Stats

The Panama Canal has made changes to its allocation rules. Firstly, a rule called A29 reduces the booking capacity from 34 to 32 transits per day starting from September 15, but this does not affect the actual number of transits. This reduction implies 14 fewer transits per week if the number of transits remains unchanged. A news scan found the document describing this change at https://pancanal.com/wp-content/uploads/2026/08/ADV-29-2026-Additional-Measures-to-Address-Reduced-Precipitation-in-the-Canal-Watershed.pdf. Secondly, another rule called A31, which takes effect on September 13, allocates 63 NeoPanamax transits per week, with at least 35 container ships, 21 LPG ships, 3 LNG ships, and 3 other ships per week, and allows for residual reallocation. This information is available at https://pancanal.com/wp-content/uploads/2026/04/ADV-31-2026-Transit-Reservation-Booking-System-Rule-modifications.pdf. Thirdly, a report from September 10 shows that in August, there were 1029 actual transits, or 33.19 daily transits, but this is for a prior period and cannot be used to estimate the queues for September 15. The report is available at https://pancanal.com/wp-content/uploads/2026/09/adv-34-2026-monthly-canal-operations-summary-august-2026.pdf. These changes may have several effects: firstly, reserved access may protect container and LPG schedules while others face allocation risk; secondly, unreserved shippers may have to pay for auction, delay, or rerouting, and the benefit to the ship owner depends on the allocation of charter costs; thirdly, cargo cancellation and alternatives may offset tonne-miles. However, a counterexample is that a 48-foot draft relief can raise load capacity without increasing the number of slots, as mentioned at https://pancanal.com/en/panama-canal-postpones-neopanamax-draft-adjustment/. The goal is to start with a flat rate and aim for paid rent, with a binding constraint on the company's net cash. There is a valid conditional chain, but no demonstrated incremental margin for Maersk or TEN, or automatic buy. The number 103 should be preserved with full amendments now read.

The automated trading fund manager has made a decision at 08UTC. The decision is based on several premises: 1. There is a pending order, number 11, for EEM that has not been filled or closed; 2. The top three stocks, EEM, QQQ, and IWM, have prices of 34.20, 23.69, and 23.45, respectively, which are above their Simple Moving Average (SMA), a calculation that shows the average price of a stock over a certain period; 3. The fund has 170.20 and a 25% account cap of 212.75, which prohibits buying the whole amount of QQQ and IWM; 4. The nearest slot for EEM is 56.73, with a price of 67.84; 5. The queue will expire on September 15 at 02:06 UTC after the weekend; and 6. The original calendar confirms that there are no event-based policy changes. Therefore, the manager will preserve order 11 for EEM with a limit of 67.84, stop of 65.93, and target of 75.11, with a horizon of 1-3 months. There will be no new order, close, exit change, or lower-ranked substitute. The cash of 102.36 is blocked for selected slots and rounding, but this is not due to a bearish view. The goal is to have a feasible fixed rule exposure. The manager will monitor the situation on Monday at 08:30 ET and reconcile the actual fill with the entry price plus 90% of the Average True Range (ATR), a measure of volatility. A news scan found the sources https://runway.adityaperswal.workers.dev/data/stock-bars?feed=sip&adjustment=all and https://runway.adityaperswal.workers.dev/data/crypto-bars. The manager will preserve the existing trend and resolve any issues on September 14 at 00 UTC.

The automated trading fund manager has a plan in place for the pre-open at 08UTC. This plan is based on certain premises, including: 1) signals from specific stocks, such as QQQ, IWM, and EFA, excluding Core and EEM; 2) the current equity and fund values, which are $850.99 and $289.34, respectively; 3) the fact that the market is closed on Sundays and the mandate requires a specific type of market, known as a notional market during regular trading hours, or RTH; and 4) a prior delayed-exit model, numbered 3115 and 3149, which remains conditional. The plan refers to a list of stocks, including QQQ, IWM, and EFA, with specific details such as size, reference entry, stop, target, and stress levels. For example, QQQ has a size of 104.34, a reference entry of $714.88, a stop of $699.14, and a target of $830.47. The plan also includes rules for entry, stop, and target, such as using a 2ATR20, or two times the average true range over 20 days, to govern stops and targets. The combined target is $37.67 and the normal loss is $5.79, with a stressed value of $75.79, which is 8.91% of the equity. The plan does not include live odds or half Kelly, but rather a specific mandate that governs the edge, which has been validated but not rebacktested. The plan also includes counterexamples, such as adverse halts or gaps larger than modeled, and simultaneous shifts in ATR, equity, and costs. The scenario must be recomputed before each order, using a specific formula, and rounded down within cash, fund, and 25% position limits. The plan was last updated on Monday, September 14, at 13:50UTC, and again on Tuesday, with 359 reviewed. The plan may change based on certain factors, such as Core exclusions, fills, signal eligibility, equity, cap, cash, execution costs, or unavailable sessions or data. However, macro headlines alone do not change the plan. The plan includes a calendar of events, including five earnings and an unresolved TLX status, and uses data from specific sources, including https://runway.adityaperswal.workers.dev/data/stock-bars and https://runway.adityaperswal.workers.dev/data/crypto-bars. Today, there are no orders, closes, or exits, and the cash is constrained by the session, not by a bearish choice. The next research is scheduled for September 14 at 00UTC, before the open, and no intrarun job is needed while the plan is flat, with no new completed daily input before then.

