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U.S. Senate

Sen. Pete Ricketts

Republican · Senator from NE

Banking, Housing, and Urban AffairsBudgetEnvironment and Public WorksForeign Relations
Results across 16 tests
Fits patternOpen questionDoes not fitNot assessedScreening signal

No test fits; open questions on trade size, breadth and concentration, anticipation of large stock moves.

Trades disclosed
25
Sep 21, 2023 to Sep 21, 2023
Companies traded
25
Disclosed value
$1.9M–$4.3M
Sum of reported ranges
Filed after 45 days
0
Median filing lag 29 days

Scorecard

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

T1Trade size0% of 25 trades were in the lowest disclosure band ($1,001-$15,000).Open question

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 0.000, 90% Wilson [0.000, 0.098]. No firm-event calendar, so the event-linked size gap was not computed.

Evidence
Descriptive
Lowest-band share
0.0% [0.0%, 9.8%] 90%
0Estimate
This member0.0%
All computed statistics (5)
n25
lowest_band_share0
lowest_band_ci[0, 0.0977]
share_over_50k1
max_z0
T2Breadth and concentration25 different companies; the effective number of equally sized positions is 22 and trading spans 83% 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 0.046 (identified set [0.040, 0.062]); trade-count HHI 0.040 vs. 95th percentile 0.046 of 25 random draws from all congressional trades (p = 0.992). Normalized sector entropy 0.83 [nan, nan]. Top three issuers (ABT, BRK.B, EQNR) carry at least 8% of dollar volume.

Evidence
Statistical
Effective number of issuers
22 [16, 25] 90%
0Estimate
This member22
All computed statistics (13)
n25
issuers25
hhi_mid0.0460
hhi_bounds[0.0400, 0.0618]
n_eff21.7350
hhi_count0.0400
peer_benchmark_p950.0464
peer_benchmark_p0.9920
sector_entropy0.8345
sector_entropy_ci[–, –]
top3_share_lower0.0779
top3[ABT, BRK.B, EQNR]
top3_tied_to_eventsfalse
T12Anticipation of large stock moves1 trades were followed within two weeks by a large company-specific move; 1 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 1.00, Clopper-Pearson [0.05, 1.00], exact one-sided p = 0.500; threshold |AR| > 3 sigma.

Evidence
Statistical
Hit rate
100.0% [5.0%, 100.0%] 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 member100.0%
All computed statistics (6)
n1
hits1
hit_rate1
ci[0.0500, 1]
priced24
share_followed0.0417
T3Cadence and event proximity100% of trading days were batches of three or more companies; 0% of trades look routine; 0.0% of trades came within five trading days before a large company-specific move (chance alone: 0.0%).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 1/1, Wilson [0.27, 1.00]; index of dispersion nan (chi-square p = 1); routine share 0.00 (portfolio-routine or Cohen-Malloy-Pomorski two-year rule). Proximity share 0.000 vs. circular-shift null mean 0.000, p = 1.000.

Evidence
Statistical
Batch-day share
100.0% [27.0%, 100.0%] 90%
p-value
1.000
Holm-adjusted p
1.000
BH q-value
1.000
0Estimate
This member100.0%
All computed statistics (14)
n25
trade_days1
batch_share_trades1
batch_day_share1
batch_day_ci[0.2699, 1]
dispersion_index–
dispersion_p1
routine_share0
proximity_share0
proximity_null_mean0
proximity_null_p950
proximity_p1
proximity_nonroutine0
proximity_routine0
T7Disclosure timeliness0 of 25 trades (0.0%) were disclosed late; median lag 29 days.Does not fit

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 0.000, Wilson [0.000, 0.098]; 90th percentile lag 29 days; longest 29 days.

