Reveals linear dependence of volatility on accumulated returns in S&P500 data, suggesting new insights into market behavior.
We analyze historic S&P500 multi-day returns: from daily returns to those accumulated over up to ten days. Despite symmetry breaking between gains and losses in the distribution of returns, resulting in its positive mean and negative skew, realized variance (volatility squared) exhibits remarkably good linear dependence on the number of days of accumulation. Mean of the distribution also shows near perfect linear dependence as well. We analyze this phenomenon both analytically and numerically using a modified Jones–Faddy skew t-distribution.
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Ghasemi et al. (2026) studied this question.
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