Notes

A news scan found the following data line: Observed Sep 11 04 UTC, which is a record of observations made on September 11 at 04 UTC. The data shows an audit of ETH/USD yearly matched OHLC, which stands for Open, High, Low, Close, a set of numbers that describe the price of a stock or currency over a certain period of time. The audit covers full 24-hour days only, with years separated and no imputation, meaning no missing values were filled in. The audit results are as follows: for the symbol ETH in the year 2024, there were 365 matched days, with 365 days showing a difference in OHLC, 0 days showing a difference in open price, and 365 days showing a difference in close price. In 2025, there were 364 matched days, with 203 days showing a difference in OHLC, 10 days showing a difference in open price, and 194 days showing a difference in close price. In 2026, there were 252 matched days, with 0 days showing a difference in OHLC, 0 days showing a difference in open price, and 0 days showing a difference in close price. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the following data: Historical data from 2024 to 2026 was retrieved on September 11 at 04 UTC. This data compares native and aggregate values for BTC/USD over full 24-hour days. The three largest absolute relative differences are listed, without claiming any cause. The differences are as follows: on January 15, 2025, the native value was 100416.199 and the aggregate value was 100511.3465, with a difference of -0.09466344180356634 percent; on April 4, 2024, the native value was 68592.7 and the aggregate value was 68529.9035, with a difference of 0.09163372016129934 percent; on November 19, 2024, the native value was 92345.65 and the aggregate value was 92424.43, with a difference of -0.08523720405957391 percent. https://runway.adityaperswal.workers.dev/data/crypto-bars

A historical review from 2024 to 2026, retrieved on September 11, 2024, at 04 UTC, compared native and aggregate data for BTC/USD on full 24-hour UTC days. The largest three absolute relative differences were found on the following days: the difference on December 2, 2025, was 3.986148185381033 percent, with a native value of 89602.3682237864 and an aggregate value of 86167.6; the difference on November 23, 2025, was 2.4489796834810784 percent, with a native value of 86694.1 and an aggregate value of 84621.731; and the difference on December 8, 2025, was 0.16528944742564278 percent, with a native value of 89692.422 and an aggregate value of 89544.4145320195. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the following data: Historical data from 2024 to 2026 was retrieved on September 11 at 04 UTC. This data compares the native and aggregate values for BTC/USD over full 24-hour UTC days. The largest 3 absolute relative differences are listed, without claiming any cause for these differences. The discrepancies are as follows: on November 23, 2025, the native value was 88127.942 and the aggregate value was 90165.3625169692, a difference of -2.2596487831851753 percent; on December 8, 2025, the native value was 91558.1005726285 and the aggregate value was 92306.181, a difference of -0.8104337318120658 percent; on December 14, 2025, the native value was 90240.3049507385 and the aggregate value was 90535.8714532015, a difference of -0.3264634202099437 percent. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the following data: Historical data from 2024 to 2026 was retrieved on September 11 at 04 UTC. This data compares the native and aggregate prices of Bitcoin (a type of digital currency) over full 24-hour periods. The largest three absolute relative differences are listed below, without claiming any cause for these differences. The data shows the following discrepancies: on December 2, 2025, the native price was 91625.132 and the aggregate price was 86270.82, a difference of 6.2064 percent; on November 23, 2025, the native price was 87421.966 and the aggregate price was 84698.415, a difference of 3.2156 percent; on December 14, 2025, the native price was 88793.16 and the aggregate price was 90323.263, a difference of -1.6940 percent. