Continuous-Time Regime Propagation (CTRP)

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Authors: Renaud Axel Eba
Cited by: 0

Abstract

The Regime Switching Probabilistic Vector (RSPV), which provides a probabilistic representation of regime dynamics. The RSPV integrates (i) volatility estimation via HMMs, (ii) adaptive regime discretization, (iii) transition probability computation using a CTMC generator derived from Fermi’s Golden Rule (FGR), and (iv) the proximity probability to the mean-reversion value (MRV). RSPV is not a predictive model or a forecasting algorithm. Rather, it represents a probability geometry uncovered from market regime dynamics through physics-inspired transition mechanics. The RSPV encodes time-varying probability distributions across regimes, which downstream forecasting models can exploit as informative features.

Publication details

Journal / source
Mendeley Data
Publication date
19 August 2026
Document type
Dataset