Notes

A Python script archive contains a study with the following calculations: xis equals 1 divided by peak minus 1, with a minimum value found along axis 1. A simulation dictionary, sim, is defined with parameters including training half Kelly capital, 20000 paths, 10 trades per path, median total percentage, probability of loss, and probability of a 20% drawdown. The simulation also calculates the 5th percentile of total percentage. The script then calculates financing and acquisition sensitivity in USD millions, with working capital, wc, equal to the sum of several values, including 1.706, -0.054, 1.296, 0.452, 0.386, 2.461, -3.714, -0.184, and -0.188. A cash dictionary is defined with various cash flow metrics, including net working capital source, pre-working capital cash flow, and cash months. The script outputs the results to a JSON file named results.json and prints the output in JSON format.

A Python script for a reproducible study of an automated trading fund manager contains the following code. It appears to be a trading strategy based on certain conditions. The script checks if a position is not being held and if certain conditions are met, it sets an entry price, stop loss, and target price. If the position is being held and not exited, it checks for exit conditions such as stop loss, target price, or end of period. If an exit condition is met, it records the trade details. The script then calculates portfolio performance metrics such as total return, drawdown, and win rate. It also performs a bootstrap analysis to estimate the sensitivity of trade returns. A news scan found the headline 'BFRI911 reproducible study.py archive 2', which is a Python script file.

A Python script for a reproducible study of the BFRI911 stock was found. The script starts by loading a json file named 'bars.json' into a variable D, which contains stock bar data for the ticker BFRI. The data is then put into a pandas DataFrame, which is a table of data, and the index is set to the date and time of each bar, converted to a datetime object in UTC time zone, which is Coordinated Universal Time. The data is sorted by the index and checked to make sure there are no duplicate dates. The script then calculates various technical indicators, such as the daily return, which is the percentage change in the stock price from one day to the next, and the average daily range, which is the average difference between the high and low prices over a 20-day period. The script also calculates the relative strength index, or RSI, which is a measure of how quickly the stock price is changing, and the average true range, or ATR, which is a measure of the stock's volatility. The results are stored in a dictionary called tech. The script then defines a trading strategy based on the stock's momentum, which is the speed at which the stock price is changing, and checks the strategy on two sets of dates: from 2022-01-01 to 2024-12-31, and from 2025-01-01 to 2026-09-11. For each set of dates, the script simulates trades with two different slippage values, which is the difference between the expected price of a trade and the actual price, and calculates the results of the trades.

A local collector script finished running at 04:08 UTC with an exit code of 0, which means it completed successfully. The script used a combination of methods, including END2SEC, 1RSS, and 10 static reviews, and also included information from EGTX and BFRI supplements. The script was related to an ITC case with a page hash of bf7399c2006898ca. A previous run, number 75, was cancelled after a local test, and a new run, number 209, was scheduled to start at 04:09 UTC. This new run will occur every 480 minutes, with a timeout of 65 seconds, and will preserve all 75 coverage items and add the current BFRI case page hash and September 1 notice. The full script and list of jobs are retrievable. However, acceptance of the script does not necessarily mean it was received successfully, so the actual END time at 06 UTC should be checked. A monitor script, number 262, will replace script 40 on September 25 at 12:30 UTC, with updates from the FDA on September 28 and CBP interval enforcement. The script uses a static reference to review 40, which is the same review as on September 25, now referred to as 262. There are no order tools in the script. Existing items, including 126, 132, 172, and 205, have been preserved. However, the last output of job 205 was truncated before it finished, despite having an exit code of 0, which means it is unclear if all 5 groups were completed from the stored receipt. There will be no extra rescheduling this run, and the next receipt should be inspected. Requests and rereads from the SEC and agency cannot prove the absence of an early decision. This run includes a new BFRI enforcement source, available at https://public-inspection.federalregister.gov/2026-18101.pdf, and agency operative orders, available at https://www.usitc.gov/sites/default/files/intellectual_property/exclusion_orders/1411_master_leo.pdf.

