Hourly Market Invariants for Price Simulations in Digital-Asset Markets
Generating reliable daily risk scenarios for digital assets is complicated by the fact that there is no market close. Talos presents an empirically validated approach to building daily-horizon price scenarios from 24/7 hourly data.
Hourly Market Invariants for Price Simulations in Digital-Asset Markets
Introduction
Generating reliable daily risk scenarios for digital assets is complicated by the fact that there is no market close. Talos presents an empirically validated approach to building daily-horizon price scenarios from 24/7 hourly data.
Abstract:
We test whether 1-hour log-returns of major digital assets can serve as market invariants in the sense of Meucci (2005) for 24/7 markets. Using 18 months of hourly prices for six liquid tokens, we find broadly stable marginal distributions across three 6-month windows, weak linear serial dependence in returns (in contrast to prices), and approximate horizon consistency after square-root-of-time rescaling from 1 hour to 1 day. These diagnostics support a practical scenario engine: map hourly innovations to a daily-equivalent return and exponentiate to generate 1-day token price scenarios for portfolio repricing and daily-horizon risk measurement, without relying on an end-of-day close.
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