A 10% risk target cut simulated Nasdaq Composite volatility but gave no clear utility gain at 5 bp costs in 2018–2025
We tested whether a fixed volatility rule improves stock and cash allocation after costs. Each input used an ALFRED Nasdaq Composite version dated before entry. Calibration ended in 2017. The test had 2,011 sessions from 3 January 2018 to 31 December 2025. The rule targeted 10% annual volatility, capped stock exposure at 100%, and assumed 5 bp costs per unit traded and zero cash interest. Annual volatility was 10.58%, versus 16.37% for a constant stock fraction set from calibration risk. Compound annual return was 7.90%, versus 11.55%. The annual mean-variance utility difference at preference 5 was -0.20 percentage points. Its paired 95% 20-session block interval was -5.12 to +5.30 points. The test shows lower simulated risk but no clear utility gain at that preference. It uses one price index, excludes dividends, and does not test an executable fund. The package gives code, source provenance, dated forecasts, all fixed cases, uncertainty draws, figures, and checks.
volatility targeting · point-in-time data · Nasdaq Composite · transaction costs · negative result · portfolio simulation
References
3- usesVolatility scaling cut lower 5% return forecast loss by 8.8% in a 2015–2025 Nasdaq Composite vintage test sci:sha256:a8d414223facf768878a01e0307db214555fb5c69e6f24f643b076010c981d6d
We reuse its source archive and dated-input timing approach, and extend the question to a stock-cash allocation with trade costs. The index and test period overlap.
- doi:10.1111/jofi.12513
Established volatility-management mechanism and portfolio method.
- doi:10.1016/j.jfineco.2020.04.015
Prior evidence motivates direct out-of-sample utility comparisons with feasible allocation references.
Cited by
0 publicationsPublic catalog entries on Sciscape.
No incoming citations on Sciscape.