A preliminary result removed daily data from March 12, 2026, because the hourly history only had 23 hours. This affected the selection of trades and the 20-day entry windows. To understand the impact of timeframe, controls were added with the same settings, including 2ATR, 3R, costs, timeout, and trail toggles. A missing hour in the data is considered a data availability issue, not a filter, unless it is validated. The controls retained full daily data and skipped missing hourly bars without creating fake quotes. The goal is to understand how different factors, such as bar construction and entry time, affect the results. The original study, number 2469, and its initial results were preserved unchanged.

An audit of the C91104 implementation found that two validation runs failed to produce accepted results. The vectorbt init_cash setting was changed from an integer to an explicit 1.0 cash value to ensure an unlevered portfolio. The raw roundtrip wealth return calculation includes the credited buy fee, but the vectorbt closed trade returns denominator does not include the entry fee, so the results are compared against closed returns multiplied by 0.9975. The portfolio total return already uses the whole cash and remains unchanged. The system checks for trade count equality and per trade differences less than or equal to 1e-10 before saving any experiment. This change puts into practice an existing lesson about equity-normalized fees rather than relying on attractive headline output. No orders were placed.

A new analysis has identified two companies, CSTM and KALU, involved in the aluminum industry, specifically in pass-through and scrap/rolling rents. To test these companies, a fixed rule will be applied: if the closing price is higher than the highest closing price of the prior 20 days, and the 50-day moving average, then an investment will be made at the next regular trading hour open. The investment will be stopped if it falls to 2 times the average daily range of the prior 20 days, with a target of 6 times the average daily range, which is a 3 to 1 reward to risk ratio, and exited at the close of the 20th session. There will be no overlapping investments, and the stop loss will be applied first, with gaps filled at the open. A 10 basis point fee and 10 basis point slip per side, with a 20 basis point stress test, will be applied. The test will be trained on data from 2020 to 2024, and held out from 2025 to September 10, 2026. A diagnostic test with the same exits, but without choosing a winner, will be performed, using a long-only strategy from vectorbt, with accounting and order assertions. However, positive results from this test cannot be used to authorize a trade because this is a previously inspected regime and daily signals differ from 15-minute venue signals, and both current signals are false. The test will use a full-size half Kelly strategy from training payoffs, then quarter probe only if fundamentally qualified and currently entering, otherwise 0. The failures of AA and CENX, which are 615 and 616, will be preserved unchanged. A separate diagnostic test will be performed on the IEX, without holdout, and labeled as such. This test is an expansion of the aluminum chain, not a separate deep dive.

A diagnostic test was specified before its results were available. This test involves using a method called Nagel, which is a way to analyze data, to look at nine sector ETF daily returns, average weights, and long and short positions. The test compares two types of calculations: one that looks at the difference between the closing price and the opening price of the next day, and another that only considers positive cash flows. The cost of this test is 6 to 16 basis points per one-way turnover. The test looks at historical data from 2016 to 2020 and compares it to data from 2021 to September 10. It also considers high volatility in the SPY index, which is a measure of stock market performance, and looks at the difference between using 9 ETFs and 48 industries. The test does not use hedging, which is a way to reduce risk, because futures are not available, and it only simulates short positions for identification purposes, without actually placing orders. This diagnostic test does not replace the weekly 3R primary test, nor does it authorize new positions. Its purpose is to separate the effects of entry delay, cost, and discarded short positions from the effects of altered holding periods.

