An independent review of public financial disclosures. Not affiliated with or endorsed by the U.S. House, the U.S. Senate, or any government agency.
U.S. Senate

Sen. Dan Sullivan

Republican · Senator from AK

Armed ServicesCommerce, Science, and TransportationEnvironment and Public WorksVeterans' Affairs
Results across 16 tests
Fits patternOpen questionDoes not fitNot assessedScreening signal

No test fits; open questions on breadth and concentration, event timing (abnormal returns), direction before market-wide shocks and more.

Trades disclosed
119
Jan 28, 2015 to Jan 24, 2024
Companies traded
60
Disclosed value
$942.1K–$3.4M
Sum of reported ranges
Filed after 45 days
4
Median filing lag 27 days

Scorecard

Select a test to see the estimate, interval, adjusted p-values and robustness checks.

T2Breadth and concentration59 different companies; the effective number of equally sized positions is 6 and trading spans 63% of maximum sector diversity.Open question

Question
Is trading concentrated in a few companies rather than spread across a diversified portfolio?

Insider signature
Informed trading concentrates in the few issuers tied to the information.

Analyst note
Dollar HHI 0.174 (identified set [0.042, 0.486]); trade-count HHI 0.033 vs. 95th percentile 0.013 of 118 random draws from all congressional trades (p = 0.002). Normalized sector entropy 0.63 [0.36, 0.76]. Top three issuers (RPM, MSFT, SPY) carry at least 21% of dollar volume.

Evidence
Statistical
Effective number of issuers
6 [2, 24] 90%
0Estimate
This member6
All computed statistics (13)
n118
issuers59
hhi_mid0.1742
hhi_bounds[0.0419, 0.4865]
n_eff5.7391
hhi_count0.0333
peer_benchmark_p950.0129
peer_benchmark_p0.0020
sector_entropy0.6279
sector_entropy_ci[0.3556, 0.7600]
top3_share_lower0.2107
top3[RPM, MSFT, SPY]
top3_tied_to_eventsfalse
T4Event timing (abnormal returns)Across 93 priced trades, purchases and sales moved 1.41% in the trade's direction relative to the market over the next month on average.Open question

Question
Do purchases rise and sales fall more than the market in the weeks after the trade?

Insider signature
Purchases before price rises and sales before price falls.

Analyst note
Mean signed CAR(1,21) = 0.0141; 90% KP interval [-0.0116, 0.0399]; t_BMP = 1.25, r-bar = 0.024, t_KP = 0.69, Patell Z = 1.16, Corrado Z = 0.66. Dollar-weighted identified set [-0.0347, 0.0612]. Calendar-time alpha -17.61%/yr (NW t = -1.30, 281 days).

Evidence
Statistical
Mean signed 21-day CAR
+1.41% [−1.16%, +3.99%] 90%
p-value
0.903
Holm-adjusted p
1.000
BH q-value
0.983
Margin δ
0.5% per trade over 21 days
Robust to variants
No, reading changes under some variants
0δEstimate
This member+1.41%
All computed statistics (16)
n93
theta0.0141
ci[-0.0116, 0.0399]
p0.2465
t_kp0.6882
rbar0.0241
se_cs0.0085
se_kp0.0155
t_cs1.6596
t_bmp1.2496
patell_z1.1637
corrado_z0.6591
dollar_weighted_bounds[-0.0347, 0.0612]
calendar_time[object Object]
calendar_alpha_ci[-0.0016, 1.96e-4]
by_horizon[object Object]
Robustness variantReadingEstimate
Horizon 5 daysOpen question+0.57%
Horizon 63 daysFits pattern+7.12%
Excluding largest batch dateOpen question+1.77%
Self-owned accounts onlyNot assessed+0.29%
Dollar-weighted (bounds)Open question+6.12%
Calendar-time alpha (annualized)−17.61%
T5Direction before market-wide shocksBefore 5 large market moves, the member's net trading pointed the right way 4 times.Open question

Question
Before the market's biggest moves, did the member's trades point the right way?