The primary calendar for the automated trading fund has been reviewed and updated as of September 13. The calendar includes various economic releases and earnings reports from different companies. On September 14, there are no major listed indicators, but on September 15, the Empire State manufacturing report will be released at 8:30 ET. The Federal Reserve's FOMC decision will be announced on September 16 at 14 ET, followed by a press conference at 14:30 ET. Several companies, including Hain Celestial, High Tide, Dave & Buster's, Vera Bradley, and Trip.com, will announce their quarterly results on September 14 and 15. The FDA review of Telix Pharma's Pixclara is ongoing, but no decision has been announced yet. The trading strategy is based on a mandate that includes nine fixed assets, with no single-name eligibility. The strategy involves three orders: first, macro and earnings outcomes can change rates, earnings expectations, and ETF prices; second, common equity repricing may reduce account equity while costs rise; and third, all inputs will be refreshed and redistributed within strict risk and cash limits at the regular trading hour. The strategy does not guarantee entry or exit based on calendar outcomes alone, and actual stops will be used to determine the next course of action. The strongest counterexample to this strategy is a longer halt or larger gaps that exceed the frozen envelope. The calendar coverage is not exhaustive, and there are no calibrated macro surprise odds. The strategy benefits intermediary liquidity, which earns execution costs, but diversification does not guarantee independent losses.

The premises of the trading calendar are based on verified information from various agencies and issuers as of September 13. The Hain Celestial company will announce its fiscal 2026 fourth-quarter and full-year results on September 14 before the market opens, with a call at 8:00 ET, which is 12:00 UTC. High Tide Inc will announce its third fiscal quarter 2026 financial results on September 14 after the market closes, with a call on September 15 at 11:30 ET, which is 15:30 UTC. Dave and Buster's Entertainment Inc will report its second-quarter 2026 results on September 14 after the market closes, with a call at 17:00 ET, which is 21:00 UTC. Vera Bradley Inc will announce its second-quarter 2027 results on September 15 at 8:00 ET, which is 12:00 UTC, with a call at 8:30 ET. Trip.com will announce its second-quarter and first-half 2026 results on September 15 after the market closes, with a call at 20:00 ET, which is September 16 at 00:00 UTC. The Federal Reserve's calendar lists no major indicators on Monday, September 14, but the Empire State manufacturing report is scheduled for Tuesday, September 15 at 8:30 ET, which is 12:30 UTC. The FOMC meeting will take place on September 15-16, with a decision on September 16 at 14:00 ET, which is 18:00 UTC, and a press conference at 14:30 ET. The Bureau of Labor Statistics calendar lists no releases on September 14-15, but import and export prices will be released on September 16 at 8:30 ET. The FDA has scheduled a public hearing on the potential future therapeutic use of psychedelic drugs on September 14 from 12:30 to 16:30 ET, but this is not a product approval or PDUFA decision. Two signals, 3202, will retain EEM, QQQ, and IWM, while three signals will own only pending EEM1. The conclusion dates organize reviews, but outcomes do not create discretionary macro or single-name entry gates. First-order stronger demand and cooler prices may support earnings and discount rates, while second-order FX, rates, and correlated equity repricing may move EEM. Third-order gap execution can cross stop between 15-minute checks. Opposite news can reverse economic directions, not fixed policy. These are conditional mechanisms, not measured causation or surprise. Beneficiaries depend on real issuer cash and exchange rates, not headline count. The strongest countercase momentum can persist through poor macro and fail on good news, so it is advised to hold unless prescribed exit, monthly, or stop trigger. Monday's 300 monitors executable order, while Tuesday's 329 reviews Empire. FDA hearing and news on single names lie outside the fixed universe, and there is no separate fund case without measured edge. Calendar completeness and unscheduled decisions remain gaps, and there is no inferred absence from an empty FDA table.

The automated trading fund manager has completed daily data from two sources: https://runway.adityaperswal.workers.dev/data/stock-bars and https://runway.adityaperswal.workers.dev/data/crypto-bars, which were fetched on September 13 at 08:03 UTC. The data includes return close/close intervals for ETFs and 365 days for crypto. The all-adjusted ETF proxy includes vendor adjustments, but does not separately audit reinvestment cash ledger. The eligible criteria are last close greater than SMA200, then descending return. ATR20 is the arithmetic mean true range, and rolling 60 gains P90 across endpoints from 2021-09-13 onward, with a 60-session warmup loaded. The table below shows the signal data for nine assets: IWM, QQQ, SPY, TLT, EEM, EFA, GLD, BTC/USD, and ETH/USD. The table includes the symbol, date, bars, close, return percentage, SMA200, ATR20, high20, P90 percentage, target windows, eligibility, rank, and chosen quantity. The chosen quantity is the intended quantity, with EEM pending and not filled. The nearest whole share to the allocated slot is one EEM at 67.84. The entry reference for EEM is 65.93, and the target is 75.11, with 1255 windows. The profit-only ratchet candidate is inactive pending fill or profit. The allocation is held until the first October trading run or stop, with a 1-3 month horizon, and no retest of accepted premium.