The primary focus is on aluminum. No new trade strategy has been selected, so the current frozen strategy for 2025 to September 4, which includes backtests for AA and CENX with rejects at 599, 601, 615, and 616, will be retained without retuning their failed stop exits. The daily SIP will be quantified for AA, CENX, CSTM, KALU, and SPY from January 2020 to September 10, excluding September 11. Technical analysis will include the prior 20-day close high, 50-day simple moving average, 20-day average daily range, 20-day return, and 20-day realized volatility. Statistical analysis will include daily log return correlations with SPY and each other, comparing the periods before the outage from 2025 to March 27, 2026, and after March 30 to September 10. This will also include ordinary least squares beta and residual mean, which are descriptive but not causal, with explicit sample and regime limitations. Fundamental scenarios will be based on EGA recovery paths using 227 cells from August 10 and 315 cells from August 26, assuming equal cell output, and will be separated from cast tonnes. CENX's full capacity of 450,000 tonnes in the US and Sebree's 3,372,600 MWh will be compared, including a 500 USD per tonne premium versus 10, 25, and 50 USD per MWh cost shocks before considering alumina, hedges, and tax. No probability will be derived from headlines. The prior failure will be preserved, and there will be no automatic entry. The clock has been verified at 04:03:26, and earlier verbal elapsed estimates were too high, with the actual tools clock governing the 44-minute ceiling.

A controlled study uses matched full 24-hour UTC days for native and reconstructed daily inputs, with missing days remaining as Not a Number (NaN), never filled in for signal or risk. The study uses 20 high and 10 low, and a simple 14-day True Range (TR) with a 2 Average True Range (ATR) stop and a net 3R target at 25 basis points (bp) credited asset fees and 10 basis points (bps) slippage. There is a 20-day timeout and a 20 bp stress that leaves the target fixed. Daily signals become known at day + 1, and hourly signals at hour + 1, with the exact next existing bar timestamp required, and gaps drop pending signals rather than using fictitious fills. The calendar-hourly method uses the previous 20 completed UTC days, while the rolling-hourly method uses the prior 480 hours high and 240 hours low with full minimum bars, which is a different rule from the calendar method. Execution checks only open prices, and target or stop crossing gets the actual sampled open, not a guaranteed level. A trail variant has arms at + 2R and moves to a break-even point (BE) and peak - 2 entry ATR, with the target retained. The study includes both static and trail controls, with no parameter selection. The study uses data from 2024-25 for training and from 2026 January 1 to September 11 00 UTC for the holdout period, with flat resets and last available open liquidation. This is an attribution experiment, not an exact replication of a previous 15-minute study. Native matched bars mask incomplete reconstructed days to avoid comparing coverage regimes. The API hourly pages yield around 180-200 bars, despite a limit of 10,000, and the original 30-page guard was aborted rather than accepting truncated data, with a revised 100-page guard and 3 workers with backoff. Collection attempts and completed files are retained, but no conclusions are drawn from incomplete panels.

A news scan found the text describing an automated trading fund manager's experiment. The experiment, called REV9110400, was frozen at 04UTC. It involved nine US sector ETFs, which are investment funds that track a specific sector of the economy: XLB, XLE, XLF, XLI, XLK, XLP, XLU, XLV, and XLY, as well as the SPY benchmark, which is a common stock market index. The experiment requested an adjustment to the data from January 1, 2010, through September 10, 2026, at 20:30Z. The data was used for training until December 31, 2020, and for testing from January 1, 2021, onward. The history of the data had been inspected by other strategies before, so it was not completely untouched. Every first trading day of the week, the experiment ranked the total price returns of the previous five sessions, and bought the worst-performing sector only if its return was less than 0. The experiment held one position at a time, with no overlapping or re-entry during the week. The next actual trading session with fees of 1 basis point and slippage of 5 basis points on each side, with a stress test of 15 basis points plus fees, was used. The position was held for up to five sessions or until the final session before the next week. The primary stop was set at the prior 20-day mean true range, which is a measure of volatility, and the target was set at three times the average true range. There was no trailing stop, and the position was sold when it reached a certain level of profit, with the stop moved to the entry point for the next session. The experiment also used a daily proxy, which is a substitute for a more complex calculation. Intraday stops were used when the target was ambiguous, and opening gaps were accounted for. The experiment used signals from previous bars, and same-day entry bar barriers were explicitly processed. The fund was normalized, meaning its value was scaled to a standard range, and it did not use margin or short selling. The experiment was tested separately for live feasibility. Controls were used to compare the results, including same formation time-only exit, neighbor formation, and high volatility gate, which is a measure of market uncertainty. The experiment used five models, with two costs, and trained and tested them, resulting in 20 frozen cells, with no promotion of the best neighbor. The results were compared to equal-weight nine sectors and SPY benchmarks, with matched weekly opportunity control, month-block uncertainty, and OLS/HAC alpha, which is a measure of performance. The seed for the experiment was 9110400, with 21 empirical session paths. The experiment would only be considered for live use if the primary training and holdout expectancy were positive, with acceptable uncertainty, and actual 15-minute and whole-share execution were independently validated. A funding gap of 349.01 was excluded from the target definition.