Insider signature
An informed trader's trades just before a market-moving event point in the direction of the coming move.

Analyst note
Hit rate 0.80, Clopper-Pearson 90% [0.34, 0.99]; exact one-sided p = 0.188; magnitude-weighted sign-flip p = 0.062. Episodes: benchmark days beyond three rolling standard deviations with trades in the prior five trading days, plus documented episodes when supplied.

Evidence
Statistical
Hit rate
80.0% [34.3%, 99.0%] 90%
p-value
0.188
Holm-adjusted p
1.000
BH q-value
1.000
Margin δ
10 points above a coin flip
0δEstimate
This member80.0%
All computed statistics (7)
n_episodes5
hits4
hit_rate0.8000
ci[0.3426, 0.9898]
p_exact0.1875
p_magnitude0.0619
episodes[[object Object], [object Object], [object Object], [object Object], [object Object]]
T7Disclosure timeliness11 of 119 trades (9.2%) were disclosed late; median lag 27 days.Open question

Question
Were trades disclosed within the STOCK Act's 45-day limit?

Insider signature
Delayed disclosure can conceal well-timed trades.

Analyst note
Late share 0.092, Wilson [0.057, 0.146]; 90th percentile lag 44 days; longest 553 days.

Evidence
Descriptive
Late share
9.2% [5.7%, 14.6%] 90%
0Estimate
This member9.2%
All computed statistics (15)
n119
amendment_rows_excluded0
late11
late_from_trade11
excused_by_notification0
late_share0.0924
late_ci[0.0574, 0.1456]
median_lag27
p90_lag44
max_lag553
filings22
late_filings4
late_priced6
timely_priced87
late_priced_dates5
T12Anticipation of large stock moves3 trades were followed within two weeks by a large company-specific move; 2 were on the profitable side.Open question

Question
When a traded stock made a large unexpected move soon after the trade, was the trade on the right side?

Insider signature
Buying shortly before a large jump or selling shortly before a large drop.

Analyst note
Hit rate 0.67, Clopper-Pearson [0.14, 0.98], exact one-sided p = 0.500; threshold |AR| > 3 sigma.

Evidence
Statistical
Hit rate
66.7% [13.5%, 98.3%] 90%
p-value
0.500
Holm-adjusted p
1.000
BH q-value
1.000
Margin δ
10 points above a coin flip
0δEstimate
This member66.7%
All computed statistics (6)
n3
hits2
hit_rate0.6667
ci[0.1353, 0.9830]
priced93
share_followed0.0323
T15Short-swing round trips4 buy-and-sell round trips within six months; in the month after opening, those positions moved +7.06% in the trade's favour relative to the market.Open question

Question
Does the member buy and sell the same stock within six months, and do those round trips beat the market?

Insider signature
Short-horizon round trips capture a temporary informational edge.

Analyst note
Opening-trade signed CAR(1,21) 0.0706 [-0.0461, 0.1874], t_KP = 1.20, over 4 priced openings. Realized market-adjusted return to the closing trade averaged +2.36% (win rate 100%); it is shown for context only because exit timing is chosen after the fact.

Evidence
Statistical
Opening-trade signed 21-day CAR
+7.06% [−4.61%, +18.74%] 90%
p-value
0.158
Holm-adjusted p
1.000
BH q-value
0.999
Margin δ
0.5% per trade over 21 days
0δEstimate
This member+7.06%
All computed statistics (9)
round_trips4
share_in_round_trips0.0678
priced4
realized_mean0.0236
realized_win_rate1
opening_car0.0706
ci[-0.0461, 0.1874]
p0.1576
openings_priced4
T1Trade size82% of 118 trades were in the lowest disclosure band ($1,001-$15,000); trades just before large company-specific moves were not larger than usual.Does not fit

Question
Are the member's trades unusually large, especially just before news?

Insider signature
Informed trades are large relative to the trader's normal activity, because the profit from an informational edge scales with position size.

