Clusters cryptocurrency market states via cross correlation analysis.
problem Analyse cryptocurrency market dynamics.
method Cross correlation structure analysis over 5 years.
result Cryptocurrency market clusters into 4 states.
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
48 results for “Cryptocurrency Market”
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.
Network analysis reveals changing cryptocurrency market leaders.
problem Understanding evolving cryptocurrency market leaders and their influence.
method Hourly-resolution data and Kendall's Tau correlation for network analysis.
result Pearson's correlation underestimates market dynamics; FTT and FTX were key during the 2021 bull run.
Study examines cryptocurrency risk spillover effects before and after pandemic.
problem Analyzing risk propagation among cryptocurrencies during extreme events.
method Asymmetric breakpoint approach and network analysis.
result Cryptocurrency risk spillover effect increased during pandemic.
Cryptocurrencies show mature market characteristics but vary by size.
problem Understanding maturity in cryptocurrency markets.
method Quantitative analysis of return distributions, volatility, and correlations.
result Smaller cryptocurrencies lack mature market characteristics.
Collective dynamics, diversification and optimal portfolio construction for cryptocurrenciesq-fin.ST
Investigates cryptocurrency maturity through collective dynamics and diversification.
problem Determining if cryptocurrency market exhibits similar mathematical properties to equity market.
method Adjusts focus to retail cryptocurrency investors' behavioral patterns, contrasting with equity market.
result Identifies ideal portfolio size and spread across cryptocurrencies, revealing signatures of maturity.
Evolutionary dynamics of the cryptocurrency marketphysics.soc-ph
The cryptocurrency market surpassed the barrier of \$100 billion market capitalization in June 2017, after months of steady growth. Despite its increasing relevance in the financial world, however, a comprehensive analysis of the whole system is still lacking, as most studies have focused exclusively on the behaviour o…
Cryptocurrencies are becoming more linked in their returns and volatilities.
problem Understanding the increasing interconnectivity of cryptocurrencies.
method Examined market linkages using returns and volatilities, applied various methodologies.
result Significant increase in market linkages for both returns and volatilities.
This study attempts to analyze patterns in cryptocurrency markets using a special type of deep neural networks, namely a convolutional autoencoder. The method extracts the dominant features of market behavior and classifies the 40 studied cryptocurrencies into several classes for twelve 6-month periods starting from 15…
Deep learning predicts cryptocurrency price movements with 78% accuracy.
problem Predicting price formation in cryptocurrency markets with high volatility and illiquidity.
method Applied deep learning to predict mid-price changes on live tick-level cryptocurrency data.
result Achieved 78% accuracy in predicting mid-price movement of Bitcoin vs USD.
Study evaluates cryptocurrency markets, focusing on Bitcoin.
problem Evaluating financial markets, especially during crises.
method Multiple-bubble testing approach.
result Identifies Bitcoin's multiple bubbles during economic periods.
Trend following in cryptocurrencies yields high returns, similar to commodities.
problem Investing in cryptocurrencies using trend following strategies.
method A decade of data analysis on cryptocurrency markets and trend following strategies.
result Cryptocurrencies offer strong returns and diversification against traditional equities.
Cryptocurrency forecasting model considers macro, sentiment, and technical indicators.
problem High price volatility in cryptocurrency markets.
method Dual-prediction mechanism incorporating macroeconomic fluctuations, technical indicators, and individual cryptocurrency price changes.
result The proposed model outperforms ten comparison methods in short-term cryptocurrency forecasting.
Unified Bayesian framework predicts cryptocurrency market dynamics and volatility.
problem Predicting cryptocurrency market trends and volatility.
method Bayesian framework based on potential field theory and Gaussian Process.
result Attractors and repellers from the potential field are reliable market indicators.
A new index CRIX for cryptocurrencies is proposed to track market changes.
problem Tracking the volatile and frequently changing cryptocurrency market.
method AIC-based method to select index constituents and assign optimal weights to altcoins.
result CRIX index improves tracking performance of cryptocurrency portfolios.
This paper uses crypto derivatives data to estimate yield curves for cryptocurrencies.
problem Estimating yield curves for cryptocurrencies without bond markets.
method Using mathematical tools and data from cryptocurrency derivatives markets.
result Yield curves can be constructed for cryptocurrencies using derivative data.
