We endorse the idea, suggested in recent literature, that BitCoin prices are influenced by sentiment and confidence about the underlying technology; as a consequence, an excitement about the BitCoin system may propagate to BitCoin prices causing a Bubble effect, the presence of which is documented in several papers abo…
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48 results for “Bitcoin derivatives”
This is the first paper that estimates the price determinants of BitCoin in a Generalised Autoregressive Conditional Heteroscedasticity framework using high frequency data. Derived from a theoretical model, we estimate BitCoin transaction demand and speculative demand equations in a GARCH framework using hourly data fo…
Paper finds funding rates on BitMEX predict Bitcoin inverse swap contracts.
problem Understanding the relationship between BitMEX funding rates and Bitcoin derivatives.
method Examined Heteroskedasticity of funding rates, established Granger causality, developed GARCH models for prediction.
result Funding rates on BitMEX predict Bitcoin inverse swap contracts.
This paper develops models for cryptocurrency trading and evaluates Bitcoin options.
problem Evaluating European options on Bitcoin with realistic models.
method Jump-diffusion models for cryptocurrency dynamics.
result Models accurately predict Bitcoin option prices.
The Bitcoin transaction graph is a public data structure organized as transactions between addresses, each associated with a logical entity. In this work, we introduce a complete probabilistic model of the Bitcoin Blockchain. We first formulate a set of conditional dependencies induced by the Bitcoin protocol at the bl…
Study uses neural networks to value Bitcoin options considering price jumps and sentiment.
problem Valuing Bitcoin options under price jumps and market sentiment.
method Bivariate jump-diffusion model, incorporating Google search sentiment, and artificial neural networks.
result Derives a closed formula for Bitcoin option pricing and validates using high-volatile stocks.
Regulated Bitcoin futures led to higher volatility and trading volume.
problem Estimating the impact of regulated Bitcoin futures on volatility and volume.
method Employed a new causal approach, C-ARIMA.
result Regulated Bitcoin futures increased Bitcoin volatility by more than double.
Proposes NDIG model to capture bitcoin volatility and option pricing.
problem Capturing the volatility and option pricing of cryptocurrency Bitcoin.
method Doubly subordinated Levy process (NDIG) to model Bitcoin time series properties.
result NDIG model perfectly captures observed in-sample volatility.
Much significant research has been done to investigate various facets of the link between Bitcoin price and its fundamental sources. This study goes beyond by looking into least to most influential factors-across the fundamental, macroeconomic, financial, speculative and technical determinants as well as the 2016 event…
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.
On Bitcoin Price Predictionq-fin.ST
This paper examines Bitcoin's price predictability, finding inefficiencies under certain conditions.
problem Predictability of Bitcoin's price movements.
method Theoretical reviews, empirical analyses, machine learning approaches, time series modeling.
result Bitcoin's market tends toward efficiency but shows exploitable inefficiencies under specific conditions.
This study compares three volatility metrics for Bitcoin, highlighting high expected volatility.
problem Understanding Bitcoin's volatility in financial markets.
method Historical volatility, forecasted volatility (GARCH models), and implied volatility (from options market).
result High expected volatility across all methodologies, especially implied volatility.
Paper finds linear laws in Bitcoin price changes, aiding anomaly detection.
problem Detecting anomalies in Bitcoin price changes.
method Time embedding of autocorrelation function, binary series generation, stepped time windows.
result Linear laws became more complex before major market events, suggesting price manipulation.
In recent literature it is claimed that BitCoin price behaves more likely to a volatile stock asset than a currency and that changes in its price are influenced by sentiment about the BitCoin system itself; in Kristoufek [10] the author analyses transaction based as well as popularity based potential drivers of the Bit…
The availability of data on digital traces is growing to unprecedented sizes, but inferring actionable knowledge from large-scale data is far from being trivial. This is especially important for computational finance, where digital traces of human behavior offer a great potential to drive trading strategies. We contrib…
Bi-LSTM with attention predicts gold and bitcoin prices accurately.
problem Predicting prices of gold and bitcoin in financial derivatives markets.
method Bidirectional LSTM neural network with attention mechanism, feature engineering, two-layer deep learning.
result Achieved 71.94% and 73.03% accuracy for bitcoin and gold respectively.
This paper analyses the relationship between BitCoin price and supply-demand fundamentals of BitCoin, global macro-financial indicators and BitCoin attractiveness for investors. Using daily data for the period 2009-2014 and applying time-series analytical mechanisms, we find that BitCoin market fundamentals and BitCoin…
PDE model predicts Bitcoin price using transaction network and sentiment data.
problem Predicting Bitcoin price with high accuracy.
method Partial differential equation model on Bitcoin transaction network, incorporating Google Trends Index.
result Average daily bitcoin price prediction accuracy of 0.82 over 362 days in 2017.