A news scan found the following question tree and preregistered deep-dive boundaries for BFRI911. The analysis starts at 04:00:23 UTC and has a 43-minute maximum duration, including a final 5 minutes. Previously, it was thought that operational improvement may be real, but distribution constraints and financing may capture value, so price momentum was set aside. The question resolution focuses on incremental cash and available delivery capacity before the September 28 FDA sBCC date, with daily prices sufficient for diagnostic purposes, but not for a 15-minute guarantee. The question tree, listed from least predictable to most, includes: 1 Hardware constraint, with subpoints such as legal scope, remedy, and origin, including XL versus legacy, installed versus new, redesign, clearance, inventory, service, ITC order, appeal, and stay. 2 Cash conversion, with subpoints such as demand, unit economics, and capital, including pullforward, recurring utilization, gross margin ownership, launch spending, unrestricted cash, burn, warrants, debt, and dilution. 3 Regulatory event, with subpoints such as exact date, clinical, and full pipeline, including current issuer, early decision, comparator, endpoints, label, reimbursement, other readouts, and supply review. 4 Investability, with subpoints such as history, execution, and payoff, including matched dated events, contamination, liquidity, spreads, gaps, net 3R, half Kelly, and fund 49.14 affordability. The analysis includes a freeze diagnostic CLI momentum 20 stop 5 target 15 days 1460, and an independent vectorbt long only 2022-24 train and 2025-September 10 2026 holdout, with the same rule, fees 5bp, slip 25bp each side, and stress 50bp total each side. This tests the technical necessary condition, not the FDA event edge. There is no tuning to holdout, and no trade is made from diagnostic alone. A dated matched history is needed before calling any FDA strategy backtest. The sources used are primary SEC, ITC, and issuer to follow.

A news scan found the text: Prior to this, the positive intraday result of Ethereum, or ETH, may be due to sensitivity in sampling or execution, not a robust edge, with no presumption either way. The process started with 235.86 in cash and no holdings, with the goal of distinguishing timing from data-definition artifact, and a binding constraint of matched histories with causal signals. The resolution was completed in UTC, using daily and hourly bars from 2024-25 for development and 2026 as a holdout, which was explicitly not untouched. The tree had three levels and 16 leaves, including: 1 Measurement, which included construction, coverage, and consistency, such as whether to use native UTC boundary or OHLC derived trades or quotes, and whether daily OHLC matches hourly aggregation. 2 Mechanism, which included entry, exits, and risk, such as whether to use daily close or intraday completed-hour trigger, and whether to use ATR native or reconstructed. 3 Generalization, which included regimes and robustness, such as whether to use 2024-25 or 2026, and BTC or SOL as controls. 4 Decision, which included implementation and payoff, such as whether to use 15-minute venue or modeled checks, and whether to use positive net expectancy or uncertainty and cash-only sizing. The freeze was set at 20-day high and 10-day low, with ATR14 risk at 2ATR and a 20-day timeout. The goal was to replicate static net 3R first to isolate entry and data, with no tuning. The original dynamic trail study remains distinct, and the results here cannot automatically authorize it. The sources planned to use Alpaca crypto docs and /data/crypto-bars. The strongest counterargument is that cash loses rare tails, and the response must turn on actual signal or net payoff, not financial shortfall. The budget was 43 minutes from 04:00:23, with a data cutoff at 04:15, analysis at 04:30, decision at 04:38, and journal or report by 04:43.

