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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

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6131925 · Oct 201919922001200920172026
48 results for decentralized cryptocurrency

Study shows multifractality emerging in decentralized cryptocurrency trading.

problem Understanding financial dynamics in decentralized cryptocurrency markets.
method Multifractal Detrended Fluctuation Analysis (MFDFA) on tick-by-tick transaction data.
result Multifractality is emerging in decentralized cryptocurrency trading, with larger fluctuations dominating.

Study shows cryptocurrency market impact on DeFi returns stronger than other drivers.

problem Understanding drivers of DeFi returns and their relative importance.
method Investigated four drivers: cryptocurrency market exposure, network effect, investor attention, and valuation ratio. Designed a new market index, DeFiX.
result Cryptocurrency market impact on DeFi returns is stronger than other drivers and provides superior explanatory power.

Regulating crypto and DeFi for inclusive economic advancement.

problem Innovative financial systems pose challenges to traditional regulatory frameworks.
method Formulating regulatory structures that balance innovation and consumer protection.
result Regulatory frameworks are essential for leveraging crypto and DeFi for inclusive economic growth.

DAM improves cryptocurrency trend forecasting using multimodal data.

problem Simplistic merging of sentiment data in cryptocurrency trend forecasting.
method Dual Attention Mechanism (DAM) integrating financial metrics and sentiment analysis.
result DAM outperforms conventional models by up to 20% in prediction accuracy.

HyFi cryptocurrencies backed by institutions show lower price risk than fully decentralized ones.

problem High volatility in decentralized finance (DeFi) cryptocurrencies.
method Panel EGLS models with fixed, random, and dynamic specifications using daily data for 18 major cryptocurrencies.
result HyFi-like assets exhibit lower price risk, especially during market stress.

Study finds significant price declines and capital reallocation from centralized to decentralized exchanges after FTX collapse.

problem Quantifying trust dynamics and redistribution between centralized and decentralized exchanges.
method Interdisciplinary approach combining causal inference and computational text analysis.
result Significant price declines and capital reallocation from centralized to decentralized exchanges following the FTX collapse.

This study analyzes cryptocurrency market dynamics using a novel qq-dependent detrended cross-correlation method.

problem Capturing correlations at varying fluctuation amplitudes and time scales in complex systems.
method Extends traditional metrics with qq-dependent detrended cross-correlation coefficient ρ(q,s) and qqMSTs.
result Significant shifts in network structures during major disruptions, leading to decentralized correlations.

This study compares price discovery in ETH and BTC markets between centralized and decentralized exchanges.

problem Understanding price discovery dynamics in cryptocurrency markets.
method Comparative analysis of centralized and decentralized exchanges, using econometric tools.
result Centralized exchanges lead in ETH price discovery, while futures markets lead in BTC.

We discuss Russia's underlying motives for issuing its government-backed cryptocurrency, CryptoRuble, and the implications thereof and of other likely-soon-forthcoming government-issued cryptocurrencies to some stakeholders (populace, governments, economy, finance, etc.), existing decentralized cryptocurrencies (such a…

2018-01-17abs ↗pdf ↗

Study compares costs and arbitrage in CEXs vs DEXs, finding DEXs better for large trades.

problem Comparing transaction costs and arbitrage in crypto exchanges.
method Comprehensive dataset analysis of transaction costs and no-arbitrage deviations.
result Fixed gas fees in DEXs impose a significant burden on small trades, while CEXs offer more competitive costs for larger trades.

Optimizes cryptocurrency trading pairs for efficiency and decentralization.

problem Finding optimal trading pairs among many cryptocurrencies without direct volume data.
method Two-stage process: 1) Fill missing values using eigenvalue decomposition with regularization, 2) Optimize pairs using branch and bound with pruning.
result Optimal trading pairs lead to more decentralized markets and better liquidity.

Study compares Web3 tokens to traditional assets, finding similar statistical properties.

problem Understanding statistical properties of Web3 tokens compared to traditional financial assets.
method Statistical analysis of various Web3 tokens across multiple time scales, comparing with traditional financial assets.
result Most Web3 tokens exhibit similar stylized facts to traditional financial assets, including heavy tails and volatility clustering.

The paper investigates cyclic arbitrage opportunities in decentralized exchanges.

problem Price discrepancies in decentralized exchanges lead to arbitrage opportunities.
method Theoretical framework and analysis of transaction-level data.
result Traders have executed over 292,606 cyclic arbitrages over eleven months, exploiting more than 138 million USD in revenue.

This work analyzes impermanent loss in decentralized markets and provides a hedging strategy.

problem Impermanent loss in automated market makers (AMMs).
method Analytical derivation of a static replication formula using European options, and numerical example with real data.
result Guaranteed hedging coverage for all final prices within a predefined interval.

