Sen. Alan Armstrong
Republican · Senator from OK
No test fits; open questions on breadth and concentration, disclosure timeliness, short-swing round trips and more.
Scorecard
Select a test to see the estimate, interval, adjusted p-values and robustness checks.
T2Breadth and concentration345 different companies; the effective number of equally sized positions is 2 and trading spans 46% 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 0.528 (identified set [0.128, 0.840]); trade-count HHI 0.003 vs. 95th percentile 0.006 of 369 random draws from all congressional trades (p = 1.000). Normalized sector entropy 0.46 [0.06, 0.88]. Top three issuers (WMB, AAPL, GLW) carry at least 39% of dollar volume.
- Evidence
- Statistical
- Effective number of issuers
- 2 [1, 8] 90%
All computed statistics (13)
| n | 369 |
| issuers | 345 |
| hhi_mid | 0.5276 |
| hhi_bounds | [0.1285, 0.8405] |
| n_eff | 1.8955 |
| hhi_count | 0.0031 |
| peer_benchmark_p95 | 0.0060 |
| peer_benchmark_p | 1 |
| sector_entropy | 0.4581 |
| sector_entropy_ci | [0.0621, 0.8761] |
| top3_share_lower | 0.3881 |
| top3 | [WMB, AAPL, GLW] |
| top3_tied_to_events | true |
T7Disclosure timeliness365 of 369 trades (98.9%) were disclosed late; median lag 116 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 0.989, Wilson [0.976, 0.995]; 90th percentile lag 116 days; longest 119 days.
- Evidence
- Descriptive
- Late share
- 98.9% [97.6%, 99.5%] 90%
All computed statistics (15)
| n | 369 |
| amendment_rows_excluded | 0 |
| late | 365 |
| late_from_trade | 365 |
| excused_by_notification | 0 |
| late_share | 0.9892 |
| late_ci | [0.9761, 0.9951] |
| median_lag | 116 |
| p90_lag | 116 |
| max_lag | 119 |
| filings | 2 |
| late_filings | 1 |
| late_priced | 294 |
| timely_priced | 2 |
| late_priced_dates | 4 |
T15Short-swing round trips5 buy-and-sell round trips within six months; in the month after opening, those positions moved +2.04% 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) 0.0204 [-0.0532, 0.0939], t_KP = 0.83, over 5 priced openings. Realized market-adjusted return to the closing trade averaged +1.43% (win rate 60%); it is shown for context only because exit timing is chosen after the fact.
- Evidence
- Statistical
- Opening-trade signed 21-day CAR
- +2.04% [−5.32%, +9.39%] 90%
- p-value
- 0.226
- Holm-adjusted p
- 1.000
- BH q-value
- 0.999
- Margin δ
- 0.5% per trade over 21 days
All computed statistics (9)
| round_trips | 5 |
| share_in_round_trips | 0.0271 |
| priced | 5 |
| realized_mean | 0.0143 |
| realized_win_rate | 0.6000 |
| opening_car | 0.0204 |
| ci | [-0.0532, 0.0939] |
| p | 0.2258 |
| openings_priced | 5 |
T16Options and leverage3 option trades (1% of all reported trades).Open question
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
3 option trades (1% of all reported trades).
- Evidence
- Descriptive
- Option share
- 0.8%
- Margin δ
- 0.5% per trade over 21 days
All computed statistics (6)
| option_trades | 3 |
| option_share | 0.0081 |
| option_car | – |
| option_ci | [–, –] |
| option_p | – |
| priced | 1 |
T1Trade size78% of 369 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 0.783, 90% Wilson [0.746, 0.816]. 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
- 78.3% [74.6%, 81.6%] 90%
- p-value
- 1.000
- Holm-adjusted p
- 1.000
- BH q-value
- 1.000
All computed statistics (9)
| n | 369 |
| lowest_band_share | 0.7832 |
| lowest_band_ci | [0.7459, 0.8164] |
| share_over_50k | 0.0542 |
| max_z | 0 |
| size_gap | 0 |
| size_gap_p | 1 |
| event_linked | 10 |
| event_linked_outliers | 0 |
T3Cadence and event proximity50% of trading days were batches of three or more companies; 0% of trades look routine; 2.7% of trades came within five trading days before a large company-specific move (chance alone: 7.6%).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 4/8, Wilson [0.25, 0.75]; index of dispersion 243.02 (chi-square p = 0); routine share 0.00 (portfolio-routine or Cohen-Malloy-Pomorski two-year rule). Proximity share 0.027 vs. circular-shift null mean 0.076, p = 0.846.
