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Factor models · Product inferenceEmpirical finding

ETF factor exposures, alpha, and multiple-testing control

Advertised exposures appeared; no tested alpha survived multiple-testing correction.

Factor regressions tested six style ETFs for their advertised exposures. A second stage asked what unexplained return survived multiple-testing correction.

Research by Quantitative Markets & Institutions LabRevised 3 sources4 figuresLedger entry

Commit 4806df9Evidence ad24c49Data · 2,892 rowsUniverse 15 instrumentsTests 239 / 239 passed

  • 0.34MTUM momentum β
  • 49MTUM momentum t-statistic (OLS)
  • 0.31VLUE value (HML) β
  • 29VLUE value t-statistic (OLS)
  • +3.29%QQQ annualised alpha
  • 0.024QQQ raw HAC p-value

The advertised exposures were recovered; no alpha survived multiple-testing correction.

MTUM loaded on momentum at β = 0.34 (t = 49). VLUE loaded on value at β = 0.31 (t = 29). QQQ's estimated +3.29% annualized alpha carried a raw HAC p-value of 0.024. Its Benjamini–Hochberg q-value was 0.147. Across the six ETFs, no alpha survived the 5% false-discovery threshold.

Factor loadings with 95% HAC intervals · six style ETFs

β · daily excess returns on FF5 + momentum · Newey–West HAC(5) · notebook 05

Dots with interval bands showing each ETF's loading on the market, size, value, profitability, investment and momentum factors.
factorQQQQQQ · lowQQQ · highUSMVUSMV · lowUSMV · highMTUMMTUM · lowMTUM · highVLUEVLUE · lowVLUE · highQUALQUAL · lowQUAL · highIWMIWM · lowIWM · high
Mkt-RF1.105611.076251.134970.7429380.6986190.7872581.040621.014641.066590.9842510.9641791.004320.9762770.957610.9949441.003520.9889211.01812
SMB-0.121876-0.14973-0.0940219-0.124721-0.168068-0.0813742-0.096254-0.136873-0.05563540.1079310.06423190.151629-0.0837018-0.10613-0.06127360.8482440.8102750.886213
HML-0.306236-0.342893-0.2695790.0101894-0.03482430.0552031-0.0202303-0.05850540.01804490.3109550.2712370.350673-0.0435282-0.0631468-0.02390960.1004390.0781640.122714
RMW0.05050080.01678160.084220.1632880.1223470.204229-0.156801-0.200634-0.1129670.00422313-0.04462020.05306640.1484680.1291380.167798-0.110021-0.131989-0.0880523
CMA-0.185612-0.237528-0.1336950.1777520.09817710.257328-0.0148822-0.07876260.04899830.1188330.06345860.1742070.0250655-0.007476780.0576078-0.0176326-0.04784610.012581
Mom0.04146210.02519930.0577248-0.0189788-0.04312550.005167930.3396230.3085750.370672-0.056308-0.0812792-0.0313368-0.0412127-0.0575118-0.02491370.02468660.00597250.0434007

Annualised alpha with HAC intervals · six style ETFs

% per year · 95% HAC(5) interval · notebook 05

Dots with interval bands of annualised alpha for the six ETFs against a zero line; QQQ carries the largest estimate, and no alpha survives Benjamini–Hochberg correction at 5%.
ETFAlpha (% p.a.)Raw pHolm pBH qSurvives 5% FDR
QQQ3.294980.02445440.1467260.146726no
USMV-1.231030.5189510.778425no
MTUM0.0206190.99015810.990158no
VLUE0.4875650.77377110.928525no
QUAL-0.7391990.41767710.778425no
IWM-1.139750.1100030.5500150.330009no