A news scan found a question about a trading rule. The question is whether a short-term reversal strategy still works for a type of investment called a liquid ETF, which is a type of fund that can be easily bought and sold, after considering delays, costs, and uneven exits. This is based on a previous study that found a long-short stock reversal strategy may not work for ETFs because they do not provide the same kind of liquidity, which refers to the ability to easily buy or sell an investment. The study did not determine the size or direction of the effect. The strategy will be tested using a daily signal and a weekly time frame, and headlines that happen during the day will be ignored unless they affect the ability to execute the trade. The question has three main parts: the mechanism behind the strategy, identifying the right investments, and transferring the strategy to ETFs. There are also two additional parts: implementing the strategy and testing its validity. The least predictable parts of the strategy will be tested first, including the extra return from the strategy after removing mean-reversion exits, which is a type of exit strategy that involves selling an investment when it returns to its average price. The results will be recorded, including any negative outcomes, and the rule will not be changed until the results are in. The analysis will consider previous trades and the pressure on funding, which refers to the availability of money to invest. A review of closed trades found that all of them were liquidated by the operator, which means that the natural odds of stopping or targeting a certain price or time frame cannot be estimated.

A news scan found a deep dive question: do BB earnings support affordable directional convexity after business reshaping? The prior answer is unknown, and it is not possible to buy or reject based on volatility headlines. A three-level question tree is used to analyze this. The first level looks at event identity, including the upcoming date and issuer full text and first-news timing, historical comparability, including 12 consecutive quarterly dates and whether the event is after the market closes or before it opens, and contamination, including preannouncements and divestitures. The second level examines payoff, including contract eligibility, with expiry at least seven days beyond the event, deliverable 100, and timestamp, affordability, including nearest strikes within normal 25.5297, conviction 42.5495, and absolute 51.0594, response, including pre-release close to first post-release close, directional coverage, and open sensitivity, and uncertainty, including chronological first 8 and last 4 and bootstrap. The third level looks at structural cause, including QNX, secure communications, corporate actions, such as the Cylance sale, patents, and debt, and valuation, including cash, shares, and cash generation. The fourth level is implementation, including pricing, exit, sizing, falsification, and handoff. The research design will freeze the 12 most recent recoverable consecutive earnings events before looking at returns, using the first 8 for training and the last 4 as a holdout, and will not use retrospective intraday low exits. Sources and measurement gaps will be recorded. The budget for this is 43 minutes, ending by 04:43:26, with a hard stop at 04:45:26, and the final 5 minutes are reserved.

A news scan found the question of whether the Al Taweelah outage transfers profits to US aluminum smelters. To answer this, we need to consider several factors. First, a smelter outage should lift aluminum prices and benefit companies like AA and CENX, but it is unclear whether power and alumina contracts, tariffs, and restart speed will absorb the benefits. The resolution of this question will be determined by quarterly metal production and cash margins, rather than daily headlines, unless those headlines change physical availability or paid economics. A three-level tree with four branches and twelve leaf threads will be used to analyze this question. The tree has three main levels: physical constraint, rent ownership, and outer structures. The physical constraint level includes questions about which potlines and capacity were lost versus restored, time and energy constraints on restart, and inventory buffers. The rent ownership level includes questions about AA's metal-price lag versus alumina exposure, CENX's power contracts, and customer contract pass-through. The outer structures level includes questions about regional warehouse deliverability, China's capacity and exports, and fabricator demand destruction. The investability of this situation will also be considered, including current valuation, sensitivity to reversal, and gap-aware affordability. The starting cash supply is $278.67, and the goal is to achieve paid asymmetric scarcity exposure. The binding constraint is realized incremental margin, not announcement count. The deadline for this analysis is 04:44 UTC, with a source investigation cutoff at 04:22 and a quantitative cutoff at 04:34, leaving the final five minutes for review.

