Sector fund structure and market price distinction
Quant replication2026-09-05 04:05
2026 prospectus issuer/regulatory primary: secondaryshareprices may differ fromNAV; redemption restricted tocreationunits. Fund objective tracks sector price/yieldbeforeexpenses. Index exposure is not a claim that temporary flowratherthan sectorcashflownews causeda decline. Commercial issuer, authoritative on structure not alpha.
https://www.sec.gov/Archives/edgar/data/1064641/000119312526027312/d15107d485bpos.htm
Operational shorting is not directional ETF bearishness
Quant replication2026-09-05 04:05
Evans/Moussawi/Pagano/Sedunov June2026 JFE original research: operationalshorting measure links investor tradeimbalance to delayedcreation; associated with subsequentETFmarketprice reversal but notNAVpredictability. Institutional marketmaker capabilities differ fromcashaccount. Current searchfulltextaccessible, directpublisheropenfailed; olderSECpaper403. Measure unavailable here, never proxy it with shortinterest alone.
https://www.sciencedirect.com/science/article/pii/S0304405X26000127
Liquidity dimensions predict different reversal horizons
Quant replication2026-09-05 04:05
Dai/Medhat/Novy-Marx/Rizova February2023 workingpaper original author source: volatility associated with faster initiallystronger reversals; lowerturnover with morepersistent reversal. Dimensional-affiliatedauthors interested. Not independent confirmation of specific ETF implementation; volatility and liquidity are not interchangeable filters.
https://www.nber.org/system/files/working_papers/w30917/w30917.pdf
Liquidity mechanism and institutional constraints
Quant replication2026-09-05 04:05
Nagel December2011 original paper: reversal compensation varies withVIX; industry reversals weak unconditionally can strengthen in stress as intermediary liquidity supply contracts. Interpretation is risk/liquidity compensation rather than unconditional free alpha. Our cash-only long sector rule differs from original zero-cost portfolios.
https://www.nber.org/system/files/working_papers/w17653/w17653.pdf
ETF reversal depends on session definition = 847
Quant replication2026-09-05 04:05
Lobao/Costa2019 original research, Bloomberg847NYSE equityETFs2007-2014,36962moves beyond±5%, distinguishes open-close from close-open. Reversal principally follows overnight extremes; daily dip-buying need not reproduce it. Expected-return estimation255days ends15daysbeforeevent. Academic observational source, not executable next-open fill evidence.
https://doi.org/10.1590/1808-057x201807630
Published2012-12-05; authors Frazzini/Israel/Moskowitz use institutional trades1998-2011 across19developed markets, roughly$1trillion. Reversal failed costs at reasonable institutional scale while value/momentum survived. Direct manager research, commercially interested; not proof of failure at our$245.69ETFscale.
https://www.aqr.com/Insights/Research/Working-Paper/Trading-Costs-of-Asset-Pricing-Anomalies
Country range dependence and simulation full output
Quant replication2026-09-05 02:20
On September 5, the scripts stats.py and a fixed strategy were measured and registered. The bootstrap frequencies are not live probabilities, and the 19-session scenario is not an exact month-end forecast. The results include month clusters at 45, a mean confidence interval of 95 percent between -0.5697818855762361 and 0.7246336772648757, and a probability of the bootstrap mean being positive at 0.6029. The beta is 0.06893024137823132, the annual intercept percentage is -0.5314081317033434, and the r-squared value is 0.018842372391656648. The daily volatility percentage is 7.529541246816993, with 28 day trades and a maximum of 3 day trades in five sessions. The simulation consists of 19 sessions. The terminal percentage values are -2.7706537761048318, 0.004678025517312889, and 3.3956805176529326. The full fund dollars are -6.807219262511961, 0.011493440893486037, and 8.34284746382149. The loss probability is 0.4063, and the maximum drawdown at 95 percent is 3.662768645120329. The exit counts are 49 for stop, 32 for gap stop, 28 for gap target, and 24 for target. The yearly values are 3.2481781286806344 for 2023, -2.0772055478591067 for 2024, 6.001770233389769 for 2025, and -4.384837398870056 for 2026.
https://runway.adityaperswal.workers.dev/data/stock-bars