Research predicts XRP price anomalies using graph topologies.
problem Forecasting extreme price movements in XRP cryptoasset.
method Analyzed topological features of XRP transaction graphs.
result Topological features indicate extreme price surges.
On-device research index
arXiv research
A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
168,695 papers · 148 categories
Trend · papers per month
25 results for “XRP cryptoasset”
Dynamic relationship between XRP price and correlation tensor spectra of the transaction networkq-fin.ST
Study shows XRP price correlates with transaction network metrics.
problem Understanding the relationship between cryptoasset price and network metrics.
method Analysis of correlation tensor spectra, random matrix theory comparison, singular values investigation.
result Distinct correlation between XRP price and singular values during bubble and non-bubble periods.
The study analyzes XRP transaction networks to understand market dynamics.
problem Understanding market dynamics of XRP through transaction data.
method Weekly weighted directed networks are embedded into a vector space using network embedding techniques. A correlation tensor is calculated and analyzed using singular value decomposition.
result The correlation tensor provides insights into the system's behavior and dependence on model parameters.
Arbitrage impact on the relationship between XRP price and correlation tensor spectra of transaction networksphysics.soc-ph
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.
Study XRP network, propose Flow Index to analyze transaction frequencies.
problem Analyze transaction frequencies in XRP network.
method Analyze XRP transaction history, propose Flow Index.
result Flow Index reveals bow-tie/walnut structure in XRP network.
Cryptoasset Factor Modelsq-fin.PM
We propose factor models for the cross-section of daily cryptoasset returns and provide source code for data downloads, computing risk factors and backtesting them out-of-sample. In "cryptoassets" we include all cryptocurrencies and a host of various other digital assets (coins and tokens) for which exchange market dat…
Altcoin-Bitcoin Arbitrageq-fin.PM
We give an algorithm and source code for a cryptoasset statistical arbitrage alpha based on a mean-reversion effect driven by the leading momentum factor in cryptoasset returns discussed in https://ssrn.com/abstract=3245641. Using empirical data, we identify the cross-section of cryptoassets for which this altcoin-Bitc…
Study finds cryptoasset markets inefficient due to capital reallocation frictions.
problem Inefficiency in cryptoasset markets due to capital reallocation frictions.
method Examined investments with dominant and secondary risk factors, derived equilibrium restrictions, and tested empirically.
result Empirical results strongly reject necessary equilibrium restrictions, indicating market inefficiency.
Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient?q-fin.GN
The paper assesses VASPs' solvency using multiple data sources.
problem Insolvency risk in VASPs without systematic auditing.
method Cross-referencing cryptoasset wallets, balance sheets, and supervisory data.
result Inconsistent data between DLT transactions and balance sheets for some VASPs.
Investors in Bitcoin exhibit the disposition effect, selling winners and holding losers.
problem The disposition effect in cryptoassets, specifically Bitcoin.
method Using transaction data from cryptoasset exchanges, the study investigated Bitcoin investors' behavior.
result Bitcoin investors exhibit the disposition effect, with intensity varying over time.
Novel AMM model for pegged cryptoassets using nested OU processes.
problem Liquidity and risk management in markets for pegged cryptoassets.
method Multi-level nested Ornstein-Uhlenbeck (OU) processes for exchange rate dynamics, calibrated and filtered AMM model.
result Consistent efficient quotes and improved liquidity provision for pegged cryptoassets.
Study examines cryptoasset service providers in Austria, revealing global integration and distinct responses to market shocks.
problem Understanding cryptoasset integration and stress behavior in national economies.
method Directly identified on-chain addresses of Austrian crypto-asset service providers, reconstructing transaction activity across multiple cryptocurrencies.
result Austrian crypto-asset service providers are globally integrated, with distinct responses to market shocks.
Study analyzes financial intermediation costs in decentralized lending protocols.
problem Understanding the cost of financial intermediation in decentralized lending protocols.
method Analysis of publicly available data on rates, supply, borrow activity, and accounts.
result Ex-post margins are 1% and lower for stablecoin markets.
This study examines asymmetric cross-correlations in cryptocurrency markets using fractal analysis.
problem Exploring asymmetric multifractal cross-correlations in cryptocurrency markets.
method Fractal analysis and MF-ADCCA method to investigate asymmetric volatility dynamics.
result Cross-correlations are stronger in downtrend markets than in uptrend markets for maturing BTC and ETH.
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.
Ethereum tackles bribery in blockchain transactions with new fee mechanism.
problem Bribing miners in Ethereum blockchain to manipulate transaction fees.
method Filtered transactions, constructed proxies for bribery level, analyzed effects on blockchain and financial markets.
result Bribing affects Ethereum and other blockchains, influencing cryptocurrency, transaction stats, and network adoption.
Information-theoretic measures for non-linear causality detection: application to social media sentiment and cryptocurrency pricesphysics.data-an
Information transfer between time series is calculated by using the asymmetric information-theoretic measure known as transfer entropy. Geweke's autoregressive formulation of Granger causality is used to find linear transfer entropy, and Schreiber's general, non-parametric, information-theoretic formulation is used to …
Bitcoin's Crypto Flow Networkq-fin.GN
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.
Quantifying Cryptocurrency Unpredictability: A Comprehensive Study of Complexity and Forecastingq-fin.ST
Cryptocurrency time-series predictability is low, resembling Brownian noise.
problem Low predictability of cryptocurrency exchange rates.
method Complexity and model predictions of Litecoin, Binance Coin, Bitcoin, Ethereum, and XRP exchange rates.
result Simpler models outperform complex ones in cryptocurrency forecasting.
Detecting unusual trading patterns on cryptocurrency exchanges by means of complexity measuresq-fin.TR
Study detects unusual trading patterns on crypto exchanges using complexity measures.
problem Detecting artificial trading activity on cryptocurrency exchanges.
method Complexity and statistical-structure measures derived from high-frequency trade-level data.
result Unusual trading patterns detected on Bitget for BTC and ETH after mid-May 2025.
The Limits of Lognormal: Assessing Cryptocurrency Volatility and VaR using Geometric Brownian Motionq-fin.RM
Study benchmarks cryptocurrency risk using GBM, revealing Lognormal limitations.
problem Tackles limitations of Lognormal assumption in modeling cryptocurrency volatility and VaR.
method Applies Geometric Brownian Motion (GBM) with Maximum Likelihood Estimation and correlated Monte Carlo Simulation.
result Observed limitations of Lognormal assumption in cryptocurrency volatility and VaR calculations.
Graph learning categorizes DeFi services into similar functionalities.
problem Identifying similar financial services in decentralized finance protocols.
method Graph representation learning (GRL) to categorize smart contract blocks into clusters.
result Purity of clustering reaches .888 in the best-case scenario.
Cross-correlations in fluctuations of the daily exchange rates within the basket of the 100 highest-capitalization cryptocurrencies over the period October 1, 2015, through March 31, 2019, are studied. The corresponding dynamics predominantly involve one leading eigenvalue of the correlation matrix, while the others la…
Study on TVL computation in DeFi protocols, proposing verifiable metrics.
problem Lack of standardization and verifiability in TVL computation.
method Systematic study of 939 DeFi projects, analyzing methodologies and proposing vTVL.
result 240 protocols use repeated balance queries, limiting verifiability.
Study reveals that cryptocurrency price variations follow power-law distributions, influenced by age and market capitalization.
problem Understanding the statistical properties of cryptocurrencies, especially their price variations.
method Comprehensive investigation of over 7000 digital currencies, analyzing their price returns over time.
result Cryptocurrency price returns follow power-law distributions, with age and market capitalization influencing these distributions.