Rolling 252-day QQQ betas with HAC bands

β · trailing 252 observations, month-end · 95% HAC(5) band · notebook 05

Lines with bands of QQQ's rolling one-year market, value and momentum loadings; the momentum loading changes sign across the sample.
window endMkt-RFMkt-RF · lowMkt-RF · highHMLHML · lowHML · highMomMom · lowMom · high
2016-01-291.04311.009061.07714-0.114465-0.210026-0.01890290.00933983-0.03626260.0549422
2016-02-291.046711.01191.08151-0.124627-0.232131-0.01712350.0139579-0.03952340.0674392
2016-03-311.050861.015541.08618-0.110771-0.21281-0.008731360.0212103-0.02749610.0699166
2016-04-291.041461.00441.07851-0.129357-0.224805-0.03390930.0143462-0.03736250.0660549
2016-05-311.04341.007051.07975-0.119298-0.21069-0.02790590.0177421-0.0332320.0687163
2016-06-301.045971.008361.08358-0.115914-0.205009-0.02681880.022749-0.02771950.0732176
2016-07-291.063461.026061.10085-0.139649-0.231184-0.04811360.0275621-0.02045320.0755775
2016-08-311.066771.020931.11262-0.149418-0.24083-0.0580060.0339202-0.01684050.0846809
2016-09-301.088661.04341.13392-0.190756-0.283014-0.09849690.0444552-0.008569150.0974796
2016-10-311.08581.049241.12235-0.170453-0.265651-0.07525360.07323240.02596940.120495
2016-11-301.100881.061061.14071-0.230305-0.360251-0.1003590.08204270.0353180.128767
2016-12-301.117481.075821.15914-0.235719-0.360282-0.1111570.08838890.04061670.136161
2017-01-311.115321.065391.16525-0.279068-0.382223-0.1759130.07460150.0248890.124314
2017-02-281.135261.086211.18431-0.265473-0.360864-0.1700810.08103920.02723570.134843
2017-03-311.120991.069051.17293-0.274333-0.367281-0.1813860.07130020.002928660.139672
2017-04-281.117361.061981.17273-0.292987-0.396814-0.1891610.0577965-0.01732930.132922
2017-05-311.126781.067241.18631-0.296072-0.404742-0.1874010.08550980.0006794070.17034
2017-06-301.11691.046281.18751-0.375655-0.481708-0.2696020.1425960.0376490.247544
2017-07-311.099411.038361.16047-0.386373-0.482092-0.2906530.2149920.1311190.298866
2017-08-311.101931.046311.15755-0.420923-0.500236-0.3416110.2605170.1962040.324829
2017-09-291.148951.088841.20906-0.415359-0.494027-0.3366910.2330340.1602530.305816
2017-10-311.157591.093181.22201-0.423138-0.495429-0.3508470.2355720.1637830.30736
2017-11-301.159121.076361.24189-0.431684-0.500004-0.3633640.1749090.08837920.261439
2017-12-291.162511.077111.24791-0.428492-0.497951-0.3590330.1647480.0854490.244047
2018-01-311.160221.076571.24386-0.434808-0.507361-0.3622550.1131740.02375570.202592
2018-02-281.107451.051971.16294-0.447878-0.523495-0.372260.1139920.02826910.199714
2018-03-291.118291.067251.16933-0.453792-0.528911-0.3786720.1045980.01171920.197476
2018-04-301.128391.080231.17655-0.462323-0.535047-0.38960.0875431-0.00794990.183036
2018-05-311.124171.077921.17042-0.485631-0.562555-0.4087070.0368532-0.0528230.126529
2018-06-291.118171.074941.1614-0.496972-0.576751-0.4171940.0129372-0.06662410.0924984
2018-07-311.121071.073161.16898-0.447737-0.532289-0.3631850.0030704-0.079320.0854608
2018-08-311.112041.065311.15877-0.439393-0.526378-0.3524080.0102088-0.07126190.0916796
2018-09-281.106371.060491.15226-0.452825-0.544201-0.3614490.00731301-0.07044950.0850755
2018-10-311.103821.056541.1511-0.43474-0.519507-0.3499740.0307729-0.04705270.108599
2018-11-301.101831.060331.14334-0.368013-0.444587-0.2914390.0638304-0.01193360.139594
2018-12-311.086641.052121.12117-0.34481-0.431694-0.2579250.0556197-0.02549990.136739
2019-01-311.077361.045261.10946-0.309277-0.392767-0.2257860.0586241-0.01295080.130199
2019-02-281.08211.041471.12273-0.300722-0.385408-0.2160370.0655325-0.006106740.137172
2019-03-291.072241.028011.11647-0.292343-0.372653-0.2120330.0535051-0.01432620.121336
