An Innovative Approach for Risk Measurement in Digital Currency Market Using Interval-valued Data
In the digital economy,the emergence of digital currencies has attracted considerable attention from both investors and researchers.However,their high volatility characteristics present new challenges in investment decision-making and risk assessment.To capture the characteristics comprehensively,this paper proposes a novel approach for constructing confidence regions for interval-valued variables based on the exponentially decay weighted bootstrap.The coverage area of the confidence regions and tail quantiles provide new indicators for assessing the volatility and tail risks in the market.Empirical results using Bitcoin as a case study demonstrate the proposed approach outperforms other traditional point-based methods such as ex-ponential weighted moving average in measuring the uncertainty and intraday price volatility.Furthermore,the derived tail quantiles exhibit superior predictive perfor-mance for tail risk compared to Value-at-risk methods and the exponential weighted moving average,as evidenced by various tests.The proposed methodology not only contributes a new statistical tool for analyzing digital currency volatility but also provides novel perspectives for extreme risk management in financial markets.
万方数据
维普