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the following data line: Observed on September 11 at 04 UTC, the results of a yearly audit of BTC/USD prices for the years 2024, 2025, and 2026 are as follows: the audit considered full 24-hour days only, with years separated and no missing data filled in. The audit results are: [{"symbol":"BTC","year":2024,"matched_days":365,"ohlc_any_difference":361,"open_difference":0,"close_difference":361},{"symbol":"BTC","year":2025,"matched_days":364,"ohlc_any_difference":203,"open_difference":12,"close_difference":193},{"symbol":"BTC","year":2026,"matched_days":252,"ohlc_any_difference":5,"open_difference":0,"close_difference":5}] https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native calendar/hourly holdout trail1 slip20'. Coverage attribution control means managing how data is used. This system keeps daily data even if hourly data is incomplete. It uses a fixed set of rules, including a 20 basis point slip, a 10 basis point target, and a 2 times risk entry. The system was trained from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results for the symbol SOL are as follows: the return was -11.38%, the drawdown was 35.68%, and the win rate was 28.57%. The system made 7 trades, with an average win of 13.52 and an average loss of 7.08. There were no trades made on days with zero volume. The results match another system called vectorbt, with no missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native calendar/hourly holdout trail1 slip10'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data it uses. It keeps daily data even if some hourly data is missing. The strategy uses specific rules, including a 20-day high and low, a 14-day average true range, a 10 basis point target, and a 25 basis point fee. It also has a 20-day timeout and checks the next timestamp open. If enabled, it uses a 2RBE entry and a 2ATR trail. The strategy was trained from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a return of -10.13513423271254, a drawdown of 35.03323677286272, and a win rate of 28.57142857142857. The average win was 13.7500032946408 and the average loss was 6.894719383827727. The results match another system called vectorbt, with no missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native calendar/hourly holdout trail0 slip20'. Coverage attribution control means the system checks the quality of the data. It keeps valid daily data even if the hourly data for that day is incomplete. The system uses a fixed set of rules, including a high and low price that does not change, a measure of price volatility called 2ATR14, and a target profit of 10 basis points. It also credits fees of 25 basis points and has a 20-day timeout. The system checks the next timestamp open and uses a 2RBE entry and 2ATR trail if enabled. The system was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results for the SOL symbol are as follows: the system made a return of -14.644645306834192, had a drawdown of 35.6796683685633, and a win rate of 28.57142857142857. The sample size was 7, the mean return was -1.763450950589423, the average win was 11.529782403440825, and the average loss was 7.080744292201521. There were no instances of zero volume entries or exits. The results match another system called vectorbt at a precision of 1e-10, and there were no fictitious missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native calendar/hourly holdout trail0 slip10'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data it uses. It keeps daily data even if some hourly data is missing. The strategy uses specific rules, including a 20-day high and low, a 14-day average true range, which is a measure of price volatility, and a fixed target of 10 basis points, which is a unit of measurement for interest rates and investment returns. It also credits fees of 25 basis points and has a 20-day timeout. The system checks the next timestamp open and uses a 2RBE, or two times risk-based entry, and a 2ATR, or two times average true range, trail if enabled. The strategy was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a return of -13.44%, a drawdown of 35.03%, and a win rate of 28.57%. The average win was 11.75% and the average loss was 6.89%. The results match another system called vectorbt at a very small margin of error, and there were no missing hour fills, which refers to gaps in the data. https://runway.adityaperswal.workers.dev/data/crypto-bars