2019-04-301.044981.001121.08884-0.246064-0.329761-0.1623660.0346771-0.03481120.104165
2019-05-311.045181.00121.08916-0.234637-0.31826-0.1510140.0274846-0.04236410.0973333
2019-06-281.025830.9835521.0681-0.219332-0.300154-0.138509-0.0236288-0.09269430.0454367
2019-07-311.035990.9925541.07943-0.225637-0.316259-0.135014-0.028592-0.09813360.0409497
2019-08-301.045851.001431.09027-0.252291-0.347878-0.156704-0.0629285-0.1314180.00556116
2019-09-301.058181.014421.10195-0.249795-0.348687-0.150902-0.0864441-0.15247-0.0204179
2019-10-311.043641.000611.08667-0.27134-0.366945-0.175735-0.113345-0.174555-0.0521339
2019-11-291.033530.9918951.07517-0.306962-0.403429-0.210496-0.128146-0.190546-0.0657456
2019-12-311.060751.009031.11247-0.28401-0.378862-0.189157-0.114432-0.180049-0.0488155
2020-01-311.092841.041561.14412-0.248375-0.343634-0.153117-0.0796321-0.144532-0.014732
2020-02-281.090931.047451.1344-0.301161-0.404396-0.197926-0.0987412-0.168026-0.0294567
2020-03-311.046311.012531.08008-0.458587-0.598099-0.319075-0.141841-0.186724-0.0969583
2020-04-301.039671.00561.07375-0.456399-0.58055-0.332249-0.107165-0.171907-0.0424221
2020-05-291.033390.999351.06742-0.418577-0.535958-0.301197-0.0936012-0.151274-0.0359282
2020-06-301.031610.9989641.06425-0.407798-0.537439-0.278156-0.0589709-0.115394-0.00254791
2020-07-311.031630.9987741.06449-0.392481-0.518375-0.266587-0.0456965-0.09874750.0073544
2020-08-311.031240.997511.06497-0.385616-0.512907-0.258326-0.0321885-0.08570790.021331
2020-09-301.041251.006241.07626-0.391554-0.522931-0.260177-0.019145-0.07769470.0394048
2020-10-301.047321.011581.08307-0.402577-0.536502-0.268653-0.0164551-0.07655560.0436454
2020-11-301.047651.01211.08321-0.391716-0.527639-0.255793-0.00633038-0.06248740.0498267
2020-12-311.049481.01381.08516-0.400935-0.535025-0.266844-0.0128069-0.06969120.0440773
2021-01-291.051541.015431.08765-0.424611-0.560897-0.288324-0.00865566-0.06769420.0503829
2021-02-261.050661.013031.08829-0.413148-0.548497-0.2777990.0029656-0.05788250.0638137
2021-03-311.136751.078521.19498-0.307101-0.386926-0.2272770.0585280.01589350.101162
2021-04-301.18951.146891.2321-0.278328-0.346564-0.2100920.07138190.03959910.103165
2021-05-281.185641.140531.23076-0.314764-0.393537-0.235990.05310570.02327910.0829323
2021-06-301.196241.141211.25128-0.328669-0.411191-0.2461480.04050390.01551220.0654957
2021-07-301.176271.121051.2315-0.358211-0.432713-0.283710.03374580.008416780.0590748
2021-08-311.167931.112451.22342-0.364214-0.437008-0.291420.03273690.007742320.0577315
2021-09-301.137341.084841.18984-0.371664-0.44137-0.3019590.03392020.007407710.0604327
2021-10-291.115821.059051.17259-0.372437-0.442786-0.3020880.03468170.00705750.0623058
2021-11-301.069811.015511.12411-0.399565-0.460004-0.3391270.09642110.05478740.138055
2021-12-311.051431.004041.09882-0.392238-0.450548-0.3339280.1254030.08746710.163338
2022-01-311.075771.02741.12414-0.331362-0.378219-0.2845060.1201520.07959490.160709
2022-02-281.086611.041061.13216-0.342628-0.397405-0.2878510.09486750.05194210.137793
2022-03-311.096341.057041.13564-0.323833-0.37756-0.2701060.06362170.02081690.106426
2022-04-291.110141.070691.14959-0.318951-0.377916-0.2599860.0409495-0.006077340.0879763
2022-05-311.113571.08041.14674-0.306421-0.367035-0.2458080.0259529-0.02339410.0753
2022-06-301.120911.091711.1501-0.289441-0.350766-0.2281160.0248096-0.02071440.0703336
2022-07-291.118471.087261.14967-0.283235-0.342597-0.2238730.0130849-0.03172740.0578971
2022-08-311.117891.087581.14819-0.282147-0.344012-0.2202830.0107129-0.03329490.0547206
2022-09-301.121511.092421.15061-0.301661-0.364773-0.2385480.0181648-0.02819910.0645288
2022-10-311.119021.090061.14799-0.311994-0.376876-0.2471110.0179194-0.02919630.065035