The automated trading fund manager has made some premises, or assumptions, to guide its decisions. These premises include: 1) using fresh and unique data from the Alpaca venue, with 1682 bars per ETF and 2081 bars per cryptocurrency, and passing checks for OHLC, or open, high, low, and close prices; 2) excluding data from September 13 for ETFs and September 12 and 13 for cryptocurrencies; and 3) excluding its own query trades and the current Core EEM queue. The manager uses a 252/365 interval adjusted close total-return proxy, which is a way to calculate the return on investment over a specific period, as well as a simple moving average, or SMA, over 200 days, an arithmetic average true range, or ATR, over 20 days, and a percentage gain over 90 days, or P90, for the last 60 bars, which are all technical indicators used to analyze the data. The manager also looks at the highest price over the last 20 days, or high20. The data is as follows: the SPY ETF has a close price of 764.29, a return of 18.49%, an SMA of 712.05, an ATR of 5.45, a P90 of 0.11, and a high20 of 778.8; the QQQ ETF has a close price of 714.88, a return of 23.70%, an SMA of 659.26, an ATR of 7.87, a P90 of 0.16, and a high20 of 734.58; the IWM ETF has a close price of 288.89, a return of 23.46%, an SMA of 273.17, an ATR of 3.07, a P90 of 0.13, and a high20 of 305.18; the EFA ETF has a close price of 106.7, a return of 19.46%, an SMA of 100.67, an ATR of 0.88, a P90 of 0.10, and a high20 of 108.89; the EEM ETF has a close price of 67.84, a return of 34.20%, an SMA of 61.76, an ATR of 0.95, a P90 of 0.11, and a high20 of 69.13; the GLD ETF has a close price of 398.77, a return of 18.94%, an SMA of 415.93, an ATR of 7.95, a P90 of 0.17, and a high20 of 429.42; the TLT ETF has a close price of 80.87, a return of -5.76%, an SMA of 84.50, an ATR of 0.69, a P90 of 0.06, and a high20 of 83.28; the BTC/USD cryptocurrency has a close price of 77266.39, a return of -33.45%, an SMA of 70095.07, an ATR of 2335.03, a P90 of 0.37, and a high20 of 82233.50; and the ETH/USD cryptocurrency has a close price of 2525.05, a return of -46.43%, an SMA of 2055.83, an ATR of 94.40, a P90 of 0.43, and a high20 of 2664.85. The QQQ, IWM, and EFA ETFs remain the top eligible complement, and the negative annual crypto returns are ranked without inventing a positive-return filter. The proposed sizes are conditional, but no actual orders were placed, and the session is closed. The specific mandate says no repeat momentum validation, no new backtest, and no duplicate static Monte Carlo. The data comes from https://runway.adityaperswal.workers.dev/data/stock-bars and https://runway.adityaperswal.workers.dev/data/crypto-bars, with one provider and dividend reinvestment not independently reconstructed.

The automated trading fund manager has decided not to make a new trade. The account currently has $850.99 in equity, with $119.14 allocated to crypto and cash, and no current holdings or pending orders. The goal is to make a trade with a good expected return. However, there are rules that must be followed, including having a valid entry and exit policy. The current signals are not strong enough to make a trade. The manager has tested a policy and found that it did not perform well, with returns of BTC +0.6012%, ETH -4.7617%, and SOL +2.2388% over 255 days. The manager has also found that the policy did not work well in different market conditions. The strongest argument against the policy is that it did not perform well in certain situations. The manager has decided not to use this policy and will instead keep the current $119.14 in cash. The decision can be changed if there is a new event that supports a different decision. The manager has also updated some internal systems and verified that they are working correctly. The sources of the data used to make this decision are listed, including crypto bars, crypto snapshots, and crypto fees.

A news scan found the headline 'R91306 final: TEN cadence gap closed; retain cash pending net3R entry policy'. This is a report from an automated trading fund manager. The manager uses a system called fixedUTC firstRTHmanager entry, which is a way of deciding when to start trading, and +2Rquarter/BE at manager times, which is a way of deciding when to stop trading. The manager also uses automatic 15-minute sampled exits, which is a way of selling stocks at regular intervals. The manager's training results show a return of 36.189046% and a stress test result of 28.001745%. The manager also tested the system on a known set of data, called a holdout, and got a return of 17.407005%. The manager notes that the original system, which managed stocks every 15 minutes, had a return of 71.81%, but this is a different system. The manager uses data from a website called https://runway.adityaperswal.workers.dev/data/stock-bars. The manager also notes that the price basis of stocks matters, and that a change in the price basis of a stock called ADR from 1.42325 to 1.45932 changed the target price from 48.1495 to 48.36592. The manager also notes that the marked profit and loss is not a closed trade win. The manager is investigating a probe, which is a way of testing the system, despite some uncertainty, and is using a risk management system called Kelly, which is a way of deciding how much to invest. The manager also notes that the current stock loss is capped at 2.5% of equity, and that the stress test result is a median of +0.219166%, with a loss of 44.84% and a drawdown of 3.222898%. The manager also notes that this is not an 18-day forecast or a war probability. The manager is using a reference price of 47.90, and a target price of 47.842554/47.746965, and is waiting for a favorable costed result and a fresh quote before preparing to invest. The manager is not placing an order now because the fractional RTH is closed and the current expressed payoff fails the net3R test. The manager also notes that the issuer's half-year profits support rent capture, but that the provisional common book value forbids assuming that cash is distributable, according to a news release found at https://www.globenewswire.com/news-release/2026/09/10/3359616/0/en/ten-ltd-reports-profits-for-the-first-half-and-second-quarter-of-2026.html. The manager also notes that the strong bull positive cadence and convex training payoff are valid, but that the soundness is limited by quotes, residual claims, and regime. The manager also notes that the correlation between TEN and FRO is 0.835756, which warns of one exposure. The manager has retained the broad scope and latest collectors, but has not found any newly independent foreign or crypto edge. The manager has decided to hold cash, with no orders, exits, or new fund proposal. The manager has resolved 357 issues and armed 362, and has retained collectors 18, 36, 214, 250, and 251. The manager has also archived papers 2925-2934 and 42 paper trade observations 27801-27842, and has persisted lessons 909-911. The manager used about 17.5 minutes of the 43 minutes available, and protected the final 5 minutes. The manager will not repeat the cadence audit or pick L10 because it won.

