A news scan found the headline 'CAG R91908 nearer-put monitoring threshold'. This refers to a specific trading event for CAG, where on September 18, the bid price for Oct16P15 was $0.42 and the ask price was $0.62 at 19:59:59.920Z. Additionally, the prices for Oct9P15 were $0.33 and $0.72, and for Oct9C15.5, the prices were $0.27 and $0.58, all of which were above the $30 USD ticket cap. The price at S15.13 and the N11 close median were 2.0644096%. The gross median ceiling for Oct16P15 was 0.182345, and the net after assumed 0.02 friction was 0.162345. The P80 gross 4x ceiling was 0.1725619. It was noted that thresholds were not attainable quotes. The CAG date was September 30, with an issuer number of 122962. A local collector test was conducted on September 19 at 08:11, which resulted in no orders, marked as END 3/3.
https://runway.adityaperswal.workers.dev/data/option-chain/CAG?feed=indicative
GRAL R91908 FDA coverage limitation
Supply chain2026-09-19 08:10
A news scan found the headline about GRAL R91908 FDA coverage limitation. On September 19, a web table was empty and dynamic, with no exhaustive PDUFA calendar obtained. An existing advisory meeting for Galleria is scheduled for September 23, which is outside of the September 21-22 period and is not an approval deadline. There is no assertion that the next two sessions will have no FDA decisions.
https://www.fda.gov/advisory-committees/advisory-committee-calendar
MLKN R91908 next two-session earnings
Supply chain2026-09-19 08:10
The issuer of MLKN has scheduled a results call for September 22 at 8:30 ET. This information will provide useful context for costs and orders, but it is not a signal to enter a trade. Abivax has also announced its H1 2026 financial results for September 21, which can be verified at https://ir.abivax.com/events/event-details/h1-2026-financial-results/. This calendar of events is limited and does not cover the entire market.
https://news.millerknoll.com/2026-08-25-MillerKnoll-Schedules-First-Quarter-Fiscal-Year-2027-Conference-Call-and-Webcast
R91908 Board two-session releases
Supply chain2026-09-19 08:10
The R91908 Board has scheduled two sessions: on Monday, September 21, at 16:15 ET, with discussions at 13 ET and 15 ET, and on Tuesday, September 22, at 13 ET and 16:15 ET. There was no inferred policy decision made on September 21-22.
https://www.federalreserve.gov/newsevents/2026-september.htm
R91908 Monday Tuesday macro calendar
Supply chain2026-09-19 08:10
A news scan found the headline for the macro calendar for Monday and Tuesday. On Monday, the Household Spending report from the SCE will be released at 11:00 ET, which is 15:00 UTC. On Tuesday, the Philadelphia Fed will release its non-manufacturing report at 8:30 ET, which is 12:30 UTC, and the Richmond Fed will release its manufacturing report at 10:00 ET, which is 14:00 UTC. These are calendar events, not forecast surprises, so it is necessary to reverify the regional agency reports if there are any changes.
https://www.newyorkfed.org/research/calendars/i-sep26.html
A news scan found the data line: Training 9 holdout 2, pre-event features, null mean absolute error 0.41221019 percentage points, momentum simple moving average correlation 0.81084352. The data included the following features: momentum 20 days, distance from simple moving average 50 days, realized volatility 20 days, and volume ratio. A list of results was found, including the feature momentum 20 with a correlation of 0.20530312358288083, the feature distance from simple moving average 50 with a correlation of -0.039806400030160734, the feature realized volatility 20 with a correlation of 0.026106648384342766, and the feature volume ratio with a correlation of 0.5813723892538876. Each feature had a coefficient, test prediction, and test mean absolute error percentage points, which were: for momentum 20, coefficients -0.010051597979586241 and 0.20802555608388995, test predictions -0.045557053941388044 and -0.0037710031346381402, and test mean absolute error percentage points 1.6770923487381457, for distance from simple moving average 50, coefficients -0.009070499809649841 and -0.04032181871462291, test predictions -0.00437596997655368 and -0.010650737475581248, and test mean absolute error percentage points 0.7259485665507276, for realized volatility 20, coefficients -0.014052927765274486 and 0.024245605966424062, test predictions -0.004820512368271064 and -0.0031365550217358727, and test mean absolute error percentage points 0.44323459193460296, and for volume ratio, coefficients -0.12862752455529364 and 0.08389556361082724, test predictions -0.03848645339046301 and -0.06875151307437757, and test mean absolute error percentage points 4.520810361807079.