Evidence
Descriptive
Late share
0.0% [0.0%, 9.8%] 90%
0Estimate
This member0.0%
All computed statistics (15)
n25
amendment_rows_excluded0
late0
late_from_trade0
excused_by_notification0
late_share0
late_ci[0, 0.0977]
median_lag29
p90_lag29
max_lag29
filings1
late_filings0
late_priced0
timely_priced24
late_priced_dates0
T8Committee overlap21% of the member's mapped trading by dollar value was in industries their committees oversee, against 29% 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 SSBK, SSBU, SSEV, SSFR; jurisdiction sectors Aerospace & Defense, Commodity Chemicals, Construction & Engineering, Construction Materials, Electric Utilities, Environmental & Facilities Services, Financials, Real Estate, Water Utilities. Dollar share 0.213 (identified set [0.105, 0.383], bootstrap nan-nan); benchmarks S&P 500 0.293, congressional peers 0.286.

Evidence
Descriptive
Jurisdiction excess share
-8.0%
Margin δ
0.5% per trade over 21 days
All computed statistics (15)
n25
in_jurisdiction_trades6
share0.2127
share_bounds[0.1053, 0.3830]
share_ci[–, –]
benchmark_sp5000.2931
benchmark_peers0.2861
excess-0.0804
excess_ci[–, –]
committees[SSBK, SSBU, SSEV, SSFR]
jurisdiction_sectors[Aerospace & Defense, Commodity Chemicals, Construction & Engineering, Construction Materials, Electric Utilities, Environmental & Facilities Services, Financials, Real Estate, 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 66% 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 0.0036, 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)
raw0.0036
posterior_mean-0.0028
posterior_sd0.0015
congress_mean-0.0028
tau20
percentile0.6642
members_compared134
lower95-0.0058
T13Co-trading with other members12% of trades had another member trading the same stock the same way within a week (chance alone: 12%).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 0.120; circular-shift null mean 0.120, 95th pct 0.120, p = 1.000. Co-traded signed CAR 0.0048, p = 0.459.

Evidence
Statistical
Co-traded share
12.0%
p-value
0.459
Holm-adjusted p
1.000
BH q-value
0.902
Robust to variants
Yes
All computed statistics (10)
n25
cotraded_share0.1200
null_mean0.1200
null_p950.1200
excess_p1
cotraded_share_wo_top0.1200
excess_p_wo_top1
cotraded_car0.0048
cotraded_car_ci[-0.1420, 0.1516]
cotraded_car_p0.4594
Robustness variantReadingEstimate
Without M001157, the member with the most trades, in the co-trade indexDoes not fit12.0%
T15Short-swing round tripsNo purchase and sale of the same stock within six months.Does not fit

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
No purchase and sale of the same stock within six months.

Evidence
Descriptive
Margin δ
0.5% per trade over 21 days
All computed statistics (2)
round_trips0
share_in_round_trips0
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
T4Event timing (abnormal returns)Across 24 priced trades, purchases and sales moved 0.36% in the trade's direction relative to the market over the next month on average.Inconclusive (too few trades)

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) = 0.0036; 90% KP interval [-0.0325, 0.0398]; t_BMP = 1.11, r-bar = 0.111, t_KP = 0.55, Patell Z = 1.00, Corrado Z = 1.55. Dollar-weighted identified set [-0.0171, 0.0194].

Evidence
Statistical
Mean signed 21-day CAR
+0.36% [−3.25%, +3.98%] 90%
p-value
0.292
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+0.36%
All computed statistics (16)
n24
theta0.0036
ci[-0.0325, 0.0398]
p0.2922
t_kp0.5548
rbar0.1107
se_cs0.0106
se_kp0.0211
t_cs0.3425
t_bmp1.1079
patell_z0.9960
corrado_z1.5490
dollar_weighted_bounds[-0.0171, 0.0194]
calendar_time–
calendar_alpha_ci[–, –]
by_horizon[object Object]
Robustness variantReadingEstimate
Horizon 5 daysOpen question+0.11%
Horizon 63 daysOpen question−0.40%
Excluding largest batch dateNot assessed–
Self-owned accounts onlyNot assessed–
Dollar-weighted (bounds)Open question+1.94%
T5Direction before market-wide shocksNo market-wide shocks or documented events fell within five trading days after the member's trades.Not assessed

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
No market-wide shocks or documented events fell within five trading days after the member's trades.