- Evidence
- Statistical
- Batch-day share
- 50.0% [24.9%, 75.1%] 90%
- p-value
- 0.846
- Holm-adjusted p
- 1.000
- BH q-value
- 1.000
All computed statistics (14)
| n | 369 |
| trade_days | 8 |
| batch_share_trades | 0.9892 |
| batch_day_share | 0.5000 |
| batch_day_ci | [0.2486, 0.7514] |
| dispersion_index | 243.0205 |
| dispersion_p | 0 |
| routine_share | 0 |
| proximity_share | 0.0271 |
| proximity_null_mean | 0.0759 |
| proximity_null_p95 | 0.1355 |
| proximity_p | 0.8460 |
| proximity_nonroutine | 0.0271 |
| proximity_routine | 0 |
T8Committee overlap3% of the member's mapped trading by dollar value was in industries their committees oversee, against 12% 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 SLIA, SSHR; jurisdiction sectors Health Care, Human Resource & Employment Services. Dollar share 0.033 (identified set [0.008, 0.147], bootstrap 0.001-0.122); benchmarks S&P 500 0.123, congressional peers 0.114.
- Evidence
- Descriptive
- Jurisdiction excess share
- -8.9% [-12.2%, -0.1%] 90%
- Margin δ
- 0.5% per trade over 21 days
All computed statistics (15)
| n | 365 |
| in_jurisdiction_trades | 53 |
| share | 0.0333 |
| share_bounds | [0.0075, 0.1472] |
| share_ci | [6.15e-4, 0.1216] |
| benchmark_sp500 | 0.1228 |
| benchmark_peers | 0.1135 |
| excess | -0.0894 |
| excess_ci | [-0.1222, -0.0012] |
| committees | [SLIA, SSHR] |
| jurisdiction_sectors | [Health Care, Human Resource & Employment Services] |
| regression_error | Error 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 11% 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 -0.0227, 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
All computed statistics (8)
| raw | -0.0227 |
| posterior_mean | -0.0028 |
| posterior_sd | 0.0015 |
| congress_mean | -0.0028 |
| tau2 | 0 |
| percentile | 0.1119 |
| members_compared | 134 |
| lower95 | -0.0058 |
T13Co-trading with other members11% of trades had another member trading the same stock the same way within a week (chance alone: 8%).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 0.106; circular-shift null mean 0.079, 95th pct 0.127, p = 0.130. Co-traded signed CAR -0.0017, p = 0.632.
- Evidence
- Statistical
- Co-traded share
- 10.6%
- p-value
- 0.632
- Holm-adjusted p
- 1.000
- BH q-value
- 0.902
- Robust to variants
- Yes
All computed statistics (10)
| n | 369 |
| cotraded_share | 0.1057 |
| null_mean | 0.0794 |
| null_p95 | 0.1274 |
| excess_p | 0.1300 |
| cotraded_share_wo_top | 0.0867 |
| excess_p_wo_top | 0.3300 |
| cotraded_car | -0.0017 |
| cotraded_car_ci | [-0.0478, 0.0444] |
| cotraded_car_p | 0.6325 |
| Robustness variant | Reading | Estimate |
|---|---|---|
| Without M001157, the member with the most trades, in the co-trade index | Does not fit | 8.7% |
T4Event timing (abnormal returns)Across 296 priced trades, purchases and sales moved 2.27% against 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) = -0.0227; 90% KP interval [-0.0569, 0.0116]; t_BMP = -4.59, r-bar = 0.039, t_KP = -1.27, Patell Z = -4.80, Corrado Z = -5.52. Dollar-weighted identified set [-0.0044, 0.0437].