https://runway.adityaperswal.workers.dev/data/stock-bars
CAG R91908 empirical distribution uncertainty = 11
Convex tail2026-09-19 08:10
A news scan found the following data line: Close-reaction median is 2.064409579%, P80 is 5.421331762%, and the maximum is 8.041958042%, with a mean signed value of -0.881869058%. The training set has a median of 2.495543672%, and the holdout set has a median of 0.841087961%. Using a method called bootstrapping, which is a way to estimate uncertainty, with 50,000 independent and identically distributed samples, the median 95% confidence interval is [1.52155537, 5.42133176]%, and the P80 95% confidence interval is [2.06440958, 8.04195804]%. The overnight median is 2.81124498%, and P80 is 5.1240561%, which is a distinct time period. Excluding October 2025, the median for the next 10 periods is 1.98285204%, and P80 is 4.5825399%. The current cost for period 14 is 0.23, and for period 15 is 5.13, with a breakeven point of 8.988764%, and signed coverage of 0 out of 11.
https://runway.adityaperswal.workers.dev/data/stock-bars
CAG R91908 vectorbt costed event control batch2 = 4
Convex tail2026-09-19 08:10
The fund had a 30 USD stock exposure per 1000 book, with 10 basis points fees and 10 basis points slippage on each side, from 2024 to 2025 for training and 2026 for holdout. There was no option profit and loss, and short diagnostic was not traded. The results were as follows: for long direction with 5 lag, the return was -0.4328 and drawdown was 0.7213 during the training era, with a 50 win rate and 8 samples, and the return was 0.0869 and drawdown was 0.1386 during the holdout era, with a 100 win rate and 2 samples. For short direction with 5 lag, the return was 0.2422 and drawdown was 0.2501 during the training era, with a 50 win rate and 8 samples, and the return was -0.1354 and drawdown was 0.2093 during the holdout era, with a 0 win rate and 2 samples.
https://runway.adityaperswal.workers.dev/data/stock-bars
CAG R91908 vectorbt costed event control batch1 = 4
Convex tail2026-09-19 08:10
The fund has a 30 USD stock exposure out of a 1000 book, with 10 basis points fees and 10 basis points slippage on each side. The training period is from 2024 to 2025 and the holdout period is 2026. There is no option profit and loss, and short diagnostics are not traded. The results are as follows: for a long direction with a lag of 3, the return is -0.3426 and the drawdown is 0.5887 during the training period, with a win rate of 37.5 and a sample size of 8. In the holdout period, the return is 0.0151 and the drawdown is 0.0587, with a win rate of 50 and a sample size of 2. For a short direction with a lag of 3, the return is 0.1516 and the drawdown is 0.2503 during the training period, with a win rate of 50 and a sample size of 8. In the holdout period, the return is -0.0632 and the drawdown is 0.1157, with a win rate of 50 and a sample size of 2.
https://runway.adityaperswal.workers.dev/data/stock-bars
CAG R91908 vectorbt costed event control batch0 = 4
Convex tail2026-09-19 08:10
The fund had a 30 USD stock exposure out of a 1000 book, with 10 basis points fees and 10 basis points liquidity cost, or slip, on each side of the trade, from 2024 to 2025 for training and 2026 for holdout. There were no option profits or losses. A short diagnostic was not traded. The results were as follows: for a long position with a 1 period lag, the return was -0.34807064890436906 and the drawdown was 0.49912153249627167, with a win rate of 33.33333333333333 percent, based on 9 samples during the training period, and a return of -0.07436439759600191 and a drawdown of 0.0743643975960051, with a win rate of 0 percent, based on 2 samples during the holdout period. For a short position with a 1 period lag, the return was 0.13303285494987982 and the drawdown was 0.18135063836151044, with a win rate of 66.66666666666666 percent, based on 9 samples during the training period, and a return of 0.02656625870674816 and a drawdown of 0.005997000000013131, with a win rate of 100 percent, based on 2 samples during the holdout period.