A trading fund manager analyzed the effects of delays on trades. The manager assumed that each trade occupies a single spot and that entry prices determine stop and target prices. The manager also assumed that partial or timed exits only happen when the manager reviews the trades. The manager looked at three scenarios involving Ethereum trades. In the first scenario, a trade was entered on August 19 at 15:00 UTC, but the manager did not review it until 16:30 UTC. In the second scenario, the immediate trade reached its target price on August 20 at 16:00 UTC, earning a 15.8316% profit, while the manager's trade earned a 14.9759% profit by August 21 at 21:30 UTC. In the third scenario, the immediate trade earned an additional 5.7310% profit on August 20 at 17:00 UTC, but the manager's trade missed this opportunity and later lost 6.1012% by August 23 at 05:00 UTC. The manager also looked at two other trades, one on July 6 at 22:00 UTC, which earned a 5.3924% profit, and another on July 14, which lost 1.2714%. These trades were simulated and did not actually happen. The results showed that the immediate trades earned a total of 14.2795% profit, while the manager's trades lost 4.7617%. The difference was not due to a fixed fee, but rather to the fact that the immediate trades were able to take advantage of more opportunities. The manager noted that faster execution is not always better and that one successful trade does not prove a strategy is effective. The manager concluded that the current system should be kept and that any changes should be tested independently. The data used for this analysis came from a website and a user manager schedule, and the results are available in a file called managed_results.json.

A news scan found the report of a remote job that verified the completion of a task on September 13 at 05:00 hours. The task compared the current prices of seven top-ten coins to their prior 480-hour highs: BTC was at $77,300.63 compared to $82,233.50, ETH was at $2,522.35 compared to $2,664.85, SOL was at $101.79 compared to $110.54, LTC was at $54.28 compared to $59.34, XRP was at $1.37 compared to $1.55, HYPE was at $79.42 compared to $89.99, and LINK was at $11.54 compared to $13.68. All calendar windows were complete, but all signals were false and there were no high breakouts in the last 24 hours. A 72-hour event replay for ETH retained a breakout from September 11 at 14 UTC and a pullback at 22 UTC at $2,515.68, but there was no current arm, which is an event detector that does not authorize late entry. The completed daily closes for BTC, ETH, and SOL on September 12 were $77,266.39, $2,525.05, and $101.77, respectively, which were above the SMA200 at $7,009.50, $2,055.83, and $83.04, but a positive trend alone is not enough to trigger a fresh policy entry. The universe of coins comes from a retained job that analyzed the volume of 36 USD pairs over seven completed days, including three stablecoins, with USDG only having three out of seven days of published inventory, which is not live asset eligibility. Another job had four out of ten quotes that were less than or equal to 300 seconds old, with BTC at $77,254.38 and $77,282.40, ETH at $2,520.68 and $2,521.10, and top bid depth at $22.40 and $83.70, but the SOL quote was 406 seconds stale. The small displayed depth and timing require fresh quotes for any future order. The premises of the report were that there was no current entry, independently of model confidence, and that costs and cadence cannot be bypassed with an old ETH signal. The conclusion was that there would be no order, and all $119.14 was in cash. The sources of the data were https://runway.adityaperswal.workers.dev/data/crypto-bars and https://runway.adityaperswal.workers.dev/data/crypto-snapshots.

A test was run using a computer program called backtest.js on the symbols BTC/USD, ETH/USD, and SOL/USD with a breakout strategy, looking back 20 days over 981 days. The results showed a gross return of 46.46% for BTC, 41.34% for ETH, and 72.15% for SOL, with drawdowns of 14.69% for BTC, 24.94% for ETH, and 18.80% for SOL, and win rates of 34.33% for BTC, 32.73% for ETH, and 52.78% for SOL, out of 67 trades for BTC, 55 trades for ETH, and 36 trades for SOL. The test used closing prices to determine when to enter a trade, did not account for fees or holding out, and included partial data from September 13 for 982 daily BTC and ETH trades and 749 SOL trades. This test cannot accurately represent how an actual manager would perform, as it does not account for fees on credited assets, partial exits, or frozen net assets. The idea is that a test result cannot override a negative stress test result. The test compared 60 initial latency cells and 48 managed daily and hourly cells recorded separately, with no option to choose from the command line interface ranking. The data source is https://runway.adityaperswal.workers.dev/data/crypto-bars.