Evidence
Descriptive
Margin δ
10 points above a coin flip
All computed statistics (1)
n_episodes0
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 overlap6 priced trades fell in affected industries in the 30 days before the member's committee events and 18 did not; at least 10 of each are needed to compare them.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
6 priced trades fell in affected industries in the 30 days before the member's committee events and 18 did not; at least 10 of each are needed to compare them.

Evidence
Descriptive
Margin δ
0.5% per trade
All computed statistics (3)
n6
n_other18
events2596
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 None (permutation p = 1.000).

Evidence
Descriptive
All computed statistics (5)
changepoint–
changepoint_LR–
changepoint_p1
tradeday_rate_before–
tradeday_rate_after–
T14Family-account tradesOnly 0 trades name the account owner; at least 10 are needed.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
Only 0 trades name the account owner; at least 10 are needed.

Evidence
Not computed
Margin δ
0.5% per trade over 21 days
All computed statistics (1)
owner_unknown25

Largest positions traded

CompanyTradesDisclosed value
UNP UNP1$100K to $250K
PM PM1$100K to $250K
EQNR EQNR1$100K to $250K
PG PG1$100K to $250K
BRK.B BRK.B1$100K to $250K
JNJ JNJ1$100K to $250K
GD GD1$100K to $250K
ABT ABT1$100K to $250K

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
25 trades
Trade dateAssetTypeAmountOwnerFiled after5-day CAR
Sep 21, 2023CVS CVSSale$50K to $100Kunknown29 d+1.4%Senate eFD search
Sep 21, 2023ADP ADPSale$50K to $100Kunknown29 d−2.7%Senate eFD search
Sep 21, 2023UNP UNPSale$100K to $250Kunknown29 d+2.8%Senate eFD search
Sep 21, 2023PM PMSale$100K to $250Kunknown29 d+1.1%Senate eFD search
Sep 21, 2023NTR NTRSale$50K to $100Kunknown29 d–Senate eFD search
Sep 21, 2023EQNR EQNRSale$100K to $250Kunknown29 d−3.1%Senate eFD search
Sep 21, 2023YUM YUMSale$50K to $100Kunknown29 d+0.3%Senate eFD search
Sep 21, 2023PG PGSale$100K to $250Kunknown29 d+3.7%Senate eFD search
Sep 21, 2023BRK.B BRK.BCommitteeSale$100K to $250Kunknown29 d+1.5%Senate eFD search
Sep 21, 2023CUBE CUBECommitteeSale$50K to $100Kunknown29 d−0.2%Senate eFD search
Sep 21, 2023WAL WALCommitteeSale$50K to $100Kunknown29 d−0.5%Senate eFD search
Sep 21, 2023JNJ JNJSale$100K to $250Kunknown29 d+2.8%Senate eFD search
Sep 21, 2023PNC PNCCommitteeSale$50K to $100Kunknown29 d−2.2%Senate eFD search
Sep 21, 2023GD GDCommitteeSale$100K to $250Kunknown29 d−0.8%Senate eFD search
Sep 21, 2023APA APASale$50K to $100Kunknown29 d−6.0%Senate eFD search
Sep 21, 2023CF CFSale$50K to $100Kunknown29 d−4.1%Senate eFD search
Sep 21, 2023ABT ABTSale$100K to $250Kunknown29 d+0.1%Senate eFD search
Sep 21, 2023MRK MRKSale$50K to $100Kunknown29 d+2.6%Senate eFD search
Sep 21, 2023PLD PLDCommitteeSale$50K to $100Kunknown29 d+1.3%Senate eFD search
Sep 21, 2023MDT MDTSale$50K to $100Kunknown29 d+1.5%Senate eFD search
Sep 21, 2023EMR EMRSale$100K to $250Kunknown29 d−1.0%Senate eFD search
Sep 21, 2023VZ VZSale$50K to $100Kunknown29 d+1.5%Senate eFD search
Sep 21, 2023KO KOSale$100K to $250Kunknown29 d+2.6%Senate eFD search
Sep 21, 2023UNH UNHSale$100K to $250Kunknown29 d−2.2%Senate eFD search
Sep 21, 2023MCD MCDSale$100K to $250Kunknown29 d+2.0%Senate eFD search