2021/05/17 by Tim Leung, Leung, Tim, Theodore Zhao +1 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · Mathematics · #62M15 #91B84 #94A12 #Applications (stat.AP) #Complex Systems and Time Series Analysis #Computational Finance (q-fin.CP) #FOS: Computer and information sciences #FOS: Economics and business #Market Dynamics and Volatility #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods #msc:62M15 #msc:91B84 #msc:94A12 #q-fin.CP #q-fin.ST #stat.AP
paper · pdf · doi:10.48550/arxiv.2105.08133
20 pages, 8 figures
arxiv created 2021/05/17 · openalex publication_date 2021/05/17 · arxiv updated 2021/05/19 · openalex created_date 2021/06/22 · openalex updated_date 2026/07/28
We study the price dynamics of cryptocurrencies using adaptive complementary ensemble empirical mode decomposition (ACE-EMD) and Hilbert spectral analysis. This is a multiscale noise-assisted approach that decomposes any time series into a number of intrinsic mode functions, along with the corresponding instantaneous amplitudes and instantaneous frequencies. The decomposition is adaptive to the time-varying volatility of each cryptocurrency price evolution. Different combinations of modes allow us to reconstruct the time series using components of different timescales. We then apply Hilbert spectral analysis to define and compute the instantaneous energy-frequency spectrum of each cryptocurrency to illustrate the properties of various timescales embedded in the original time series.