{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T04:00:19Z","timestamp":1790740819875,"version":"4.1.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":0,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>This paper examines how reducing exposure during drawdowns impacts portfolio performance. Three exposure reduction strategies based on fixed thresholds, linear scaling, and moving averages are tested on SPY from 2000 to 2025 and compared with a buy-and-hold benchmark. All three strategies reduced annualised volatility and maximum drawdown, with the moving averages strategy reducing them the most, from 19.38% to 9.35% and from-55.19% to-21.97%, respectively, and all three lost less than the benchmark during major crises. This came at the cost of lower returns, with CAGR falling from 8.03% to between 5.27% and 7.41%, and none of the strategies improved on the benchmark's Sharpe or Sortino ratio. Lower returns were driven mainly by remaining underexposed during recoveries, an effect exacerbated by fast recoveries, and whipsaws during shallow drawdowns that reversed before losses could be meaningfully limited. Despite this, all three strategies recorded a higher Calmar ratio than the benchmark, indicating that the reduction in drawdown was sufficient to offset the decline in return even where the reduction in volatility was not. This improvement was only marginal for the fixed thresholds strategy and the linear scaling strategy (0.18 and 0.16 vs. 0.15), but the moving averages strategy stood out clearly (0.24). Overall, exposure reduction can materially improve downside characteristics, but involves a persistent trade-off between reducing drawdown and sacrificing return. Among the three approaches tested, the trend-based approach of the moving averages strategy provided the strongest trade-off.<\/jats:p>","DOI":"10.2139\/ssrn.7542498","type":"posted-content","created":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T03:31:43Z","timestamp":1790739103000},"source":"Crossref","is-referenced-by-count":0,"title":["How Does Reducing Exposure During Drawdowns Impact Portfolio Performance?"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2465-5786","authenticated-orcid":true,"given":"Oscar","family":"Strahle","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T03:31:43Z","timestamp":1790739103000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7542498"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7542498","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}