Analyst note
Lowest-band share 0.822, 90% Wilson [0.757, 0.873]. Event-linked size gap Delta_z = 0.00 (within-issuer permutation p = 1.000); 0 event-linked trades with z > 3 in bands of $50,001 or more.

Evidence
Statistical
Lowest-band share
82.2% [75.7%, 87.3%] 90%
p-value
1.000
Holm-adjusted p
1.000
BH q-value
1.000
0Estimate
This member82.2%
All computed statistics (9)
n118
lowest_band_share0.8220
lowest_band_ci[0.7571, 0.8725]
share_over_50k0.0678
max_z0
size_gap0
size_gap_p1
event_linked2
event_linked_outliers0
T3Cadence and event proximity23% of trading days were batches of three or more companies; 0% of trades look routine; 1.7% of trades came within five trading days before a large company-specific move (chance alone: 4.6%).Does not fit

Question
Do trades arrive in routine rebalancing batches, or sporadically just before company news?

Insider signature
Opportunistic trades carry information and routine trades do not.

Analyst note
Batch-day share 7/31, Wilson [0.13, 0.37]; index of dispersion 17.72 (chi-square p = 0); routine share 0.00 (portfolio-routine or Cohen-Malloy-Pomorski two-year rule). Proximity share 0.017 vs. circular-shift null mean 0.046, p = 0.862.

Evidence
Statistical
Batch-day share
22.6% [12.7%, 36.8%] 90%
p-value
0.862
Holm-adjusted p
1.000
BH q-value
1.000
0Estimate
This member22.6%
All computed statistics (14)
n118
trade_days31
batch_share_trades0.7881
batch_day_share0.2258
batch_day_ci[0.1273, 0.3683]
dispersion_index17.7200
dispersion_p0
routine_share0
proximity_share0.0169
proximity_null_mean0.0463
proximity_null_p950.1102
proximity_p0.8620
proximity_nonroutine0.0169
proximity_routine0
T8Committee overlap11% of the member's mapped trading by dollar value was in industries their committees oversee, against 22% for a comparable benchmark.Does not fit

Question
Does the member trade industries their committees oversee, and do those trades do better?

Insider signature
Members may trade on information about industries their committees oversee.

Analyst note
Committees SSAS, SSCM, SSEV, SSVA; jurisdiction sectors Aerospace & Defense, Air Freight & Logistics, Automobile Manufacturers, Cargo Ground Transportation, Commodity Chemicals, Communication Services, Construction & Engineering, Construction Materials, Electric Utilities, Environmental & Facilities Services, Health Care Facilities, Health Care Services, Interactive Media & Services, Passenger Airlines, Rail Transportation, Semiconductors, Water Utilities. Dollar share 0.106 (identified set [0.018, 0.423], bootstrap 0.035-0.200); benchmarks S&P 500 0.200, congressional peers 0.223.

Evidence
Descriptive
Jurisdiction excess share
-11.7% [-18.9%, -2.3%] 90%
Margin δ
0.5% per trade over 21 days
0δEstimate
This member-11.7%
All computed statistics (15)
n100
in_jurisdiction_trades22
share0.1062
share_bounds[0.0177, 0.4229]
share_ci[0.0347, 0.2004]
benchmark_sp5000.2000
benchmark_peers0.2233
excess-0.1170
excess_ci[-0.1886, -0.0229]
committees[SSAS, SSCM, SSEV, SSVA]
jurisdiction_sectors[Aerospace & Defense, Air Freight & Logistics, Automobile Manufacturers, Cargo Ground Transportation, Commodity Chemicals, Communication Services, Construction & Engineering, Construction Materials, Electric Utilities, Environmental & Facilities Services, Health Care Facilities, Health Care Services, Interactive Media & Services, Passenger Airlines, Rail Transportation, Semiconductors, Water Utilities]
regression_errorError evaluating factor: TypeError: 'module' object is not callable y ~ J + C(sector) + C(month) ^^^^^^^^^
gamma1–
gamma1_ci[–, –]
gamma1_p–
T11Performance relative to CongressAfter adjusting for noise, the member's trades rank at the 86% percentile of 134 members (shrunk estimate -0.28% per trade over a month).Does not fit

Question
After accounting for noise, does the member's trading beat that of other members?