2022-11-301.121261.089931.1526-0.302127-0.366966-0.237288-0.0118193-0.05946650.0358278
2022-12-301.110511.079131.14189-0.290284-0.358038-0.22253-0.0508557-0.1018110.00010016
2023-01-311.104331.073461.1352-0.310163-0.390169-0.230157-0.0645213-0.12232-0.00672235
2023-02-281.10251.070231.13477-0.289609-0.380968-0.19825-0.0928476-0.164553-0.021142
2023-03-311.097771.066151.12939-0.3121-0.400274-0.223925-0.0911897-0.159487-0.0228928
2023-04-281.09691.063521.13027-0.300046-0.388721-0.211371-0.0935594-0.160766-0.0263531
2023-05-311.075821.027931.12371-0.266587-0.353489-0.179686-0.0899443-0.159315-0.0205736
2023-06-301.023790.9904131.05717-0.321598-0.383917-0.259279-0.0988675-0.148735-0.0489998
2023-07-311.039981.002031.07794-0.295769-0.364916-0.226622-0.0582612-0.11551-0.00101245
2023-08-311.061061.017071.10505-0.27949-0.346482-0.212498-0.0329903-0.09124350.025263
2023-09-291.064811.016981.11264-0.274877-0.345471-0.204283-0.0341547-0.09126860.0229593
2023-10-311.084511.038361.13066-0.271964-0.337385-0.206543-0.00633444-0.06024730.0475784
2023-11-301.101091.059441.14274-0.262229-0.330513-0.193945-0.014508-0.06956780.0405517
2023-12-291.122391.079191.1656-0.259675-0.332387-0.186963-0.0128974-0.06875840.0429635
2024-01-311.130071.084441.1757-0.263979-0.343498-0.184461-0.0039334-0.06309270.0552259
2024-02-291.113361.063441.16327-0.241794-0.329251-0.1543360.0126195-0.0438940.069133
2024-03-281.136631.088271.18499-0.160566-0.236994-0.08413760.0428995-0.006662690.0924616
2024-04-301.134611.085571.18365-0.158209-0.233101-0.08331740.042219-0.009234520.0936725
2024-05-311.124931.075171.1747-0.1463-0.219255-0.07334430.0291949-0.03137440.0897642
2024-06-281.141891.085241.19854-0.141285-0.215073-0.06749740.0329004-0.02949170.0952925
2024-07-311.227171.165211.28914-0.23774-0.316866-0.1586140.08101470.01482390.147205
2024-08-301.219411.16361.27521-0.255099-0.327729-0.1824690.08777790.02308420.152472
2024-09-301.229591.173821.28536-0.260679-0.330455-0.1909020.09058710.02782120.153353
2024-10-311.24921.193051.30535-0.273564-0.346689-0.2004380.06133230.0005068380.122158
2024-11-291.247591.188981.3062-0.261909-0.327908-0.195910.06543290.00691050.123955
2024-12-311.234481.176881.29208-0.291381-0.36217-0.2205920.0569003-0.001599570.1154
2025-01-311.231591.174781.28841-0.288139-0.35951-0.2167690.05501240.001914510.10811
2025-02-281.241871.187221.29651-0.301315-0.372266-0.2303650.0438658-0.006920540.0946522
2025-03-311.197111.135161.25906-0.322592-0.401056-0.2441290.05916120.006221990.1121
2025-04-301.148491.106361.19062-0.331322-0.410875-0.2517680.08526880.04140310.129134
2025-05-301.144911.103261.18657-0.330715-0.411542-0.2498890.08451860.0414910.127546
2025-06-301.142191.099411.18497-0.314242-0.397619-0.2308660.06628610.02279360.109779
2025-07-311.134711.094081.17535-0.300634-0.378363-0.2229050.0449450.0009034110.0889867
2025-08-291.136591.097131.17605-0.296329-0.373822-0.2188350.04578830.004436790.0871398
2025-09-301.127731.089941.16552-0.279356-0.357166-0.2015460.04309770.0007045280.0854908
2025-10-311.133831.096071.17158-0.266025-0.33718-0.1948710.04802510.009432070.0866181
2025-11-281.124651.088721.16058-0.286419-0.356989-0.2158490.04758050.009139880.0860211
2025-12-311.126641.087141.16614-0.265717-0.340534-0.19090.04930580.010610.0880017
2026-01-301.123861.085131.16258-0.253772-0.337594-0.1699510.04073150.00212440.0793385
2026-02-271.132541.092011.17307-0.236664-0.326443-0.1468840.03994990.001564020.0783357
2026-03-311.135711.09181.17962-0.172204-0.25802-0.08638740.0189084-0.009558430.0473752
2026-04-301.162551.115411.20969-0.0935731-0.164716-0.02243030.0194545-0.0108960.0498051
2026-05-291.158581.108041.20912-0.046941-0.1216590.02777650.0323238-0.002738040.0673857