A trading system called C91104 uses a special method to control its decisions, keeping daily data even if hourly data is incomplete. It uses specific rules, including a 20 basis point slip, to make trades. The system was trained on data from 2024 to 2025 and tested on data from January 1, 2026, to September 11, 2026. The results show a return of 19.095789114810245 percent and a drawdown of 31.93026465423815 percent. The system had a win rate of 41.66666666666667 percent and an average win of 13.555524409177577 percent. A basis point is a unit of measurement, equal to one hundredth of a percent. The system's results match another system called vectorbt, with no missing hourly data. https://runway.adityaperswal.workers.dev/data/crypto-bars

A trading system called C91104 uses a full-native calendar and hourly training data. It keeps daily data even if some hourly data is missing. The system uses specific rules, including a 20-day high and low, a 14-day average true range, and a 10 basis point target. It also credits fees of 25 basis points and has a 20-day timeout. The system checks for the next timestamp open and uses a 2RBE entry and 2ATR trail if enabled. The system was trained from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026, with a holdout period. The results show a return of 21.99%, a drawdown of 31.38%, and a win rate of 41.67%. The system made 12 trades with an average return of 2.22%. The average win was 13.78% and the average loss was 6.04%. There were 4 entries and 3 exits with zero volume. The results match another system called vectorbt with a small margin of error of 1e-10, and there are no missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native calendar/hourly train trail0 slip20'. This is a report about a trading system for the cryptocurrency SOL, which is traded against the US dollar. Coverage attribution control means the system checks the quality of the data it uses. The system keeps daily data even if some hourly data is missing. It uses a fixed set of rules, including a 20-day high and low, a 14-day average true range, which is a measure of how much prices move, and a target profit of 10 basis points, which is 0.1 percent. The system also credits fees of 25 basis points and has a 20-day timeout. It checks the next timestamp open and uses a 2RBE, or two times risk-based entry, and a 2ATR, or two times average true range, trail if enabled. The system was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results are as follows: the symbol is SOL, the source is native full, the signal is calendar, the execution is hourly, the part is train, the trail is false, the slip is 20 basis points, the return is -2.561500215154977 percent, the drawdown is 36.44372139916362 percent, the win rate is 33.33333333333333 percent, the sample size is 12, the mean is 0.7978837086137355, the average win is 19.17959594919288, the average loss is 8.392972411675837, there are 4 zero volume entries, and 3 zero volume exits. The wealth returns match vectorbt at 1e-10, which means they are very similar, and there are no fictitious missing hour fills, which means the system does not make up data for missing hours. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native calendar/hourly train trail0 slip10'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data it uses. The system retains daily data even if the hourly data for a day is incomplete. It uses specific rules to decide when to buy or sell, including a high and low price threshold, a measure of price volatility called 2ATR14, and a fixed target profit of 10 basis points. It also credits fees of 25 basis points and has a 20-day timeout. The system checks the next timestamp open and can use a trailing stop loss if enabled. The system was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026, with a holdout period starting at 00 UTC. The results show a return of -0.1947, a drawdown of 35.55, and a win rate of 33.33. The average win was 19.42 and the average loss was 8.21. There were 4 entries and 3 exits with zero volume. The wealth returns match the vectorbt system at a precision of 1e-10, with no fictitious missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A trading system called C91104 uses a method called coverage attribution control, which means it keeps daily data even if hourly data is incomplete. It uses specific rules, including a 20 basis point slip and a 10 basis point target, with fees of 25 basis points. The system also has a 20-day timeout and checks for the next timestamp open. If enabled, it uses a 2RBE entry and a 2ATR trail. The system was trained from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026, at 00:00 UTC for a holdout period. The results for the symbol SOL are as follows: the return was -28.09506955990557 percent, the drawdown was 33.19674129390442 percent, and the win rate was 14.285714285714285 percent, based on a sample of 7 trades, with a mean of -4.410229752400173. The average win was 7.862940130118989 and the average loss was 6.455758066153367. There were no zero-volume entries or exits. A news scan found the headline is not available, but the raw wealth returns match vectorbt at 1e-10, with no fictitious missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native daily/hourly holdout trail1 slip10'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data it uses. It keeps daily data even if hourly data is incomplete. The strategy uses specific rules, including a high and low price limit, a measure of price volatility called 2ATR14, and a fixed target for profits. It also credits fees of 25 basis points and has a 20-day timeout. The system checks for the next timestamp open and uses a trailing stop loss if enabled. The strategy was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a return of -27.08131846860409 percent, a drawdown of 32.39027116453072 percent, and a win rate of 14.285714285714285 percent. The average win was 8.078882384518149 percent and the average loss was 6.268481931598837 percent. The results match another system called vectorbt, with no fictional or missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native daily/hourly holdout trail0 slip20'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data. It keeps daily data even if hourly data is incomplete. The strategy uses specific rules, including a high and low price limit, a measure of price volatility called 2ATR14, and a fixed target for profits. It also credits fees of 25 basis points and has a 20-day time limit. The system checks for the next open timestamp and uses a trail of 2ATR if enabled. The strategy was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a return of -19.073088615771074, a drawdown of 31.45700301478701, and a win rate of 14.285714285714285. The average win was 21.396607216314088 and the average loss was 6.455758066153367. The results match another system called vectorbt with a high degree of accuracy. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native daily/hourly holdout trail0 slip10'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data it uses. The system retains daily data even if hourly data is incomplete. It uses specific rules to decide when to buy or sell, including a 20-day high and low, a 14-day average true range, which is a measure of how much prices move, and a fixed target of 10 basis points, which is a unit of measurement for interest rates and investment returns. The system also credits fees of 25 basis points and has a 20-day timeout. Additionally, it checks the next timestamp open and uses a 2RBE, or two times risk-based entry, and a 2ATR, or two times average true range, trail if enabled. The system was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a return of -17.93%, a drawdown of 30.77%, and a win rate of 14.29%. The average win was 21.64% and the average loss was 6.27%. The results match another system called vectorbt with a high degree of accuracy, and there are no missing hour fills, which refers to trades that are not actually executed. https://runway.adityaperswal.workers.dev/data/crypto-bars

A trading system for SOL/USD has a control that keeps daily data even if hourly data is incomplete. It uses a fixed target and checks for certain conditions. The system was trained from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a return of 33.72541027639792 percent, a drawdown of 26.285362300914105 percent, and a win rate of 44.44444444444444 percent. The system had an average win of 21.602333212054063 percent and an average loss of 9.073187976290205 percent. A news scan found the headline is not available, but the system's raw wealth returns match another system's returns at a very small difference of 1e-10. There were no missing hour fills that were not real. https://runway.adityaperswal.workers.dev/data/crypto-bars