Structural Change Analysis of Active Cryptocurrency Market
Study high-frequency trading patterns in cryptocurrencies.
problem Understanding automated trading algorithms in cryptocurrency markets.
method Analyzes intraday trading data of cryptocurrencies, focusing on returns, volumes, and volatility.
result Provides insights into predictability of economic value in cryptocurrency markets.
Study shows institutional investments significantly impact cryptocurrency market evolution.
problem Limited understanding of institutional investments' role in cryptocurrency market evolution.
method Quantitative analysis of 1324 cryptocurrencies' investments from 2014-2022.
result Institutional investments correlate with cryptocurrency market capitalization.
Study on cryptocurrency market dynamics and correlations over time.
problem Understanding the dynamics and correlations of cryptocurrency market over time.
method Evolutionary correlation analysis, turning point algorithm, inverse relationship between market size and collective dynamics, time-varying consistency of relationships, examination of volatility structure.
result Increased uniformity in volatility during market crashes, termed 'volatility dispersion'.
Cryptocurrency market becomes more cross-correlated over time.
problem Understanding the inter-market dependencies of cryptocurrencies.
method Time series analysis, spectral analysis, topological analysis of minimal spanning trees.
result Cryptocurrency market becomes more cross-correlated with other markets over time.
The return of (I)DeFiXq-fin.CP
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.
Study finds TVL doesn't predict cryptocurrency returns.
problem Assumption of TVL predicting returns in crypto markets.
method Examined TVL-sorted portfolios against crypto market returns, using various TVL measures.
result TVL-sorted portfolios' returns are linear functions of crypto market returns, replicable with standard tools.
Study finds cryptocurrency market diversity patterns inconsistent with neutral models.
problem Cryptocurrency market diversity patterns not consistent with neutral models.
method Analysis borrowing methods from ecology, focusing on diversity patterns and community structure.
result Cryptocurrency market diversity patterns not consistent with neutral models, suggesting strong interactions between species.
This research predicts cryptocurrency price volatility using deep learning models.
problem Predicting the volatility of cryptocurrency prices to mitigate investment risk.
method Used CNN, LSTM, BiLSTM, and GRU models to predict the risk factor of 20 cryptocurrency parameters.
result Developed a new model with RMSE of 0.0089, significantly outperforming existing models.
Study compares cryptocurrency and stock markets using statistical equilibrium models.
problem Comparing the stochastic structure of cryptocurrency and stock markets.
method Applied QRSE model to analyze daily returns of cryptocurrencies and S&P 500 companies.
result Revealed differences in informational efficiency between cryptocurrency and stock markets.
The efficient market hypothesis has far-reaching implications for financial trading and market stability. Whether or not cryptocurrencies are informationally efficient has therefore been the subject of intense recent investigation. Here, we use permutation entropy and statistical complexity over sliding time-windows of…
Paper uses SAC and DDPG to optimize cryptocurrency portfolios.
problem Adapting to volatile and nonlinear cryptocurrency markets.
method Reinforcement learning with SAC and DDPG algorithms.
result SAC and DDPG outperform traditional strategies in cryptocurrency markets.
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.
Paper constructs a CRRIX index to assess cryptocurrency market risks from regulatory changes.
problem Lack of indices quantifying regulatory risks in cryptocurrencies.
method CRRIX index based on news coverage frequency, using Latent Dirichlet Allocation and Hellinger distance.
result CRRIX successfully captures major policy-changing moments and synchronizes with market volatility.
FinBERT-BiLSTM predicts cryptocurrency prices using sentiment analysis.
problem Predicting volatile cryptocurrency market prices.
method Hybrid model combining Bi-LSTM and FinBERT for sentiment analysis.
result Enhanced forecasting accuracy for volatile financial markets.
Study cryptocurrency market complexity using multifractal and cross-correlation analyses.
problem Understanding the complexity and dynamics of cryptocurrency markets, especially during the COVID-19 pandemic.
method Multifractal formalism, cross-correlation analyses, network representation.
result Cryptocurrency market dynamics exhibit multifractal and intermittent bifractality, with topology changes during significant events.