In-sample versus holdout R² · chronological 50/50 split

R² (%) · coefficients frozen on the first half · notebook 05

Grouped columns comparing training R-squared with holdout R-squared for each ETF; USMV decays most.
ETFtraining R²holdout R²
QQQ95.054292.933
USMV89.585459.9519
MTUM95.199986.3837
VLUE94.540582.4719
QUAL97.50595.3112
IWM98.45398.0048

Factor exposures · OLS coefficients with HAC(5) intervals and plain-OLS t

ETFFactorβCI lowCI highHAC tOLS t
QQQMkt-RF1.105611.076251.1349773.8038205.689
QQQSMB-0.121876-0.14973-0.0940219-8.5759-12.2298
QQQHML-0.306236-0.342893-0.269579-16.3735-33.7056
QQQRMW0.05050080.01678160.084222.93544.07505
QQQCMA-0.185612-0.237528-0.133695-7.0073-12.2598
QQQMom0.04146210.02519930.05772484.9977.18718
USMVMkt-RF0.7429380.6986190.78725832.8556109.461
USMVSMB-0.124721-0.168068-0.0813742-5.6394-9.9114
USMVHML0.0101894-0.03482430.05520310.44370.888155
USMVRMW0.1632880.1223470.2042297.817110.4348
USMVCMA0.1777520.09817710.2573284.37819.29796
USMVMom-0.0189788-0.04312550.00516793-1.5405-2.60537
MTUMMkt-RF1.040621.014641.0665978.5147161.416
MTUMSMB-0.096254-0.136873-0.0556354-4.6445-8.05315
MTUMHML-0.0202303-0.05850540.0180449-1.0359-1.85649
MTUMRMW-0.156801-0.200634-0.112967-7.0111-10.5494
MTUMCMA-0.0148822-0.07876260.0489983-0.4566-0.819576
MTUMMom0.3396230.3085750.37067221.438849.0852
VLUEMkt-RF0.9842510.9641791.0043296.1098153.021
VLUESMB0.1079310.06423190.1516294.84099.05063
VLUEHML0.3109550.2712370.35067315.344728.6007
VLUERMW0.00422313-0.04462020.05306640.16950.284774
VLUECMA0.1188330.06345860.1742074.20616.55914
VLUEMom-0.056308-0.0812792-0.0313368-4.4196-8.15663
QUALMkt-RF0.9762770.957610.994944102.503274.9
QUALSMB-0.0837018-0.10613-0.0612736-7.3146-12.7124
QUALHML-0.0435282-0.0631468-0.0239096-4.3486-7.25115
QUALRMW0.1484680.1291380.16779815.054118.1325
QUALCMA0.0250655-0.007476780.05760781.50972.50579
QUALMom-0.0412127-0.0575118-0.0249137-4.9558-10.8126
IWMMkt-RF1.003520.9889211.01812134.728318.814
IWMSMB0.8482440.8102750.88621343.7865145.352
IWMHML0.1004390.0781640.1227148.837518.8777
IWMRMW-0.110021-0.131989-0.0880523-9.8157-15.1604
IWMCMA-0.0176326-0.04784610.012581-1.1438-1.98882
IWMMom0.02468660.00597250.04340072.58557.30751

