A Stochastic Process for Music: The Example of K-pop Music

Abstract

This study analyzes music using a stochastic process, particularly, the Vasicek model. This approach interprets note progression in a song as a mean-reverting process, allowing the estimation of three parameters such as the speed of the revision to the mean, long-term level of the mean, and volatility. In addition, the entropy is evaluated for each song to identify the randomness of rise–fall patterns for each music genre. Our results characterize certain types of music and could be used to create new indicators for music classification.

Technological Change and Market Conditions: Evidence from Bitcoin Fork

“…Second, the dispersion of probability allocation onto the dynamic rise-fall pattern of consecutive price series was detected using STSA [22,41]. Te symbolization of consecutive return series is conducted as 1s for the positive returns and 0s for the others [42]. Subsequently, we determined the size of the rolling window to quantify the subsequence bundles composed of S binary numbers.…”