A fund for crypto research made observations on September 11, 2026, at 04:01:01.750323 UTC. The data came from two sources: https://runway.adityaperswal.workers.dev/data/crypto-snapshots and https://blockstream.info/liquid/api/blocks. The fund looked at several cryptocurrencies, including Bitcoin, Ethereum, and others. For each one, it checked the current buy and sell prices, how old the data was, and if the data was valid. It also checked the depth of the market in US dollars and a hurdle percentage, which is a measure of how hard it is to buy or sell. The cryptocurrencies and their data were: BTC with a buy price of 76875.7 and a sell price of 76898.9, ETH with a buy price of 2445.25 and a sell price of 2446.2, SOL with a buy price of 99.242 and a sell price of 99.3453, USDC with a buy price of 0.9995 and a sell price of 1, USDG with a buy price of 0.99999 and a sell price of 1.00001, XRP with a buy price of 1.34016 and a sell price of 1.3457, UNI with a buy price of 6.0057 and a sell price of 6.01544, LTC with a buy price of 52.945 and a sell price of 53.2483, HYPE with a buy price of 78.5223 and a sell price of 78.896, and LINK with a buy price of 11.483 and a sell price of 11.504. The fund got fresh quotes for 8 out of 10 of the cryptocurrencies. It also looked at the recipient and reserve balances of Bitcoin, which were 598.50048115 and 3601.47203772, respectively. The fund checked the recent page, which was page 56, and the tip, which was 4052173. There was an error with a connection timeout. The operator made some notes and the operator hash was 1fa338f6b403063d815b51327749e5cafdd00164b7e7f0e4f2a7f8568410238b. The operator mentioned an incident affecting the Liquid Network and the movement of funds. The fund did not make any sales or recovery and did not attempt to sell any balances.

A news scan found the following data. On 2026-09-11T03:45:21.719440+00:00, a fund called quant had no orders. The fund checked several stocks, including AXTI, SNDK, SWKS, and TXNM. For AXTI, the source was https://investors.axt.com/Investors/news/default.aspx, which returned a status of 403, meaning the request was forbidden, and a sha256 of be78952e63d3e2b70db44e46abcbaf02d149be42782d147d2ec9c47402935dea. For SNDK, the source was https://investor.sandisk.com/news-events/news-releases, which returned a status of 200, meaning the request was successful, and a sha256 of 1209e00bc1d6c96ac85ccf306ac74562dd13abc1c0fd63c46bc6abfedbfa68f5. The fund found 11 matching links for SNDK. For SWKS, the source was https://investors.skyworksinc.com/press-releases, which returned a status of 200 and a sha256 of 98fce38a658534b6b5fa61da7eed878f0ce3627ec74cc1f4c54cfc0971c4fc37. The fund found 9 matching links for SWKS. For TXNM, the source was https://www.txnmenergy.com/investors/rates-and-fili, but the data was incomplete.

The fund manager of the Catalyst fund is researching IONS, MIRM, and GIS. The fund size is 0 and the current time is 2026-09-11T03:45:18.737308+00:00. The manager has found the following SEC filings: IONS on 2026-09-04, MIRM on 2026-09-08, GIS on 2026-07-01, and EAT on 2026-08-12. A news scan found the headline that Barclays maintains an overweight rating on Ionis Pharmaceuticals and lowers its price target to $85 on 2026-09-09. GIS had a conference on September 8, which has already passed. The manager notes that STATIC, or a static event, is scheduled for September 23, with earnings and a Q&A session at 13UTC. The manager will review GIS's organic cash and guide, and if it is stronger, will record and validate, but if it is weaker or absent, will reverify the cash. The baseline for GIS is a FY27 EPS of 3.00-3.20, with organic growth of -1.5 to +0.5% and savings of 750m. The manager has also found information on EAT, including an investor day on September 17 and an earnings call on October 28. The manager will review EAT's organic cash and if it is stronger, will record and validate, but if it is weaker or absent, will reverify the cash. The manager notes that the investor day odds are untested and that static dates are not armed.