Insider signature
A member with an information edge stands out from the cross-section of congressional traders.

Analyst note
Empirical Bayes: raw 0.0141, posterior -0.0028 (sd 0.0015); Congress mean -0.0028, between-member variance 0.000000.

Evidence
Statistical
Shrunk signed 21-day CAR
−0.28% [−0.53%, −0.03%] 90%
Margin δ
0.5% per trade over 21 days
0δEstimate
This member−0.28%
All computed statistics (8)
raw0.0141
posterior_mean-0.0028
posterior_sd0.0015
congress_mean-0.0028
tau20
percentile0.8582
members_compared134
lower95-0.0058
T13Co-trading with other members21% of trades had another member trading the same stock the same way within a week (chance alone: 13%).Does not fit

Question
Does the member trade the same stock in the same direction as other members at the same time more than chance predicts?

Insider signature
Shared nonpublic information spreads through networks and shows up as clustered trades.

Analyst note
Co-traded share 0.212; circular-shift null mean 0.132, 95th pct 0.239, p = 0.110. Co-traded signed CAR 0.0141, p = 0.443.

Evidence
Statistical
Co-traded share
21.2%
p-value
0.443
Holm-adjusted p
1.000
BH q-value
0.902
Robust to variants
Yes
All computed statistics (10)
n118
cotraded_share0.2119
null_mean0.1324
null_p950.2390
excess_p0.1100
cotraded_share_wo_top0.1525
excess_p_wo_top0.3400
cotraded_car0.0141
cotraded_car_ci[-0.0256, 0.0539]
cotraded_car_p0.4426
Robustness variantReadingEstimate
Without M001157, the member with the most trades, in the co-trade indexDoes not fit15.3%
T16Options and leverageNo option trades were reported.Does not fit

Question
Does the member use options, and do option trades point the right way?

Insider signature
Informed traders favour options because leverage raises the payoff to private information.

Analyst note
No option trades were reported.

Evidence
Descriptive
Margin δ
0.5% per trade over 21 days
All computed statistics (2)
option_trades0
option_share0
T6Control and independenceNo documentary record of trading arrangements or absence periods was available.Not assessed

Question
Does the member direct the trades, and does trading change when the member's access to information changes?

Insider signature
The person holding the information directs the trade.

Analyst note
No documentary record of trading arrangements or absence periods was available.

Evidence
Not computed
T9Policy-topic overlap21 priced trades fell in affected industries in the 30 days before the member's committee events, but on only 4 distinct dates; at least 10 dates are needed for a date-clustered comparison.Not assessed

Question
Did trades in stocks affected by the member's legislative work come before votes and move the right way?

Insider signature
Trading on knowledge of legislation before it is public.

Analyst note
21 priced trades fell in affected industries in the 30 days before the member's committee events, but on only 4 distinct dates; at least 10 dates are needed for a date-clustered comparison.

Evidence
Descriptive
Margin δ
0.5% per trade
All computed statistics (4)
n21
n_other72
trade_dates4
events3678
T10Behavior after scrutinyNo documented scrutiny date; the estimated change point in trading activity is shown for reference.Not assessed

Question
Did trading change after press scrutiny or an ethics inquiry?

Insider signature
A member who trades on information has an incentive to keep control of trading after scrutiny.

Analyst note
No documented scrutiny date; the estimated change point in trading activity is shown for reference. Estimated change point 2015-01-29 (permutation p = 0.220).

Evidence
Descriptive
All computed statistics (5)
changepoint2015-01-29
changepoint_LR6.7112
changepoint_p0.2200
tradeday_rate_before1
tradeday_rate_after0.0128
T14Family-account trades4% of trades were in a spouse's or dependent's name; returns not computed for them.Not assessed

Question
Do trades in a spouse's or dependent's name do better than the member's own?