ETF alpha tests with family-wise and false-discovery corrections

ETFAlpha (annualised)Alpha HAC SE (annualised)Raw pHolm adjusted pBH qSurvives BH 5%n
QQQ0.03294980.01464490.02445440.1467260.146726no0.9498312,867
USMV-0.01231030.01908680.5189510.778425no0.8132792,867
MTUM0.000206190.0167150.99015810.990158no0.9177332,867
VLUE0.004875650.0169620.77377110.928525no0.9090992,867
QUAL-0.007391990.009120760.41767710.778425no0.9669772,867
IWM-0.01139750.007131550.1100030.5500150.330009no0.9837042,867

Chronological holdout results; coefficients fitted only on the first half

ETFTraining R²Holdout R²ChangeTraining windowHoldout windowHoldout RMSE (daily)
QQQ0.9505420.92933-0.02121282015-01-05 – 2020-09-112020-09-14 – 2026-05-290.00374699
USMV0.8958540.599519-0.2963352015-01-05 – 2020-09-112020-09-14 – 2026-05-290.00492912
MTUM0.9519990.863837-0.08816142015-01-05 – 2020-09-112020-09-14 – 2026-05-290.0048687
VLUE0.9454050.824719-0.1206862015-01-05 – 2020-09-112020-09-14 – 2026-05-290.00470729
QUAL0.975050.953112-0.02193792015-01-05 – 2020-09-112020-09-14 – 2026-05-290.00233515
IWM0.984530.980048-0.004482342015-01-05 – 2020-09-112020-09-14 – 2026-05-290.00202335

Daily factor correlations, 2015–2026

FactorMkt-RFSMBHMLRMWCMAMom
Mkt-RF10.192215-0.0922692-0.223637-0.262154-0.110321
SMB0.19221510.273967-0.2703960.0440945-0.30201
HML-0.09226920.27396710.3213090.559635-0.312252
RMW-0.223637-0.2703960.32130910.27769-0.0589468
CMA-0.2621540.04409450.5596350.277691-0.014175
Mom-0.110321-0.30201-0.312252-0.0589468-0.0141751

Rolling QQQ beta ranges across windows

FactorMinMax
Mkt-RF1.023791.2492
HML-0.496972-0.046941
Mom-0.1418410.260517

Audience and decision

Research significance

ETF allocators, product researchers, and exposure owners

The result matters when a branded strategy is selected for a specific systematic exposure, or when a portfolio report attributes historical return to manager skill rather than priced factors.

Decision context

Evidentiary threshold for attributing alpha

First verify the intended exposure, then test residual return with robust uncertainty, multiplicity correction, and a chronological holdout. A raw p-value from one of several regressions is not the conclusion.