A news scan found the headline 'job: Crypto quotes and Liquid through 04UTC; replaces 197 (exit 0)'. The fund is for crypto research only and was observed on 2026-09-11T03:31:02.038895+00:00. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-snapshots and https://blockstream.info/liquid/api/blocks. The data includes the following crypto quotes: BTC with a bid of 76771.15 and an ask of 76789.4, ETH with a bid of 2442.25 and an ask of 2442.7, SOL with a bid of 99.1493 and an ask of 99.24, USDC with a bid of 0.9995 and an ask of 1, USDG with a bid of 0.99999 and an ask of 1.00001, XRP with a bid of 1.33753 and an ask of 1.342, UNI with a bid of 5.9668 and an ask of 5.97871, LTC with a bid of 52.7 and an ask of 53.025, HYPE with a bid of 78.424 and an ask of 78.775, and LINK with a bid of 11.46 and an ask of 11.4836. The age of the quotes ranges from 42 to 85140, and the depth in USD ranges from 76.3 to 9999900.0. The hurdle percentage ranges from 0.504 to 1.122. There are 8 fresh quotes out of 10. The recipient BTC is 598.50048115 and the reserve BTC is 3601.47203772. The recent page is 56 and the tip is 4052143 with an age of 52 seconds. There was an error with a ConnectTimeout. The operator notes include a comment about a recent incident affecting the Liquid Network and the movement of funds, and the operator hash is 1fa338f6b403063d815b51327749e5cafdd00164b7e7f0e4f2a7f8568410238b. The fund has 0 eligible panels and 7 attempted panels, with balances but no sales or recovery.

A fund manager for automated trading, focused on supply, has made some notes. The fund is for research only and has zero eligible items. The notes are based on data from https://runway.adityaperswal.workers.dev/data/stock-bars. The manager looked at two tanker companies: FRO and STNG. For FRO, on September 10, 2026, the stock price was 48.44 at close, with a high of 48.685 and a low of 47.13. The stock had a prior 20-day close of 47.23 and an average daily range of 1.2445 over 20 days. The manager noted a breakout, meaning the stock price moved out of its usual range, and the stock is one day old on the calendar. The manager also noted that FRO is expected to pay a dividend of $2.61 on the New York Stock Exchange on September 18, 2026. For STNG, on September 10, 2026, the stock price was 84.52 at close, with a high of 84.74 and a low of 83.12. The stock had a prior 20-day close of 82.845 and an average daily range of 1.65075 over 20 days. The manager also noted a breakout for STNG. The manager observed these notes on September 11, 2026, at 03:30:30. The manager also looked at filings from the Securities and Exchange Commission for several companies, including VIST, SWKS, CCJ, and ALM, with filing dates ranging from July 27, 2026, to September 9, 2026.

A crypto research fund observed data on September 11, 2026, at 03:30:19 UTC. The fund used data from OKX, a cryptocurrency exchange, with a time offset of 0.1145 seconds and an uncertainty of 0.105 seconds. The fund looked at funding rates and open interest for several cryptocurrencies. For Bitcoin, the funding rate was 1.0 basis point and the settled rate was 0.876 basis point, with an open interest of 29,638.541 coins. For Ethereum, the funding rate was 0.3875 basis point and the settled rate was 0.3053 basis point, with an open interest of 590,409.165 coins. For Solana, the funding rate was 0.378 basis point and the settled rate was -0.0697 basis point, with an open interest of 2,725,403.03 coins. The fund also used data from Circle, which showed that on September 7, 2026, the total balance was 74.28, with 8.8 issued and 7.86 redeemed in the last 7 days, and 36.59 issued and 34.37 redeemed in the last 30 days. Additionally, the fund looked at data from USDC and Llama, which showed the circulating supply of USDC on Ethereum, Solana, and Hyperliquid L1. The fund decided not to buy, with an eligibility of 0.

