2022/04/06 by James B. Glattfelder, Glattfelder, James B., Anton Golub +1
Computer Science · Decision Sciences · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Economics and business #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods #Time Series Analysis and Forecasting #Trading and Market Microstructure (q-fin.TR)
paper · pdf · doi:10.48550/arxiv.2204.02682
openalex publication_date 2022/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Intrinsic time is an example of an event-based conception of time, used to analyze financial time series. Here, for the first time, we reveal the connection between intrinsic time and physical time. In detail, we present an analytic relationship which links the two different time paradigms. Central to this discovery are the emergence of scaling laws. Indeed, a novel empirical scaling law is presented, relating to the variability of what is know as overshoots in the intrinsic time framework. To evaluate the validity of the theoretically derived expressions, three time series are analyzed; in detail, Brownian motion and two tick-by-tick empirical currency market data sets (one crypto and one fiat). Finally, the time series analyzed in physical time can be decomposed into their liquidity and volatility components, both only visible in intrinsic time, further highlighting the utility of this temporal kinship.