Thousands of cryptocurrencies have been issued and publicly exchanged since Bitcoin was invented in 2008. The total cryptocurrency market value exceeds 300 billion US dollars as of 2019. This paper analyzes the prices, volumes, blockchain transactions, coin difficulties and public opinion popularities of 3607 actively …
The paper tackles backtest overfitting in cryptocurrency trading using deep reinforcement learning.
problem Backtest overfitting in deep reinforcement learning for cryptocurrency trading.
method Formulated hypothesis test for overfitting detection, trained agents, estimated overfitting probability, and rejected overfitted agents.
result Less overfitted deep reinforcement learning agents outperformed more overfitted agents and market benchmarks.
Modeling financial crises and cryptocurrency shocks using copulae clustering.
problem Detecting financial crises and shock events in stock and cryptocurrency markets.
method Copulae clustering based on probability distribution distances.
result Successfully detected all past crises and shock events in stock and cryptocurrency markets.
This study analyzes how cryptocurrency networks adapt to financial disruptions.
problem Understanding how cryptocurrency networks respond to financial crises.
method Vertex centrality measures to assess network stability and resilience.
result Different cryptocurrencies experienced shifts in their network roles during the FTX crisis.
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.
Study shows how cryptocurrency market skewness and kurtosis interact during pandemic.
problem Understanding the dynamics of cryptocurrency markets during the pandemic.
method Examined skewness and kurtosis interactions in cryptocurrency market data.
result More observations cluster around extremes during pandemic, indicating volatile behavior.
Network-based strategy for optimal cryptocurrency portfolios identified.
problem Challenges in predicting cryptocurrency prices in a volatile market.
method Network methods to identify decorrelated cryptocurrencies, Markowitz Portfolio Theory.
result Network-based portfolios outperform benchmarks with high expected returns.
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 examines dynamic relationship between BRICS stocks and cryptocurrencies.
problem Understanding the impact of BRICS stock markets on cryptocurrency markets.
method Time-varying parameter vector autoregression model (TVP-VAR).
result Three out of five BRICS stock markets are primary sources of shocks affecting the financial network.
Study shows diverse data sources improve cryptocurrency forecasting models.
problem Improving cryptocurrency market forecasting accuracy.
method Integrating various data types, including on-chain metrics, traditional indices, and macroeconomic indicators.
result Data source diversity significantly enhances forecasting model performance.
Cryptocurrencies are increasingly correlated with traditional financial markets.
problem Determining the independence of cryptocurrencies from traditional financial markets.
method High-frequency detrended cross-correlation analysis over various time scales and market periods.
result Cryptocurrencies have become more aligned with traditional financial markets, especially during bear phases.
This study examines whether the efficiency of cryptocurrency markets (Bitcoin and Ethereum) evolve over time based on Lo's (2004) adaptive market hypothesis (AMH). In particular, we measure the degree of market efficiency using a generalized least squares-based time-varying model that does not depend on sample size, un…
Paper detects pump and dump schemes in cryptocurrencies.
problem Cryptocurrency market manipulation by communities.
method Analyzed communities, reported case studies, introduced real-time detection approach.
result Real-time detection approach outperforms current methods.
This paper examines autocorrelation in major crypto markets, finding persistent correlations on short time frames.
problem Assessing the efficiency of major cryptocurrency markets through autocorrelation analysis.
method Pearson's autocorrelation coefficient, Ljung-Box test, rolling window analysis.
result Persistent autocorrelation on 5m and 1H time frames, disagreement on 1D and 1W time frames.
Time-dependent weighted directed networks of cryptocurrency interaction from high-frequency returnsq-fin.TR
Investigate the evolving structure of cryptocurrency interactions using high-frequency returns.
problem Evolution of cryptocurrency interactions
method Construct directed and weighted networks from Granger causal relationships between cryptocurrency log-returns.
result Normalized returns exhibit heavy-tailed distributions.
Dynamics, behaviours, and anomaly persistence in cryptocurrencies and equities surrounding COVID-19q-fin.ST
Study shows similarities and differences in crypto and equity dynamics during pandemic.
problem Comparing cryptocurrency and equity market dynamics during the pandemic.
method New methodologies applied to study cryptocurrency and equity market dynamics, including recently introduced methods for trajectory and anomaly analysis.
result Cryptocurrencies exhibit stronger collective dynamics and correlation, while equities show greater persistence in anomalies over time.