{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T22:39:56Z","timestamp":1792276796964,"version":"4.4.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":33,"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\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Infrastructure exchange-traded funds share a label but not a common economic exposure. Using a survivorship-adjusted universe of U.S.-listed infrastructure and infrastructure-adjacent ETFs, monthly CRSP returns through April 2026, and seven replicable archetypes, this study tests whether differences visible in mandates survive formal empirical scrutiny. Raw returns, Sharpe ratios, and factor-adjusted alphas do not differ reliably across archetypes, but volatility, market beta, income characteristics, within-group similarity, and several systematic factor loadings do. Owner\/operator funds are the lowest-beta and lowest-volatility group; development, renewable\/power, digital, energy-network, water, and hybrid funds perform different portfolio jobs. Downside and rate-regime results reinforce the distinction. Starting from a 60\/40 equity bond benchmark, a 60\/30\/10 infrastructure reallocation case and a constrained infrastructure sleeve optimization show that the preferred archetype changes with defensive, growth, income, and diversification objectives. Infrastructure selection should begin with portfolio function, not fund label or recent return.<\/jats:p>","DOI":"10.2139\/ssrn.7590179","type":"posted-content","created":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T02:17:11Z","timestamp":1791771431000},"source":"Crossref","is-referenced-by-count":0,"title":["Infrastructure ETFs: Factor Exposures, Regime Risk, and Portfolio Roles"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1426-6593","authenticated-orcid":true,"given":"Xuan","family":"Feng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0709-3599","authenticated-orcid":true,"given":"Ziming","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"2","key":"ref1","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.finmar.2010.10.005","article-title":"Conventional Mutual Index Funds versus Exchange-Traded Funds","volume":"14","author":"Anna Agapova","year":"2011","journal-title":"Journal of Financial Markets"},{"issue":"4","key":"ref2","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1093\/rfs\/hhj035","article-title":"Downside Risk","volume":"19","author":"Andrew Ang","year":"2006","journal-title":"Review of Financial Studies"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1146\/annurev-financial-110716-032538","article-title":"Exchange-Traded Funds","volume":"9","author":"Ben-David","year":"2017","journal-title":"Annual Review of Financial Economics"},{"issue":"6","key":"ref4","doi-asserted-by":"crossref","first-page":"2471","DOI":"10.1111\/jofi.12727","article-title":"Do ETFs Increase Volatility?","volume":"73","author":"Ben-David","year":"2018","journal-title":"Journal of Finance"},{"issue":"2","key":"ref5","doi-asserted-by":"crossref","first-page":"162","DOI":"10.3905\/jai.2020.1.105","article-title":"Cryptocurrencies as an Asset Class? 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