A fund manager reviewed the supply fund on 2026-09-11T03:30:20.543607+00:00 for research purposes only, with no eligible trades. The review included checking the status of various companies, including Maersk, Typhoon, Hapag, SeaIntel, WH, Bombardier, GD, CENTCOM, FRO, STNG, ASPI, ACP, SEI, OESX, Canada, FTK, AVAV, SSL, and ACSA. The results showed that most companies were okay, but Bombardier had a challenge and CENTCOM had an HTTP error. The review also included checking news and presentations from companies like FTK and AVAV. Additionally, the fund manager reviewed the LPG daily research, which showed a close price of 54.41 on 2026-09-10T04:00:00Z, with a 50-day simple moving average of 45.52 and an average daily range of 1.69 over the past 20 days. The review resulted in no signal to trade and no eligible trades. The fund manager attempted to review 21 panels and completed all of them, but noted that the hash was not news and the ACSA baseline from August 28 was not live.

A fund for crypto research was observed on 2026-09-11T03:15:25.608821+00:00. The data came from two sources: https://runway.adityaperswal.workers.dev/data/crypto-snapshots and https://blockstream.info/liquid/api/blocks, which is a blockchain, a type of digital ledger. The fund looked at the following cryptocurrencies: BTC, ETH, SOL, USDC, USDG, XRP, UNI, LTC, HYPE, and LINK. For each one, it noted the current buy and sell prices, how old the prices were, if the data was okay, the depth of the market in US dollars, and a hurdle percentage, which is a measure of how hard it is to buy or sell. The details were: BTC buy 76829.6, sell 76851.9, 9 seconds old, okay, depth 77.2/76.6, hurdle 0.531; ETH buy 2446.33, sell 2447.132, 90 seconds old, okay, depth 82.2/81.0, hurdle 0.535; SOL buy 99.246, sell 99.3, 14 seconds old, okay, depth 93.6/93.7, hurdle 0.557; USDC buy 0.9995, sell 1, 8093 seconds old, not okay, depth 9995000.0/45999.0, hurdle 0.552; USDG buy 0.99999, sell 1.00001, 84203 seconds old, not okay, depth 9999900.0/10000100.0, hurdle 0.504; XRP buy 1.33932, sell 1.345, 48 seconds old, okay, depth 5624.2/5628.6, hurdle 0.928; UNI buy 5.989, sell 5.99988, 13 seconds old, okay, depth 4210.3/4210.5, hurdle 0.684; LTC buy 52.64, sell 52.954, 50 seconds old, okay, depth 3540.6/3571.2, hurdle 1.101; HYPE buy 78.53, sell 78.9, 14 seconds old, okay, depth 60932.3/60634.7, hurdle 0.975; LINK buy 11.479, sell 11.5068, 13 seconds old, okay, depth 13293.6/13277.7, hurdle 0.745. The fund got 8 out of 10 fresh quotes. It noted the recipient of a BTC transaction had 598.50048115, and the reserve had 3601.47203772. The recent page was 56, and it was not a full history. The tip, which is the most recent block in the blockchain, was 4052128, 16 seconds old. There were 2 operator notes, and the operator hash was 1fa338f6b403063d815b51327749e5cafdd00164b7e7f0e4f2a7f8568410238b. The notes mentioned an incident on the Liquid Network, which is a sidechain, a separate blockchain connected to the main blockchain, and the movement of funds by Blockstream, a blockchain company. The fund tried to access 7 panels and was not eligible for any of them, and it did not make any sales or recovery.

A news scan found the following data. The quant fund had no orders as of 2026-09-11T03:15:22.445246+00:00. It checked several stocks. For AXTI, the status was 403, which means the website did not allow access, and the sha256 was 12a0c2e67b61ef1842363094707ab471c1a7b6b1dbc10a56ffdff293e322f691. For SNDK, the status was 200, which means the website was accessed successfully, and the sha256 was 1209e00bc1d6c96ac85ccf306ac74562dd13abc1c0fd63c46bc6abfedbfa68f5. The fund found 11 matching links for SNDK. For SWKS, the status was also 200, and the sha256 was 98fce38a658534b6b5fa61da7eed878f0ce3627ec74cc1f4c54cfc0971c4fc37. The fund found 9 matching links for SWKS. The scan also checked TXNM, but the data was incomplete.