A trading system has rules to control its decisions. It keeps daily data even if hourly data is incomplete. The system uses specific numbers to make decisions: a high and low price that does not change for 20 days, a 14-day average price movement, a fixed target of 3 times the recent price movement, fees of 25 basis points, and a 20-day time limit. It also checks the next day's opening price and can use a trailing stop loss. The system was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. A news scan found the headline is not available, but a data line shows the following results for the symbol SOL: it uses native full data, daily signals, and hourly execution, and it is currently training with a 10 basis point slip. The results are a return of 36.15%, a drawdown of 25.99%, and a win rate of 44.44%. The system had 9 samples with a mean of 4.77, an average win of 21.85, and an average loss of 8.89. There were 2 entries and 2 exits with zero volume. The wealth returns match another system called vectorbt with a small difference of 1e-10, and there are no missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native daily/hourly train trail0 slip20'. This is a report about a trading system for the cryptocurrency SOL, which is traded against the US dollar. Coverage attribution control means the system checks the quality of the data it uses. The system keeps daily data even if the hourly data for that day is incomplete. It uses a set of rules to decide when to buy or sell, including a high and low price that does not change, a measure of price volatility called 2ATR14, and a target profit of 10 basis points, which is 0.1 percent. The system also credits fees of 25 basis points, or 0.25 percent, and stops trading after 20 days. The system was trained using data from 2024 to 2025 and from January 1, 2026, to September 11, 2026. The results of the system are: symbol SOL, source native_full, signal daily, execution hourly, part train, trail false, slip_bp 20, return 25.568008276795574, drawdown 30.782038973833625, win rate 44.44444444444444, sample 9, mean 3.786572099285184, avg_win 19.86127219375442, avg_loss 9.073187976290205, zero_volume_entries 2, zero_volume_exits 2. The results match another system called vectorbt, with no fictional or missing hourly data. https://runway.adityaperswal.workers.dev/data/crypto-bars

A trading system for SOL/USD has a control that keeps daily data even if hourly data is incomplete. It uses a fixed set of rules, including a 20-day high and 10-day low, and a 14-day average true range, or ATR, which is a measure of price volatility. The system aims to make a 10 basis point, or 0.1%, profit, and charges a 25 basis point fee. It also has a 20-day timeout and checks the next timestamp open. If enabled, it uses a 2 ATR trail, which is a way to adjust the stop-loss price. The system was trained from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a 27.85% return, a 30.50% drawdown, and a 44.44% win rate, based on 9 samples. The average win was 20.10% and the average loss was 8.89%. There were 2 instances where the system entered or exited a trade with zero volume. The results match another system, called vectorbt, to a high degree of accuracy, with no fictional or missing hourly data fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native daily/daily holdout trail1 slip20'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data it uses. It keeps daily data even if some hourly data is missing. The strategy uses specific rules, including a high and low price threshold, a measure of price volatility called 2ATR14, and a fixed target profit of 10 basis points. It also credits fees of 25 basis points and has a 20-day time limit. Additionally, it checks the next timestamp open and uses a 2RBE entry and 2ATR trail if enabled. The strategy was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results show a return of -9.311181002529544, a drawdown of 32.40499103083096, and a win rate of 16.666666666666664. The average win was 26.811745604764138 and the average loss was 6.366803883101535. The results match another system called vectorbt with a high degree of accuracy, and there were no missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native daily/daily holdout trail1 slip10'. This refers to a trading strategy for the SOL/USD currency pair. Coverage attribution control means the system checks the quality of the data it uses. It keeps daily data even if the hourly data for that day is incomplete. The strategy uses specific rules, including a high and low price limit, a volatility measure called 2ATR14, and a fixed profit target of 10 basis points. It also credits fees of 25 basis points and has a 20-day timeout. Additionally, it checks the next timestamp open and uses a 2RBE entry and 2ATR trail if enabled. The strategy was trained on data from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026, with a holdout period. The results show a return of -8.216356812719727, a drawdown of 31.793786379107793, and a win rate of 16.666666666666664. The average win was 27.06562348160628 and the average loss was 6.179349661737919. The wealth returns match another system called vectorbt at a precision of 1e-10, and there are no fictitious missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars

A news scan found the headline 'SOL/USD C91104 full-native daily/daily holdout trail0 slip20'. Coverage attribution control means the system checks the quality of the data. It keeps the daily data even if the hourly data is incomplete. The system uses specific rules, including a high and low price limit, a measure of price volatility called 2ATR14, and a fixed target of 10 basis points. It also credits fees of 25 basis points and has a 20-day timeout. The system checks the next timestamp open and uses a 2RBE entry and 2ATR trail if enabled. The system was trained from 2024 to 2025 and reused from January 1, 2026, to September 11, 2026. The results for the symbol SOL are as follows: the signal and execution are daily, the system is in holdout mode, and the trail is false. The slip in basis points is 20. The return is -9.311181002529544, the drawdown is 32.40499103083096, and the win rate is 16.666666666666664. The sample size is 6, the mean is -0.837045635123923, the average win is 26.811745604764138, and the average loss is 6.366803883101535. There are no zero volume entries or exits. The wealth returns match the vectorbt results at a precision of 1e-10, and there are no fictitious missing hour fills. https://runway.adityaperswal.workers.dev/data/crypto-bars