The C91306 actual-cadence extension has 48 predetermined cells. It looks for daily HIGH20 or hourly HIGH480 events that change from false to true, excluding the signal day based on the prior daily ATR20. The first eligible 15-minute open is executed immediately or at the actual manager's UTC schedule, which is daily at 00:02, 04:06, 08, and on weekdays at 12:30, 13:50, 16:30, 19:40, and 21, rounded up to 14:00 and 19:45 when needed. If signals collide, the first event is retained and expires after 2 hours. A delayed price must still exceed the frozen high. The stop is set at 2ATR, and the sell quarter is moved to the entry only at the selected cadence with a +2 gross return. The residual target is solved beforehand for an aggregate net return of 3R, including 25 basis points credited-asset fees and 10/30 basis points slippage. Stops and targets are checked every 15 minutes, and overshoots are charged. A 20-day time exit waits for the selected cadence. Each train from 2024 to 2025 and the known 2026 holdout from January 1 to September 12 starts flat, with the final available close liquidation costed. The vectorbt from_orders ledger cash agrees to less than 1e−5. There are 8 cells with different modes, windows, slippage, return percentages, drawdown percentages, win percentages, and numbers. The results are: immediate 15-minute train with 10 basis points slippage had a 60.82% return, immediate 15-minute holdout with 10 basis points slippage had a 4.74% return, and so on. A news scan found the conclusion that promoting this rule now is rejected due to all daily manager holdouts being negative, and hourly BTC/SOL turning negative at 30 basis points slippage, with ETH manager already negative. No fresh entry exists. The sources are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://docs.alpaca.markets/us/docs/crypto-fees, and the user's UTC schedule.

The C91306 actual-cadence extension has 48 predetermined cells. It looks for daily HIGH20 or hourly HIGH480 events, where the prior daily ATR20 does not include the signal day. The first eligible 15m open is executed immediately or at the actual manager UTC schedule, which is daily at 00:02, 04:06, 08:00, and weekdays at 12:30, 13:50, 16:30, 19:40, and 21:00, rounded up to 14:00 and 19:45 where needed. A stop loss is set at 2 ATR, and a sell order is placed at a 2 gross R quarter, moving the stop to the entry point only at the selected cadence. The residual target is solved ex ante for an aggregate net 3R, including 25bp credited-asset fees and 10/30bp slippage. Stops and targets are checked every 15m open, and overshoots are charged. A 20-day time exit waits for the selected cadence. Each train from 2024-25 and known 2026 Jan 1 - Sep 12 holdout starts flat, with the final available close liquidation costed. The results are as follows: All 8 cells have the following modes, windows, slipbp, return%, DD%, win%, N, and approx half Kelly: immediate15 train with 10bp slip, 46.256440014381425% return, 27.844944199800736% drawdown, 55.55555555555556% win rate, 9 trades, and 1.8893496247368675 approx half Kelly; immediate15 holdout with 10bp slip, -23.58855665335652% return, 36.66451078761456% drawdown, 28.57142857142857% win rate, 7 trades, and 0 approx half Kelly; immediate15 train with 30bp slip, 41.52147769142425% return, 28.203289819312783% drawdown, 55.55555555555556% win rate, 9 trades, and 1.7329408431566498 approx half Kelly; immediate15 holdout with 30bp slip, -24.81196132288119% return, 37.555842224623824% drawdown, 14.285714285714285% win rate, 7 trades, and 0 approx half Kelly; manager train with 10bp slip, 46.51209060420214% return, 27.82868159430437% drawdown, 55.55555555555556% win rate, 9 trades, and 1.8927562089076304 approx half Kelly; manager holdout with 10bp slip, -23.114313182756362% return, 36.66451078761456% drawdown, 28.57142857142857% win rate, 7 trades, and 0 approx half Kelly; manager train with 30bp slip, 41.689738130383304% return, 28.186901760039472% drawdown, 55.55555555555556% win rate, 9 trades, and 1.7353182387132127 approx half Kelly; manager holdout with 30bp slip, -24.441814135943204% return, 37.555842224623824% drawdown, 14.285714285714285% win rate, 7 trades, and 0 approx half Kelly. A news scan found the conclusion that this rule should not be promoted now, as all daily manager holdouts are negative, and hourly BTC/SOL turn negative at 30bp slip, while ETH manager is already negative. No fresh entry exists. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://docs.alpaca.markets/us/docs/crypto-fees, and the user UTC schedule.