- Evidence
- Statistical
- Mean signed 21-day CAR
- −2.27% [−5.70%, +1.16%] 90%
- p-value
- 0.897
- 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
All computed statistics (16)
| n | 296 |
| theta | -0.0227 |
| ci | [-0.0570, 0.0116] |
| p | 0.8969 |
| t_kp | -1.2671 |
| rbar | 0.0393 |
| se_cs | 0.0057 |
| se_kp | 0.0208 |
| t_cs | -3.9516 |
| t_bmp | -4.5865 |
| patell_z | -4.7973 |
| corrado_z | -5.5175 |
| dollar_weighted_bounds | [-0.0044, 0.0437] |
| calendar_time | – |
| calendar_alpha_ci | [–, –] |
| by_horizon | [object Object] |
| Robustness variant | Reading | Estimate |
|---|---|---|
| Horizon 5 days | Open question | +0.17% |
| Horizon 63 days | Open question | −0.87% |
| Excluding largest batch date | Open question | −2.21% |
| Self-owned accounts only | Not assessed | – |
| Dollar-weighted (bounds) | Open question | +4.37% |
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_episodes | 0 |
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 overlap44 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
44 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)
| n | 44 |
| n_other | 252 |
| trade_dates | 4 |
| events | 1026 |
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 2026-04-01 (permutation p = 0.006).
- Evidence
- Descriptive
All computed statistics (5)
| changepoint | 2026-04-01 |
| changepoint_LR | 12.4899 |
| changepoint_p | 0.0060 |
| tradeday_rate_before | 0.6667 |
| tradeday_rate_after | 0.0392 |
T12Anticipation of large stock moves46 trades were followed within two weeks by a large company-specific move; 25 were on the profitable side.Inconclusive (too few trades)
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 0.54, Clopper-Pearson [0.41, 0.67], exact one-sided p = 0.329; threshold |AR| > 3 sigma.
- Evidence
- Statistical
- Hit rate
- 54.3% [41.3%, 67.0%] 90%
- p-value
- 0.329
- Holm-adjusted p
- 1.000
- BH q-value
- 1.000
- Margin δ
- 10 points above a coin flip
All computed statistics (6)
| n | 46 |
| hits | 25 |
| hit_rate | 0.5435 |
| ci | [0.4125, 0.6701] |
| priced | 341 |
| share_followed | 0.1349 |
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_unknown | 369 |
Largest positions traded
| Company | Trades | Disclosed value |
|---|---|---|
| WMB Option Type: Call Strike price: $75.00 Expires: 2026-08-21 | 4 | $5.3M to $25.6M |
| AAPL AAPL | 2 | $251K to $515K |
| GLW GLW | 1 | $100K to $250K |
| HD HD | 2 | $65K to $150K |
| RACE RACE | 2 | $51K to $115K |
| FDX FDX | 2 | $51K to $115K |
| HON HON | 2 | $51K to $115K |
| GOOG GOOG | 2 | $51K to $115K |
All disclosed trades
Amounts are the ranges reported on the filing. Late filings are those made more than 45 days after the trade.
| Trade date | Asset | Type | Amount | Owner | Filed after | 5-day CAR | |
|---|---|---|---|---|---|---|---|
| Aug 20, 2026 | WMB Option Type: Call Strike price: $75.00 Expires: 2026-08-21 | Purchase | $15K to $50K | unknown | 28 d | +2.8% | Senate eFD search |
| Aug 19, 2026 | WMB Option Type: Call Strike price: $75.00 Expires: 2026-08-21 | Purchase | $1,001 to $15K | unknown | 29 d | +1.0% | Senate eFD search |
| Jun 24, 2026 | WMB WMB | Sale | $5M to $25M | unknown | 27 d | +4.7% | Senate eFD search |
| Jun 22, 2026 | WMB Option Type: Call Strike price: $75.00 Expires: 2026-08-21 | Sale | $250K to $500K | unknown | 29 d | +0.2% | Senate eFD search |
| Mar 31, 2026 | ASML ASML | Purchase | $1,001 to $15K | unknown | 112 d | +1.0% | Senate eFD search |
| Mar 31, 2026 | AZN AZNCommittee | Purchase | $1,001 to $15K | unknown | 112 d | +1.1% | Senate eFD search |
| Mar 31, 2026 | NVS NVSCommittee | Purchase | $1,001 to $15K | unknown | 112 d | −0.8% | Senate eFD search |
| Mar 31, 2026 | SAN SAN | Purchase | $1,001 to $15K | unknown | 112 d | +3.1% | Senate eFD search |
| Mar 30, 2026 | ORLY ORLY | Purchase | $1,001 to $15K | unknown | 113 d | −1.5% | Senate eFD search |