The paper examines Bitcoin's nature using fractal geometry and finds it highly persistent, affecting predictability and decentralization.

problem Understanding the nature and predictability of Bitcoin prices.
method Statistical analysis of Bitcoin returns using fractal geometry.
result Bitcoin exhibits high persistence in prices, reducing efficiency but increasing predictability.

Study uses sentiment analysis to predict cryptocurrency token returns in virtual reality.

problem Predicting cryptocurrency token returns in virtual reality economies.
method Used BERT for sentiment analysis and developed LSTM models integrating multi-modal features.
result Multi-modal model significantly outperforms price-only baseline in prediction accuracy.

Study compares quantum and classical ML in crypto trading, finding hybrid models outperform.

problem Comparing quantum and classical machine learning in crypto trading strategies.
method Backtesting 10 models across multiple crypto assets using classical ML, quantum ML, hybrid models, and transformer models.
result Hybrid quantum models achieve superior performance with 13.99% return and 1.76 Sharpe ratio.

Study finds on-chain data can proxy off-chain cryptocurrency pricing.

problem Develop methods to proxy off-chain cryptocurrency pricing using on-chain data.
method Graphical models, mutual information, and ensemble machine learning.
result A significant amount of pricing information is contained in on-chain data, but precise prices are hard to recover except on short time scales.

A new AMM design reduces impermanent loss and retains more liquidity.

problem Inefficiencies in conventional AMM designs lead to liquidity loss and user engagement issues in DEXs.
method Proposes a dual-mechanism framework: a power-law invariant BMM and dynamic rebate system.
result Reduces impermanent loss by 36% and retains 3.98x more liquidity during price volatility.

This study examines yield aggregators in DeFi, summarizing strategies and analyzing performance.

problem Understanding and optimizing yield farming strategies in DeFi.
method Summarizes yield farming protocols and tokens, analyzes performance through simulations and empirical data.
result Plausible connection between data anomalies and historical events in yield aggregators.

FinSurvival provides a large-scale financial survival modeling benchmark.

problem Lack of large-scale, realistic, and freely available datasets for benchmarking AI survival models.
method Derived 16 survival modeling tasks from cryptocurrency lending data using an automated pipeline.
result Demonstrated that existing AI survival models are not well-suited for these challenging tasks.

Modeling DEX liquidity with heterogeneous LPs and MEV bots.

problem Understanding and predicting the dynamics of decentralized cryptocurrency exchanges.
method Mean-field game approach to model liquidity providers' optimal strategies and interactions.
result Calibrated model produces consistent pool exchange rate dynamics and liquidity evolution.

Study compares altcoins to Bitcoin, analyzing their features and market performance.

problem Comparing altcoins to Bitcoin to understand market performance and features.
method Used Google Trend data, price, volume, and market capitalization data from coinmarketcap.com.
result Features of Litecoin, Zcash, Bitcoin Cash, Ethereum, and Bitcoin Gold affect market performance and user preferences.

Study analyzes gambling behavior and risk attitudes using blockchain data.

problem Lack of real-life gambling data for validating predictions and experimental findings.
method Collects and analyzes betting data from a decentralized application on the Ethereum Blockchain.
result Empirical examples of gambling systems and insights into risk preferences.

Study analyzes global public sentiment on DeFi from 2012-2022.

problem Global public sentiment on DeFi is understudied.
method Sentiment analysis, spatial econometrics, clustering, topic modeling.
result Economic development significantly influences DeFi engagement, especially after 2015.

Enhances crypto-asset AMM with deep learning for better liquidity and efficiency.

problem Reduced slippage and improved liquidity in decentralized finance.
method Deep reinforcement learning for predicting market equilibrium and optimizing liquidity.
result Improved capital efficiency and reduced slippage for crypto-asset traders.

The paper uses AI to analyze on-chain parameters and identify risky cryptocurrencies.

problem Identifying risky cryptocurrencies and understanding their price factors.
method Historical data analysis, AI algorithms, clustering, classification.
result A significant negative correlation between cryptocurrency price and maximum and total supply, and a weak positive correlation with 24-hour trading volume.

Cryptocurrencies show similarities to traditional markets but also have unique characteristics.

problem Understanding the investment potential and characteristics of cryptocurrencies.
method Organized stylized facts and analyzed through empirical asset pricing.
result Cryptocurrencies exhibit similarities to traditional markets but also have distinct characteristics.

Study analyzes cryptocurrency market complexity, comparing it to traditional markets.

problem Understanding the dynamics and characteristics of cryptocurrency markets.
method Statistical physics methods and analysis of price fluctuations.
result Cryptocurrency market exhibits complexity similar to traditional markets but with slower information flow.