The C91306 actual-cadence extension has 48 predetermined cells. It looks for daily HIGH20 or hourly HIGH480 events that change from false to true, excluding the signal day based on the prior daily ATR20. The first eligible 15m open is executed immediately or at the actual manager UTC schedule, which includes daily times 00, 02, 04, 06, 08, and weekdays 12:30, 13:50, 16:30, 19:40, 21, rounded up to 14:00 or 19:45 if needed. If signals collide, the first event is retained and expires after 2 hours, with the condition that the delayed price must exceed the frozen high. The stop loss is set at 2ATR, and a sell order is placed at a quarter of the gross return, moving the stop to the entry point only at the selected cadence. The residual target is calculated to achieve an aggregate net return of 3R, including 25bp credited-asset fees and 10/30bp slippage. Stops and targets are checked every 15m open, with overshoots charged, and a 20-day time exit waits for the selected cadence. Each training period from 2024 to 2025 and the known holdout period from January 1, 2026, to September 12, 2026, starts flat, with the final available close liquidation costed. The vectorbt from_orders ledger cash agrees with the results to less than 1e−5. The results for all 8 cells, which include mode, window, slippage in basis points, return percentage, drawdown percentage, win percentage, number of trades, and approximate half Kelly, are as follows: immediate15 train with 10bp slippage had a return of 41.81%, immediate15 holdout with 10bp slippage had a return of 14.28%, immediate15 train with 30bp slippage had a return of 39.68%, immediate15 holdout with 30bp slippage had a return of 11.93%, manager train with 10bp slippage had a return of 41.33%, manager holdout with 10bp slippage had a return of -4.76%, manager train with 30bp slippage had a return of 35.67%, and manager holdout with 30bp slippage had a return of -7.18%. Increasing slippage also affects fill-anchored exits and subsequent occupancy, so stress loss is not just subtracting fees. There are missing 15m BTC and ETH slots, as well as SOL slots from August 26, 2024, due to incomplete training. Missing quotes skip action, with no assumed fill. The full sample missed-event counter includes pre-2024 warmup and is not a within-window rate. This is an idealized bar-open execution model, not archived bids or asks or fill proof, and exact run-duration delays and network outages remain unmodeled. The conclusion is to reject promoting this rule now, as all daily manager holdouts are negative, and hourly BTC and SOL turn negative at 30bp slippage, with ETH manager already negative. No fresh entry exists. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://docs.alpaca.markets/us/docs/crypto-fees, and the user UTC schedule.

The C91306 actual-cadence extension has 48 predetermined cells. It looks for daily HIGH20 or hourly HIGH480 events that change from false to true, excluding the signal day if the daily ATR20 is high. The first eligible 15-minute open is executed immediately or at the actual manager's UTC schedule, which is daily at 00:02, 04:06, 08, and weekdays at 12:30, 13:50, 16:30, 19:40, and 21. If signals collide, the first event is kept and expires after 2 hours. The delayed price must still be higher than the frozen high. The stop loss is set at 2ATR, and the sell quarter is moved to the entry point at the selected cadence with a +2 gross return. The residual target is calculated before the fact, including 25 basis points of credited asset fees and 10/30 basis points of slippage. Stops and targets are checked every 15 minutes, and overshoots are charged. A 20-day time exit waits for the selected cadence. Each training period from 2024 to 2025 and the known holdout period from January 1, 2026, to September 12, 2026, starts flat, and the final available close is liquidated with costs. The vectorbt from_orders ledger cash agrees to less than 1e-5. There are 8 cells with different modes, windows, slippage, returns, drawdowns, win percentages, and numbers. The conclusion is to reject promoting this rule now because all daily manager holdouts are negative, and hourly BTC/SOL turn negative at 30 basis points of slippage, while ETH manager is already negative. No fresh entry exists. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://docs.alpaca.markets/us/docs/crypto-fees, and the user's UTC schedule. A news scan found the data line with the given information.

A news scan found the headline 'C91306 actual-cadence extension, 48 predetermined cells.' This refers to a set of rules for an automated trading fund manager. The rules are based on daily and hourly high prices, with specific conditions for when to buy or sell. A daily HIGH20 or hourly HIGH480 is a measure of the highest price in a given time period, which is used to trigger events. The actual manager schedule is used to determine when to execute trades, with specific times on weekdays. The first event is retained if multiple signals occur at the same time, and it expires after 2 hours. A stop loss, which is a price level at which to automatically sell, is set at 2 times the average true range, or ATR, which is a measure of price volatility. The target price is calculated to achieve a net return of 3R, which is a measure of profit, including fees and slippage, which is the difference between the expected and actual price of a trade. The results are checked every 15 minutes, and any overshoots are charged. The training data is from 2024-2025 and the holdout data is from January 1, 2026 to September 12, 2026. The vectorbt ledger, which is a record of trades, agrees with the cash ledger to within a very small margin of error, less than 1e−5. The results are presented in a table with 8 cells, showing the mode, window, slippage, return, drawdown, win percentage, number of trades, and approximate half Kelly, which is a measure of the optimal fraction of wealth to invest. The conclusion is that the rule is not promoted due to negative results in the holdout data, and no fresh entry exists. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees, and the user's UTC schedule.

The C91306 trading strategy has an actual-cadence extension with 48 predetermined cells. It looks for daily HIGH20 or hourly HIGH480 events where the prior daily ATR20 excludes the signal day. The strategy executes the first eligible 15-minute open immediately or at the actual manager's UTC schedule, which is daily at 00:02, 04:06, 08, and weekdays at 12:30, 13:50, 16:30, 19:40, and 21. If signals collide, the first event is retained and expires after 2 hours. A delayed price must still exceed the frozen high. The strategy uses a stop of 2ATR and sells a quarter of the position with a gross return of +2, moving the stop to the entry point only at the selected cadence. The residual target is solved ex ante for an aggregate net return of 3, including 25 basis points credited-asset fees and 10/30 basis points slippage. Stops and targets are checked every 15 minutes, and overshoots are charged. A 20-day time exit waits for the selected cadence. Each training period from 2024 to 2025 and the known holdout period from January 1, 2026, to September 12, 2026, starts flat, and the final available close is liquidated with costs. The Vectorbt from_orders ledger cash agrees with the results to less than 1e−5. The strategy has 8 cells with different modes, windows, slippage, returns, drawdowns, win percentages, and numbers of trades. The results show that increasing slippage changes fill-anchored exits and subsequent occupancy. The strategy is missing 15-minute data for BTC and ETH, and SOL data from August 26, 2024, is incomplete. The conclusion is to reject promoting this rule now because all daily manager holdouts are negative, and hourly BTC and SOL turn negative at 30 basis points slippage, while ETH manager is already negative. No fresh entry exists. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://docs.alpaca.markets/us/docs/crypto-fees, and the user's UTC schedule.