Insider signature
Routing informed trades through family accounts.

Analyst note
4% of trades were in a spouse's or dependent's name; returns not computed for them.

Evidence
Descriptive
Margin δ
0.5% per trade over 21 days
All computed statistics (3)
family_trades1
family_share0.0400
owner_unknown93

Documented episodes

Trades placed near a documented market or policy event, and which way the market moved next.

Market move on 2015-08-21
–
1 trade(s) in the prior five trading days
-3.01%

S&P 500 (SPY) daily move (Aug 21, 2015)

Right way.

Market move on 2015-08-24
–
1 trade(s) in the prior five trading days
-4.21%

S&P 500 (SPY) daily move (Aug 24, 2015)

Right way.

Market move on 2018-12-26
–
2 trade(s) in the prior five trading days
+5.05%

S&P 500 (SPY) daily move (Dec 26, 2018)

Right way.

Market move on 2022-03-07
–
1 trade(s) in the prior five trading days
-2.95%

S&P 500 (SPY) daily move (Mar 7, 2022)

Right way.

Market move on 2022-03-09
–
1 trade(s) in the prior five trading days
+2.68%

S&P 500 (SPY) daily move (Mar 9, 2022)

Wrong way.

Disclosed trades per monthPurchasesSales
2015201620172018201920202021202220232024

Largest positions traded

CompanyTradesDisclosed value
RPM RPM International Inc.14$329K to $810K
Alaska State General Obligation Bond1$250K to $500K
MSFT MSFT5$68K to $195K
SPY SPDR S&P 500 ETF3$66K to $165K
GOOG GOOG6$20K to $125K
WCMIX WCM Focused International Growth Fund Institutiona1$50K to $100K
AAPL AAPL4$18K to $95K
AMZN AMZN5$5,005 to $75K

All disclosed trades

Amounts are the ranges reported on the filing. Late filings are those made more than 45 days after the trade.

