blockchain security.
method Building financial models to price quantum risk in blockchain scenarios.
result Quantum crypto-economics models can assess and price quantum risks in blockchain.
Study reveals structure of Bitcoin's crypto flow network.
problem Understanding crypto flows among Bitcoin users.
method Blockchain data, user identification, network construction, bow-tie structure, Hodge decomposition, non-negative matrix factorization.
result Users are located in upstream, downstream, and core of the crypto flow network.
The effects of saving and spending patterns on holding time distribution of money are investigated based on the ideal gas-like models. We show the steady-state distribution obeys an exponential law when the saving factor is set uniformly, and a power law when the saving factor is set diversely. The power distribution c…
New framework predicts crypto volatility, outperforming traditional models.
problem Forecasting volatility in cryptocurrencies during the crypto-winter.
method Combines LSTM and rough volatility models, using a parsimonious parametric model.
result Similar prediction performances with fewer parameters, suggesting universality of volatility mechanisms.
Crypto markets show negative spillovers between chains, not positive co-movements.
problem Negative spillovers in crypto asset returns across different blockchains.
method On-chain data from multiple blockchains (Ethereum, Solana, Binance, Arbitrum, Avalanche) analyzed over 2022-2025.
result Surges on one chain often coincide with declines on others, especially during attention shocks.
Bitcoins have emerged as a possible competitor to usual currencies, but other crypto-currencies have likewise appeared as competitors to the Bitcoin currency. The expanding market of crypto-currencies now involves capital equivalent to 1010 US Dollars, providing academia with an unusual opportunity to study the em…
Gamification enhances law enforcement training on terrorism financing.
problem Complex technologies limit engagement in fighting cyber-criminal activities.
method Combining learning and training methods with gamification.
result Participants show increased expertise and positive feedback.
The year 2017 saw the rise and fall of the crypto-currency market, followed by high variability in the price of all crypto-currencies. In this work, we study the abrupt transition in crypto-currency residuals, which is associated with the critical transition (the phenomenon of critical slowing down) or the stochastic t…
Crypto simulations show HODL strategy loads risk onto most investors, with macro-sentiment affecting returns.
problem Understanding real risk-return trade-offs and factors affecting crypto returns.
method Two independent analyses: 480 million Monte Carlo simulations and Bayesian multi-horizon local projection framework.
result HODL strategy exposes most investors to extreme downside risk, and macro-sentiment conditions are dominant indicators for future outcomes.
This paper develops a new framework to assess crypto portfolio risk using simulation methods.
problem Traditional financial risk models fail to capture crypto market characteristics like volatility and contagion.
method The framework integrates four components: volatility stress testing, hedging, contagion modeling, and Monte Carlo simulation.
result The framework robustly assesses crypto portfolio risk and is validated with real data.
Study examines how crypto arbitrage affects XRP price and network correlation.
problem Impact of crypto arbitrage on XRP price and network correlation.
method Examined XRP price fluctuations and correlation tensor spectra of transaction networks across crypto exchanges.
result Arbitrage opportunities across crypto exchanges anti-correlate with XRP price during bubble periods.
Research identifies four motivational groups for crypto-metaverse landowners.
problem Understanding motivations of retail investors in the crypto-metaverse.
method Detailed financial behavior survey and principal components analysis.
result Four distinct motivational groups identified: Aesthetics, Social, Speculation, Innovation.
We analyze an ideal gas like models of a trading market. We propose a new fit for the money distribution in the fixed or uniform saving market. For the marketwith quenched random saving factors for its agents we show that the steady state income (m) distribution P(m) in the model has a power law tail with Pareto in…
We discuss the ideal gas like models of a trading market. The effect of savings on the distribution have been thoroughly reviewed. The market with fixed saving factors leads to a Gamma-like distribution. In a market with quenched random saving factors for its agents we show that the steady state income (m) distributi…
Study finds Binance's tether-margined contracts significantly impact bitcoin volatility.
problem Understanding volatility transmission in the crypto market, especially through Binance.
method Analyzing high-frequency realised volatility dynamics and spillovers in bitcoin market pairs.
result Binance's tether-margined contracts are the primary source of volatility and transmit strong flows.
We consider the ideal-gas models of trading markets, where each agent is identified with a gas molecule and each trading as an elastic or money-conserving (two-body) collision. Unlike in the ideal gas, we introduce saving propensity λ of agents, such that each agent saves a fraction λ of its money and trades with t…
Reinforcement learning crypto agent achieves high returns on Bitcoin derivatives.
problem Maximizing returns on volatile cryptocurrency markets.
method Online transfer learning with an echo state network and recurrent reinforcement learning.
result Achieves a total return of 350%, net of transaction costs, over five years.
Paper uses AI to optimize crypto portfolios, showing better risk-adjusted returns.
problem Managing volatile crypto markets with high volatility.
method Multi-agent system designed to autonomously construct and evaluate crypto-asset allocations.
result Dynamic optimization strategy outperforms static equal weighting strategy in terms of risk-adjusted returns.