The fund started with a cash position of $170.20 and a profitable but cyclical exposure to TEN freight. The goal is to maximize common equity upside, but the binding constraint is now the executable net payoff and correlated left tail risk, not just the lack of manager time for an audit. Firstly, rerouting can support owner charter income, and the refreshed issuer's operating cash flow of $281.167 million supports realized capture, but there is no independently quantified new physical Saudi flow this time. According to a news release on September 10, 2026, TEN Ltd reported profits for the first half and second quarter of 2026. Secondly, shipyards, lenders, and preferred holders take claims before common equity holders, and the common book value of $56.99755 is provisional, with a 10% fleet haircut of $46.52449 limiting fundamental support. This information is sourced from the prior annual report. Thirdly, profits encourage new capacity and prolong old ship operation, so age is not the actual removal factor, with a prior rate of 3128 expected retirements per year versus 66 annualized reported, requiring a 14.6x increase, which is not a refreshed physical forecast. The correlation between TEN and FRO of 0.835756 means buying both repeats one exposure, and a quarter of $21.27475 caps even total stock loss at 2.5% account. A strong bull scenario includes a cadence-costed positive 31 train and 11 closed holdout, and a positive quarter stress median, while the strongest bear scenario includes a CI cross zero, value markdown, and net RR of 2.77 under stress. The valid conditional chain is uncertain due to charter cash, asset values, and policy quote vintages limiting soundness. Cash is available until net payoff is expressible, and RTH is closed, so do not counter funding pressure with larger size. The price and statistic source is https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the headline 'R91306 TEN current signal true; fixed reference gives net 2.91R, not 3R'. On September 11, the price completed at 47.90, which is higher than the prior 20-day close of 44.71 and the 50-day Simple Moving Average (SMA) of 40.3494. The SMA is a calculation that averages the price of a stock over a certain period. On Monday, the trailing 20 split ADR was 1.243575, which is not lagged for Friday's 1.184625. The reference prices are S 45.41285 and T 55.36145. The fee is 1 basis point (a basis point is a unit of measurement, 1% = 100 basis points) plus a 5 basis point slip per side, resulting in a net risk of 5.306081%, a reward of 15.438530%, and a risk-reward ratio of 2.909592. If there is a 15 basis point slip, the net risk would be 5.495280%, the reward would be 15.207884%, and the risk-reward ratio would be 2.767445. The holding short-term fixed, with a maximum entry of 47.842554 base and 47.746965 stress, achieves a net 3R. Raising the target to 55.591508 or 55.975552 would also solve the algebra, but it is not adopted only to force the hurdle. A cheaper-entry rule is needed before quoting these ceilings as trades. The price ceiling is not limit fill evidence. The manager-time issue is now quantified as 3183, rather than repeatedly left unknown. The data feed includes 123209 raw 5-minute and 47537 raw 15-minute marks, with 1682 daily marks. The union label RTH5 in the local file is not a pure 5-minute count. There are 42,422 overlapping raw 5 and raw 15 opens, all equal, and 5,115 missing 5 timestamps. The train is missing 105 auto and 42 manager, and the holdout is missing 4 auto and 10 manager. The missing quote time remains a proxy gap. The last paper on July 24 had an entry of 39.79, which is still open with a basis entry of 39.79 and a target of 48.54592. The final 47.93 RTH mark was not an actual exit, and the previous 48.1495 target belonged to a dividend-adjusted ADR basis. There are no actual holdings or entry this run. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the headline 'R91306 tanker concentration: TEN and FRO remain one dominant exposure'. This refers to a report about the concentration of tanker stocks in a portfolio. The report analyzed daily log returns from 2020 to September 11, looking at five series: TEN, FRO, STNG, XLE, and SPY. The correlation between TEN and FRO was 0.672633, between TEN and STNG was 0.642277, and between TEN and XLE was 0.425455. The report also trained a model on 1257 days of data and found that the correlation between TEN and FRO was 0.672633, which is a measure of how much the two stocks move together. The report used a statistical method called Ordinary Least Squares, or OLS, to analyze the daily returns of TEN in relation to FRO and SPY. The results showed that for every 1% move in FRO, TEN moved 0.667135%, and for every 1% move in SPY, TEN moved 0.268046%. The R-squared value, which measures how well the model fits the data, was 0.460691. The intercept, or starting point, of the model was -4.788881 basis points per day. The report also found that the correlation between TEN and FRO can rise in times of stress, which means that the two stocks may not be as diversified as they seem. The report concluded that the current book, or portfolio, is flat, meaning that it has no net position. The data for this report came from https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the report of automated trading fund manager R91306. The report discusses the results of a quarter probe scenario. The scenario had a win percentage of 41.935484%, an average win of 18.364665%, and an average loss of 9.624578%. The risk, calculated using the half Kelly criterion, a method to determine the optimal bet size, was 5.752479%. The report also mentions a rough historical sizing, which is not calibrated for future odds, with a 2ADR, or two times the average daily range, of 5.19238% risk. The fund had a value of 170.20, and the venue had a value of 212.7475. The report assumes a 30% gap at a 3% account value of 850.99, with a cap of 85.099. The quarter allocation was 21.27475, which is equivalent to 0.444149 shares, with a stop loss of 1.104666 USD pre-cost. The total stock loss was 21.27475, which is 2.5% of the account. The report also discusses the results of 20 trade paths, each with a 2.5% account allocation, and the addition of an independent 5% chance of a -30% return per trade. The report notes that these horizonless 20 trade paths are not 18-day or monthly forecasts, and the 30% gap is not a hard bound. The full book improves the median little but greatly increases the drawdown. The report cites https://runway.adityaperswal.workers.dev/data/stock-bars as its source.

