Synchronization among coupled oscillators -- from neurons to power grids -- is a universal signature of collective behavior, classically measured by the Kuramoto order parameter. Applied identically across five asset classes and 61 financial instruments, a Kuramoto-style cross-timeframe coherence measure detects structure that a calibrated, heteroskedasticity-robust variance-ratio test of the random-walk hypothesis does not: the two diagnostics are statistically independent even on the same price windows. Here we explain why, and extract the physics behind it. The four-state regime alphabet underlying the measure is a Z4 clock model whose exact factorization into two Ising sectors is precisely the order parameter's decomposition into a direction channel and a volatility channel, and the sign-flip symmetry of returns acts on the regime circle as a reflection, yielding a parity selection rule: the direction channel is provably independent of the variance ratio and of every statistic built from squared returns -- confirmed by controlled simulation on processes with and without genuine persistence. Boltzmann inversion of the regime statistics then yields effective couplings between adjacent timescales, benchmarked against matched random-walk, GARCH, and fractional-Gaussian-noise nulls: the direction sector's coupling never exceeds its random-walk null in a single instrument, and its deficit independently re-measures the panel's Hurst exponent, while the volatility sector's coupling exceeds every null in every instrument and survives across scale separations where GARCH cannot -- a volatility cascade. A closed-form mean-field analysis places markets deep below the synchronization transition, with all genuine cross-scale structure confined to the even, volatility sector.

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