| Mar 30, 2026 | IX IX | Purchase | $1,001 to $15K | unknown | 113 d | −1.5% | Senate eFD search |
| Mar 30, 2026 | HSBC HSBC | Purchase | $15K to $50K | unknown | 113 d | +3.1% | Senate eFD search |
| Mar 30, 2026 | SONY SONY | Purchase | $15K to $50K | unknown | 113 d | +1.7% | Senate eFD search |
| Mar 30, 2026 | CHKP CHKP | Purchase | $1,001 to $15K | unknown | 113 d | +3.3% | Senate eFD search |
| Mar 30, 2026 | TEVA TEVACommittee | Purchase | $1,001 to $15K | unknown | 113 d | −1.8% | Senate eFD search |
| Mar 30, 2026 | STLA STLA | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | AZN AZNCommittee | Purchase | $15K to $50K | unknown | 113 d | +1.0% | Senate eFD search |
| Mar 30, 2026 | SAN SAN | Purchase | $15K to $50K | unknown | 113 d | +1.5% | Senate eFD search |
| Mar 30, 2026 | NVS NVSCommittee | Purchase | $15K to $50K | unknown | 113 d | −1.4% | Senate eFD search |
| Mar 30, 2026 | UBS UBS | Purchase | $15K to $50K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | MT MT | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | TM TM | Purchase | $15K to $50K | unknown | 113 d | −4.0% | Senate eFD search |
| Mar 30, 2026 | MSFT MSFT | Purchase | $1,001 to $15K | unknown | 113 d | +0.3% | Senate eFD search |
| Mar 30, 2026 | NVO NVOCommittee | Purchase | $15K to $50K | unknown | 113 d | +1.1% | Senate eFD search |
| Mar 30, 2026 | ESLT ESLT | Purchase | $1,001 to $15K | unknown | 113 d | +9.0% | Senate eFD search |
| Mar 30, 2026 | EA EA | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | CCEP CCEP | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | UBER UBER | Purchase | $1,001 to $15K | unknown | 113 d | −1.5% | Senate eFD search |
| Mar 30, 2026 | PSO PSO | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | BBVA BBVA | Purchase | $15K to $50K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | DGX DGXCommittee | Purchase | $1,001 to $15K | unknown | 113 d | −1.2% | Senate eFD search |
| Mar 30, 2026 | LOGI LOGI | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | SAP SAP | Purchase | $15K to $50K | unknown | 113 d | −1.9% | Senate eFD search |
| Mar 30, 2026 | STM STM | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | HMC HMC | Purchase | $1,001 to $15K | unknown | 113 d | −4.2% | Senate eFD search |
| Mar 30, 2026 | ING ING | Purchase | $1,001 to $15K | unknown | 113 d | +4.0% | Senate eFD search |
| Mar 30, 2026 | CIEN CIEN | Purchase | $1,001 to $15K | unknown | 113 d | +10.6% | Senate eFD search |
| Mar 30, 2026 | SCHW SCHW | Purchase | $1,001 to $15K | unknown | 113 d | −3.3% | Senate eFD search |
| Mar 30, 2026 | NBIS NBIS | Purchase | $1,001 to $15K | unknown | 113 d | +12.5% | Senate eFD search |
| Mar 30, 2026 | VRSN VRSN | Purchase | $1,001 to $15K | unknown | 113 d | +8.6% | Senate eFD search |
| Mar 30, 2026 | MNDY MNDY | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | SNY SNYCommittee | Purchase | $15K to $50K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | AAPL AAPL | Purchase | $1,001 to $15K | unknown | 113 d | −2.6% | Senate eFD search |
| Mar 30, 2026 | JNJ JNJCommittee | Purchase | $1,001 to $15K | unknown | 113 d | −3.0% | Senate eFD search |
| Mar 30, 2026 | GOOG GOOG | Purchase | $1,001 to $15K | unknown | 113 d | +5.8% | Senate eFD search |
| Mar 30, 2026 | LYG LYG | Purchase | $1,001 to $15K | unknown | 113 d | +3.6% | Senate eFD search |
| Mar 30, 2026 | ICL ICL | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | NMR NMR | Purchase | $1,001 to $15K | unknown | 113 d | – | Senate eFD search |
| Mar 30, 2026 | WELL WELL | Purchase | $1,001 to $15K | unknown | 113 d | +1.3% | Senate eFD search |
| Mar 30, 2026 | RIO RIO | Purchase | $15K to $50K | unknown | 113 d | +2.8% | Senate eFD search |
| Mar 30, 2026 | BTI BTI | Purchase | $15K to $50K | unknown | 113 d | −0.5% | Senate eFD search |