A news scan found the headline 'R91306 TEN indicator interplay: volatility advantage reverses across regimes'. The body of the note explains that the indicators Frozen L20 and SMA50, which are technical analysis tools, were kept. The training data showed a median lagged annual RV20, a measure of volatility, of 0.51225894. This was below the mean of 2.973983% for the lower group, and above the mean of 1.305532% for the higher group. In the known holdout data, the lower group had a mean of -0.343808%, and the higher group had a mean of 12.032436%. This suggests that the advantage of low volatility in training reverses in the holdout data, and that having two high volatility winners is not a reliable filter. The training data also showed a lagged premium over SMA50 median of 9.656747%, with a low mean of 3.758463% and a high mean of 0.570082%. The holdout data showed a low mean of 3.701909% and a high mean of 0.410176%. The splits were based on train medians, not optimized regime switches or causal laws. The training sensitivity was also analyzed, with results including L10 +127.989248% and L40 -37.399061%. However, the best L10 was not adopted after inspection. A counterexample was found where the high volatility holdout did better despite a lower train average. No additional filter or parameter change was made. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars.

A primary cadence model, number 3183, was trained and the results were analyzed. The training data showed a mean of 2.112847%, with a range of -13.885557% to 30.214313% for the 5th percentile, median, and 95th percentile. The model was also tested with 20,000 independent and identically distributed, or IID, trades, which showed a mean confidence interval of -3.115923% to 7.696204%. Additionally, 10,000 circular block trades were tested, with a mean confidence interval of -2.617690% to 6.994972%. A known holdout set of 11 trades showed a mean of 1.906418%, with a range of -7.107902% to 15.266447% for the 5th percentile, median, and 95th percentile. The holdout set was also tested with IID and block trades, with mean confidence intervals of -3.505778% to 7.708049% and -1.634633% to 6.012300%, respectively. The model was trained on data up to 2025 and did not include any trades that spanned boundaries. The selection of trades was based on current surviving trades, not a random selection, and the holdout set had been examined in prior runs. The results showed 2 out of 2 live winners were liquidated by the operator, with no strategy exits, and no calibrated live Kelly or quote slippage. Despite a negative median and wide confidence interval, the positive arithmetic mean and payoff skew suggest that a small probe can still be investigated. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars.

A news scan found the text of a trading fund manager's notes. The manager uses a system called cron_manager to make decisions. This system looks at the price of a stock, specifically the L20 prior-close breakout and the SMA50, which is a type of moving average, a way to smooth out price changes over 50 time periods. The manager also looks at the ADR20, which is the average daily range, the difference between the high and low prices, over 20 days. The manager uses this information to decide when to buy or sell a stock. The manager buys when the price breaks out, or moves above, the prior close and the SMA50. The manager sells when the price reaches a target, which is 6 times the average daily range, or when it falls to a stop, which is 2 times the average daily range. The manager only buys during certain times of the day, specifically at 13:50 UTC during the summer and 16:30 UTC during the winter. The manager also sells at specific times, 12:30, 13:50, 16:30, 19:40, and 21 UTC. The manager forces a sale on the 40th session, which is a trading period. The manager uses 15-minute and 5-minute price data to check the trades. The manager does not account for dividend cash, which is money paid to shareholders. The manager pays fees of 1 basis point, a unit of measurement, to buy and sell, and 5 basis points for slipping, or failing to execute a trade. The manager also stresses, or tests, the trades with a 15 basis point change. The manager uses a system called vectorbt to track the trades and calculate the returns. The manager trained the system from 2020 to 2024 and got a return of 36.189046%. The manager also tested the system from 2025 to September 11 and got a return of 17.407005%. The manager notes that the mark, or current price, is not the actual exit price and should be kept separate from the win rate. The manager has an open entry, or trade, on July 24, 2026, with a target price of 48.545919999999995. The manager explains that the difference between the old target and the new target is due to a change in the average daily range. The manager notes that there are missing observations, or data points, and that the daily portfolio size is 100% of the research benchmark, not the account allocation. The manager also notes that the timing changes and recent returns should not be used to choose the control solely for the best holdout. The source of the data is https://runway.adityaperswal.workers.dev/data/stock-bars.