Trend patterns statistics for assessing irreversibility in cryptocurrencies: time-asymmetry versus inefficiency
In this paper, we present a measure of time irreversibility using trend pattern statistics. We define the irreversibility index as the Kullback-Leibler divergence between the distribution of uptrends subsequences (increasing trends) and the corresponding downtrends subsequences distribution (decreasing trends) in a time series. We use this index to analyze the degree of irreversibility in log return series over time, specifically focusing on five cryptocurrencies: Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash. Our analysis reveals a strong indication of irreversibility in all these cryptocurrencies and the characteristic evolves over time. We additionally evaluate the market efficiency for these cryptocurrencies based on a recently proposed information-theoretic measure. By comparing inefficiency and irreversibility, we explore the relationship between these statistical features. This comparison provides insight into the non-trivial relationship between inefficiency and irreversibility.
Code (0)
등록된 구현이 없습니다.
Tasks
Time SeriesSimilar Papers 제목 키워드 기반
Clustering Digital Assets Using Path Signatures: Application to Portfolio Construction
We propose a new way of building portfolios of cryptocurrencies that provide good diversification properties to investors. First, we seek to filter these digital assets by creating some clusters based on their path signa…
ClusteringA Decade of Evidence of Trend Following Investing in Cryptocurrencies
Cryptocurrency markets have many of the characteristics of 20th century commodities markets, making them an attractive candidate for trend following strategies. We present a decade of evidence from the infancy of bitcoin…
Rise of the Machines? Intraday High-Frequency Trading Patterns of Cryptocurrencies
This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns related to algorithmic trading and its impact on the European cryptocurrency market. We study trading quanti…
Algorithmic TradingVocal Bursts Intensity PredictionForecasting Cryptocurrencies Log-Returns: a LASSO-VAR and Sentiment Approach
Cryptocurrencies have become a trendy topic recently, primarily due to their disruptive potential and reports of unprecedented returns. In addition, academics increasingly acknowledge the predictive power of Social Media…
Practical Forecasting of Cryptocoins Timeseries using Correlation Patterns
Cryptocoins (i.e., Bitcoin, Ether, Litecoin) are tradable digital assets. Ownerships of cryptocoins are registered on distributed ledgers (i.e., blockchains). Secure encryption techniques guarantee the security of the tr…
Time SeriesTime Series Forecasting