Hedging with Bitcoin Futures: The Effect of Liquidation Loss Aversion and Aggressive Tradingq-fin.RM
Study optimizes Bitcoin futures hedging to reduce liquidation risk.
problem Optimizing hedging strategies to minimize liquidation risk in Bitcoin futures.
method Derived a semi-closed form optimal hedging strategy considering spot and futures extreme returns, loss aversion, leverage, and collateral management.
result Optimal strategy reduces both hedged portfolio variance and liquidation probability.
Study shows Bitcoin security tied to mining rewards and prices.
problem Understanding Bitcoin security's dependency on market outcomes.
method Used ARDL approach with daily blockchain and Bitcoin data from 2014-2019.
result Bitcoin security outcomes linked to Bitcoin price and mining rewards.
Cohort analysis speeds up Bitcoin blockchain data queries.
problem Efficiently querying Bitcoin blockchain data for economic insights.
method Cohort analysis applied to Bitcoin transaction data.
result Creation of datasets and visualizations for key Bitcoin transaction indicators.
This paper investigates the effects of the launch of Bitcoin futures on the intraday volatility of Bitcoin. Based on one-minute price data collected from four cryptocurrency exchanges, we first examine the change in realized volatility after the introduction of Bitcoin futures to investigate their aggregate effects on …
Bitcoin Does Not Hedge Inflationq-fin.PR
Bitcoin reacts negatively to inflation surprises, contrary to belief.
problem Bitcoin's ability to hedge inflation is questioned.
method Examined cryptocurrency responses to macroeconomic news announcements.
result Bitcoin's price decreases by 24 bps in response to inflationary surprises.
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 shows Bitcoin mining with surplus electricity can boost KEPCO's financial stability.
problem Improving energy resource efficiency and reducing KEPCO's debt.
method Utilized surplus electricity for Bitcoin mining using Antminer S21 XP Hyd, analyzed with Random Forest Regressor and Long Short-Term Memory models.
result Bitcoin mining with surplus electricity generates economic revenue, minimizes energy loss, and resolves payment issues for KEPCO.
Study tests if equity factors explain Bitcoin's risk and returns.
problem Explaining Bitcoin's risk and return with equity factors.
method Applied statistical methods to test Fama-French factors on Bitcoin's excess returns.
result Fama-French factors have explanatory power on Bitcoin's risk and returns.
Bitcoin's attention is linked to Google Trends data, not general uncertainty.
problem Bitcoin's correlation with Google Trends data was previously misunderstood.
method Analyzed bidirectional relationships between Bitcoin returns and Google Trends attention over six days.
result Information flows from Bitcoin volatility to Google Trends attention, not the other way.
Attempts to accurately measure the monetary velocity or related properties of bitcoin used in transactions have often attempted to either directly apply definitions from traditional macroeconomic theory or to use specialized metrics relative to the properties of the Blockchain like bitcoin days destroyed. In this paper…
Recent research on Bitcoin Transaction Networks reveals a growing, sparse, and core-periphery structure.
problem Understanding the evolution of Bitcoin's network structure and user behavior.
method Review of recent results on Bitcoin Transaction Networks, including Address Network, User Network, and Lightning Network.
result Bitcoin Transaction Networks exhibit a core-periphery structure, indicating increasing centralization.
Bitcoin draws the highest degree of attention among cryptocurrencies, while coin mining is one of the most important fashion of profiting in the Bitcoin ecosystem. This paper constructs fresh coin circulation networks by tracking the fresh coin transfer routes with transaction referencing in Bitcoin blockchain. This pa…
Report presents analysis of empirical distribution of future returns of bitcoin (BTC) from BTUSD inverse option prices. Logistic pdf is chosen as underlying distribution to fit option prices. The result is satisfactory and suggests that these prices can be described with just three or even one parameter. Fitted Logisti…
Bitcoin reacts positively to USDT minting but not burning, showing state-dependence.
problem Understanding Bitcoin's response to Tether's supply changes.
method Analyzing Bitcoin's intraday price movements in response to USDT minting and burning events.
result Bitcoin's response to USDT minting events declines after 60 minutes and is influenced by investor sentiment and public announcements.
Paper compares ETF and futures carry rates in segmented Bitcoin markets.
problem Limitations in cross-margining between spot Bitcoin and CME futures.
method Estimates carry rates from IBIT options and CME futures, uses put-call parity and daily ETF holdings.
result Mean and median wedge in carry rates is 2.58 and 2.52 percent, respectively.