The regression found product identity more clearly than unexplained return

The study aligned 2,867 daily observations from 5 January 2015 through 29 May 2026. It ran six-factor time-series regressions for MTUM, VLUE, QUAL, IWM, USMV, and QQQ. The factors were the Fama–French five plus momentum, estimated with Newey–West HAC(5) intervals.

The named style loadings came out economically meaningful and precisely estimated. The alpha tests went the other way. Holm and Benjamini–Hochberg corrections ran across six simultaneous hypotheses, and none met a 5% false-discovery threshold. That does not mean the funds delivered nothing. It means the measured return read mainly as exposure under this factor model.

A chronological 50/50 holdout froze the first-half coefficients and applied them to the second half. Holdout R² fell by 0.4 to 29.6 percentage points across the ETFs. USMV decayed most. Exposure estimates can stay useful and still depend on the state.

Separate exposure, inference, and temporal stability

  • Check the intended sign and an economically meaningful loading on a branded ETF's named factor.
  • Correct alpha inference for the number of products or strategies searched.
  • Use heteroskedasticity- and autocorrelation-consistent intervals for daily return regressions.
  • Freeze coefficients into a chronological holdout instead of reporting full-sample fit alone.
  • Monitor rolling betas. A full-sample coefficient is a time average, not a permanent product identity.

Inspect every loading, interval, holdout result, and adjusted test

Numbers

StatementValueAs statedNote
MTUM momentum β0.340.34
MTUM momentum t-statistic (OLS)4949Plain-OLS t as printed in notebook 05; HAC(5) t = 21.4.
VLUE value (HML) β0.310.31
VLUE value t-statistic (OLS)2929Plain-OLS t as printed in notebook 05; HAC(5) t = 15.3.
QQQ annualised alpha+3.29%+3.29%
QQQ raw HAC p-value0.0240.024
QQQ Benjamini–Hochberg q-value0.1470.147
alphas surviving the 5% false-discovery threshold00
aligned daily observations2,8672,867
First aligned observation2015-01-055 January 2015
Last aligned observation2026-05-2929 May 2026
Smallest holdout R² decay (percentage points)0.40.4
Largest holdout R² decay (percentage points)29.629.6
ETF with the largest holdout decayUSMVUSMV
IWM size (SMB) β0.850.85
IWM R²0.980.98
USMV market β0.740.74
QQQ market β1.111.11
QQQ value (HML) β−0.31-0.31
QUAL profitability (RMW) β0.150.15

Limitations

  • The chosen factor menu defines the leftover alpha. Omitted technology, industry, or intangible-capital effects can matter.
  • Fama–French factor portfolios are paper long–short portfolios, not costless tradable products.
  • Eleven years remains one historical sample, including an unusual growth-over-value period.
  • The chronological 50/50 split is one holdout path rather than repeated rolling-origin evaluation.
  • HAC lag choice and vendor adjustments to ETF prices can move inference.

Sources

  1. 1Fama, E. F., and K. R. French (2015), “A Five-Factor Asset Pricing Model,” Journal of Financial Economics 116(1), 1–22. doi:10.1016/j.jfineco.2014.10.010
  2. 2Benjamini, Y., and Y. Hochberg (1995), “Controlling the False Discovery Rate,” Journal of the Royal Statistical Society: Series B 57(1), 289–300. doi:10.1111/j.2517-6161.1995.tb02031.x
  3. 3Harvey, C. R., Y. Liu, and H. Zhu (2016), “...and the Cross-Section of Expected Returns,” Review of Financial Studies 29(1), 5–68. doi:10.1093/rfs/hhv059

Cite this

Wisniewski, K. (2026, August 8). ETF factor exposures, alpha, and multiple-testing control. Quantitative Markets & Institutions Lab. https://www.kylewisniewski.com/lab/factor-etfs

@misc{wisniewski2026factor,
  author = {Wisniewski, Kyle},
  title = {ETF factor exposures, alpha, and multiple-testing control},
  year = {2026},
  month = {aug},
  howpublished = {\url{https://www.kylewisniewski.com/lab/factor-etfs}},
  note = {Empirical finding · Quantitative Markets & Institutions Lab · commit 4806df9}
}