JSON · CSV
119 trades
Trade dateAssetTypeAmountOwnerFiled after5-day CAR
Jan 24, 2024RPM RPMSale$15K to $50Kunknown16 d−0.5%Senate eFD search
Aug 22, 2023AAPL AAPLSale$15K to $50Kunknown27 d−0.6%Senate eFD search
Aug 22, 2023ZTS ZTSSale$1,001 to $15Kunknown27 d−3.4%Senate eFD search
Aug 22, 2023ALGN ALGNSale$1,001 to $15Kunknown27 d+0.5%Senate eFD search
Aug 22, 2023AME AMESale$1,001 to $15Kunknown27 d−0.5%Senate eFD search
Aug 22, 2023SCHW SCHWSale$1,001 to $15Kunknown27 d−3.6%Senate eFD search
Aug 22, 2023LH LHCommitteeSale$1,001 to $15Kunknown27 d+3.7%Senate eFD search
Aug 22, 2023PPG PPGSale$1,001 to $15Kunknown27 d+1.5%Senate eFD search
Aug 22, 2023PNC PNCSale$1,001 to $15Kunknown27 d+0.9%Senate eFD search
Aug 22, 2023TJX TJXSale$15K to $50Kunknown27 d+0.2%Senate eFD search
Aug 22, 2023BMY BMYSale$1,001 to $15Kunknown27 d−1.2%Senate eFD search
Aug 22, 2023CVX CVXSale$1,001 to $15Kunknown27 d+1.3%Senate eFD search
Aug 22, 2023CVS CVSCommitteeSale$1,001 to $15Kunknown27 d+0.5%Senate eFD search
Aug 22, 2023JNJ JNJSale$1,001 to $15Kunknown27 d+1.1%Senate eFD search
Aug 22, 2023BKNG BKNGSale$1,001 to $15Kunknown27 d+2.0%Senate eFD search
Aug 22, 2023TMO TMOSale$1,001 to $15Kunknown27 d−3.2%Senate eFD search
Aug 22, 2023AXP AXPSale$1,001 to $15Kunknown27 d+2.3%Senate eFD search
Aug 22, 2023LUV LUVCommitteeSale$1,001 to $15Kunknown27 d+1.4%Senate eFD search
Aug 22, 2023MSFT MSFTSale$50K to $100Kunknown27 d+1.6%Senate eFD search
Aug 22, 2023ACN ACNSale$15K to $50Kunknown27 d−1.7%Senate eFD search
Aug 22, 2023MA MASale$1,001 to $15Kunknown27 d−0.7%Senate eFD search
Aug 22, 2023JPM JPMSale$1,001 to $15Kunknown27 d+1.1%Senate eFD search
Aug 22, 2023COST COSTSale$1,001 to $15Kunknown27 d+1.0%Senate eFD search
Aug 22, 2023LRCX LRCXSale$1,001 to $15Kunknown27 d+2.0%Senate eFD search
Aug 22, 2023NTRS NTRSSale$1,001 to $15Kunknown27 d+0.1%Senate eFD search
Aug 22, 2023HON HONSale$1,001 to $15Kunknown27 d+0.3%Senate eFD search
Aug 22, 2023GOOG GOOGCommitteeSale$15K to $50Kunknown27 d−1.2%Senate eFD search
Aug 22, 2023AMZN AMZNSale$1,001 to $15Kunknown27 d+3.0%Senate eFD search
Aug 22, 2023BLK BLKSale$1,001 to $15Kunknown27 d−0.5%Senate eFD search
Aug 22, 2023PXD PXDSale$1,001 to $15Kunknown27 d–Senate eFD search
Aug 22, 2023ULTA ULTASale$1,001 to $15Kunknown27 d+5.2%Senate eFD search
Aug 22, 2023CHD CHDSale$1,001 to $15Kunknown27 d−1.5%Senate eFD search
Aug 22, 2023TSCO TSCOSale$1,001 to $15Kunknown27 d−1.7%Senate eFD search
Aug 22, 2023APH APHSale$1,001 to $15Kunknown27 d+0.3%Senate eFD search
Mar 17, 2023WFC WFCSale$1,001 to $15Kunknown40 d+5.4%Senate eFD search
Feb 21, 2023CHD CHDPurchase$1,001 to $15Kunknown23 d+0.3%Senate eFD search
Feb 10, 2023SCHW SCHWSale$1,001 to $15Kunknown34 d+0.2%Senate eFD search
Feb 10, 2023GOOG GOOGCommitteePurchase$1,001 to $15Kunknown34 d+0.5%Senate eFD search
Feb 10, 2023CHD CHDPurchase$1,001 to $15Kunknown34 d+1.7%Senate eFD search
Jan 10, 2023BMY BMYSale$1,001 to $15Kunknown34 d−0.0%Senate eFD search
Jan 10, 2023CVS CVSCommitteeSale$1,001 to $15Kunknown34 d+3.0%Senate eFD search
Jan 10, 2023ALGN ALGNPurchase$1,001 to $15Kunknown34 d+7.3%Senate eFD search
Jan 10, 2023AMZN AMZNPurchase$1,001 to $15Kunknown34 d+6.4%Senate eFD search
Jan 10, 2023PXD PXDSale$1,001 to $15Kunknown34 d–Senate eFD search
Jan 10, 2023BKNG BKNGSale$1,001 to $15Kunknown34 d−3.1%Senate eFD search
Jan 10, 2023ZTS ZTSPurchase$1,001 to $15Kunknown34 d+3.8%Senate eFD search
Jan 10, 2023ULTA ULTASale$1,001 to $15Kunknown34 d−1.3%Senate eFD search
Jan 10, 2023JPM JPMSale$1,001 to $15Kunknown34 d+1.5%Senate eFD search
Nov 30, 2022MLM MLMCommitteeSale$1,001 to $15Kunknown21 d+0.1%Senate eFD search
Nov 30, 2022ADBE ADBESale$1,001 to $15Kunknown21 d−1.0%Senate eFD search