The Impact of Bitcoin ETF Approval on Bitcoin's Hedging Properties Against Traditional Assetsq-fin.GN
ETF approval boosts Bitcoin's correlation with equities, stabilizes with gold, and maintains negative correlation with fiat currencies.
problem Impact of Bitcoin ETF approval on Bitcoin's relationships with traditional assets.
method Rolling correlation analysis, Chow tests, and DCC-GARCH models.
result Bitcoin's correlation with equities increased significantly post-ETF approval, while its relationship with gold stabilized and remained negatively correlated with fiat currencies.
Study finds time-varying volatility and multifractality in Bitcoin, with asymmetry weakening as market efficiency increases.
problem Investigating time-varying properties of Bitcoin's volatility and multifractality.
method Rolling window method to examine daily Bitcoin returns and multifractal properties over time.
result Volatility asymmetry in Bitcoin changes over time, becoming less pronounced as market efficiency increases.
This research aims to identify how Bitcoin-related news publications and online discourse are expressed in Bitcoin exchange movements of price and volume. Being inherently digital, all Bitcoin-related fundamental data (from exchanges, as well as transactional data directly from the blockchain) is available online, some…
Examining the Effect of Monetary Policy and Monetary Policy Uncertainty on Cryptocurrencies Marketq-fin.ST
Study finds monetary policy uncertainty negatively impacts Bitcoin returns.
problem Impact of monetary policy and uncertainty on cryptocurrencies market.
method Markov Switching Means VAR (MSM-VAR) method.
result Monetary policy uncertainty leads to a decline in Bitcoin returns.
Study reveals centralization in Bitcoin transactions involving retail users.
problem Centralization and bias in Bitcoin transaction data.
method Heuristic classification of Bitcoin users, weekly activity pattern analysis.
result Most real transactions involve Frequent Receivers, centralizing the ecosystem.
Modeling Bitcoin prices and media attention using jump-type processes.
problem Capturing the dynamics of Bitcoin prices and media attention.
method Lévy processes and semiparametric estimation.
result Effective modeling of Bitcoin prices and media attention using Lévy processes.
Bitcoin returns exhibit a distinct inverse cubic law scaling behavior.
problem Investigating the scaling properties of Bitcoin price returns.
method Analysis of recent Bitcoin data to determine tail index and autocorrelation of absolute returns.
result The tail index of Bitcoin returns changes to approximately 3, consistent with the inverse cubic law.
In this paper, we study the possibility of inferring early warning indicators (EWIs) for periods of extreme bitcoin price volatility using features obtained from Bitcoin daily transaction graphs. We infer the low-dimensional representations of transaction graphs in the time period from 2012 to 2017 using Bitcoin blockc…
2024 saw Bitcoin ETF approval, offering regulated exposure.
problem Understanding unique liquidity risks in Bitcoin ETFs.
method Analyzed premium/discount patterns in first four months.
result Premium/discount behavior differs from traditional ETFs.
Although Bitcoin has long been dominant in the crypto scene, it is certainly not alone. Ether is another cryptocurrency related project that has attracted an intensive attention because of its additional features. This study seeks to test whether these cryptocurrencies differ in terms of their volatile and speculative …
This study uses neural networks to predict Bitcoin prices, finding GRUs outperform LSTMs.
problem Predicting Bitcoin's volatile price movements.
method Used LSTMs and GRUs for forecasting, with L2 regularization to reduce overfitting.
result GRUs models outperform LSTMs in predicting Bitcoin's price with lower MSE.
The study improves Bitcoin price prediction using hybrid machine learning and enhances interpretability.
problem Improving Bitcoin price prediction accuracy and interpretability.
method Hybrid machine learning algorithms (OLS, LASSO, LSTM, decision tree regressors) and preprocessing techniques for time-series data.
result Linear regression achieves the best performance in predicting Bitcoin prices.
Institutional Adoption and Correlation Dynamics: Bitcoin's Evolving Role in Financial Marketsq-fin.PM
Bitcoin's integration with major financial indices intensifies, suggesting a shift from alternative to integrated asset.
problem Understanding Bitcoin's evolving role in financial markets and its correlation dynamics.
method Rolling-window correlation, static correlation coefficients, and event-study framework on daily data from 2018 to 2025.
result Correlation levels between Bitcoin and major indices reached 0.87 in 2024, indicating a more integrated role.
Predicts stock market crashes using rational bubble model.
problem Financial market crashes prediction.
method White box model based on rational bubble theory.
result Successfully predicts major crashes in Dow Jones and Bitcoin markets.
Bitcoin fails to prove safe haven status during pandemic.
problem Determining if Bitcoin is a reliable safe haven asset during crises.
method Quantile correlations of Bitcoin with S&P500, VIX, and gold.
result Gold is a better safe haven during crises, not Bitcoin.