# Rebalancing Frequency Dominates Risk-Proxy Choice: A Comparison of Mean–Variance, MAD, and Quantile-Constrained Portfolios of U.S. Sector ETFs

> A comparison of variance, MAD, IQR and a wider central-quantile risk proxy in constrained portfolio construction across nine U.S. sector ETFs and 27 years, finding that rebalancing cadence matters more than the risk measure.

- Author: Siddhant Shah, Aishwarya Malhotra, Gourav Salotra, Eugene Pinsky
- Published: 2026-10-02
- Canonical URL: https://siddhants.com/research/rebalancing-frequency-risk-proxy/
- Published in: Risks 14(10): 229
- DOI: https://doi.org/10.3390/risks14100229
- PDF: https://doi.org/10.3390/risks14100229

## Thesis

Practitioners argue about which risk measure to optimise against. The comparison
suggests they are arguing about the wrong decision: once realistic constraints are
imposed, how often you rebalance moves outcomes more than whether you constrain
variance, mean absolute deviation, interquartile range or a wider central quantile.

Portfolio construction offers a choice of risk proxy — variance, mean
absolute deviation (MAD), interquartile range (IQR), or a wider central-quantile
measure (P95). The practical question is whether that choice actually changes
outcomes, or whether it gets swamped by the other decisions involved in running a
portfolio.

## The setup

Nine U.S. sector ETFs over **27 years**. Every strategy shares the same constraints —
long-only, fully invested, a maximum allocation cap and an explicit cash sleeve — and
each is evaluated across a range of annualised risk budgets and rebalancing schedules
under a **strict no-look-ahead timeline**.

Holding the constraints fixed is what makes the comparison mean anything. Risk proxies
are usually compared in isolation, where implementation differences are free to
masquerade as differences between the measures themselves.

## The finding

**Rebalancing frequency dominates the choice of risk proxy.** Once the constraints are
imposed, performance differences across rebalancing schedules are typically larger than
differences across variance, MAD, IQR or P95.

The robust proxies are feasible to implement, and they are not a free lunch: at longer
rebalance intervals in particular, they converge toward similar allocations and similar
realised outcomes as variance-based optimisation.

## Why it matters

The implication is a reordering of priorities. Operational decisions — how often the
portfolio is actually traded — may deserve more attention than the selection of the
risk metric, which is where much of the methodological argument has gone.

## Disclosure

The views expressed here are my own personal opinions. This is **not investment advice** and should not be relied upon as such. Nothing here is connected to, endorsed by, or written on behalf of Rosenblatt Securities.

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