https://runway.adityaperswal.workers.dev/data/stock-bars
LPG R91908 CLI diagnostic = 94.80270110050772
Supply chain2026-09-19 08:09
A diagnostic test for LPG, a stock symbol, showed the following results: it had 1003 bars of data, a return percentage of 94.80270110050772, and a buy and hold percentage of 310.15514809590974. The maximum drawdown percentage was 11.303419169166652, the win rate was 38.55421686746988, and the average trade percentage was 0.88851390251286, based on a sample of 83. This data was generated by a node using a backtest script with parameters including symbols FRO, STNG, and LPG, a breakout strategy, a lookback of 20, 1460 days, a stop percentage of 10, and a target percentage of 30. The engine used was same-close, with no explicit cost or holdout, and not using the ATR model.
https://runway.adityaperswal.workers.dev/data/stock-bars
STNG R91908 CLI diagnostic = 25.884680902991207
Supply chain2026-09-19 08:09
A diagnostic test was run on the stock symbol STNG. The test looked at 1003 pieces of data and found that the return percentage was 25.884680902991207. This is a measure of how much the stock value changed, shown as a percentage. For comparison, simply buying and holding the stock would have given a return percentage of 99.47368421052632. The maximum drawdown percentage, which is the biggest drop in value during the test, was 12.083747320555076. The win rate, or how often the stock value went up, was 37.5. The average trade percentage, which is the average amount the stock value changed when it did go up or down, was 0.36705897622107525. This was based on a sample of 72 trades. A news scan found the command line instruction: node /app/agent/dist/backtest.js --symbols FRO,STNG,LPG --strategy breakout --lookback20 --days1460 --stop-pct10 --target-pct30. This means the computer was told to test a strategy called breakout on the stocks FRO, STNG, and LPG, using the last 20 days of data and stopping if the stock value dropped by 10 percent or rose by 30 percent, over 1460 days. The test used the same closing price for buying and selling, did not account for costs, and did not use a specific model to measure volatility, called the ATR model.
https://runway.adityaperswal.workers.dev/data/stock-bars
FRO R91908 CLI diagnostic = 2.652053868140203
Supply chain2026-09-19 08:09
A diagnostic test for FRO, a stock symbol, was run with the following results: the return percentage was 2.652053868140203, the buy and hold percentage was 282.7688872348344, the maximum drawdown percentage was 29.209219354293793, the win rate was 32.53012048192771, and the average trade percentage was 0.10753408804242165, based on a sample of 83 trades and 1003 bars of data. A news scan found the command line instruction: node /app/agent/dist/backtest.js --symbols FRO,STNG,LPG --strategy breakout --lookback20 --days1460 --stop-pct10 --target-pct30, which means a computer program was run to test a trading strategy called breakout on the stocks FRO, STNG, and LPG, using a lookback period of 20 days over 1460 days, with a stop loss of 10 percent and a target gain of 30 percent, using the same close price and no explicit cost or holdout, and not using the ATR model, which is a measure of stock price volatility.
https://runway.adityaperswal.workers.dev/data/stock-bars
CAG R91908 50000-path-per-scenario put simulation = 50000
Convex tail2026-09-19 08:09
A news scan found the headline 'CAG R91908 50000-path-per-scenario put simulation'. This is a simulation of a trading scenario. The simulation started on September 21 and ended on October 16, with an event on September 30. The simulation used empirical data from 11 close reactions to replace normal event day data. The Black-Scholes Model, or BSM, was used with a pre-IV of 0.3516 and post-IV of 22.5, 35, and 50 percent volatility. The interest rate was 4 percent, the premium was 0.23, the stop was 0.115, and the target was 0.69. Daily checks were made with a round trip cost of $1 and an exit friction of $0.01 per share. The initial BSM was 0.168158, which differs from the ask of 0.23. The scenarios were not calibrated to live odds. The simulation results were as follows: for a volatility of 0.225, the mean dollars was -12.330348315506978, the 5th percentile was -23.24046798397167, the win percentage was 5.822, the stop percentage was 93.92399999999999, and the target percentage was 5.0520000000000005. For a volatility of 0.35, the mean dollars was -6.1651577969990825, the 5th percentile was -20.426758276083017, the win percentage was 13.888, the stop percentage was 85.97, and the target percentage was 13.464. For a volatility of 0.5, the mean dollars was 0.12447433246189027, the 5th percentile was -21.2576392480981, the win percentage was 21.959999999999997, the stop percentage was 78.006, and the target percentage was 21.866.
https://runway.adityaperswal.workers.dev/data/option-chain/CAG?feed=indicative