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.
A news scan found the headline 'C91306 SOL hourly: delayed gross3R breakout control'. This refers to a trading strategy for the cryptocurrency SOL, where a 'gross3R' means a target return of three times the risk, and 'breakout control' is a method to manage risk. The strategy uses a'stop', which is a price level at which to sell a security, and a 'target', which is a price level at which to buy a security. The strategy also uses 'ATR20', which stands for Average True Range over 20 days, a measure of price volatility. Each training period starts with no existing positions, and the strategy uses a'reindex' to adjust the calendar and ensure there are no missing data points. The strategy freezes the ATR calculation, excluding the signal, at the start of each day, and only buys if the price exceeds the previous high. The strategy sells at the start of each hour if the price has exceeded the target, and includes a 'terminal close cost', which is the cost of closing a trade. The strategy also includes a 'coin buy fee' of 25 basis points, and a'sell fee' of 25 basis points plus a'slip' of 10 or 30 basis points, which is the difference between the expected and actual price of a trade. The results are summarized in arrays, including the window of time, delay in hours, slip in basis points, return percentage, drawdown percentage, win percentage, number of trades, and a 'half Kelly' measure, which is a formula to determine the optimal size of a trade. The results are as follows: for the training period, the return was 25.81%, the drawdown was 38.76%, and the win percentage was 54.55%, and for the holdout period, the return was 4.70%, the drawdown was 22.48%, and the win percentage was 50%. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the headline 'C91306 ETH hourly: delayed gross3R breakout control'. This refers to a trading strategy for Ethereum, a cryptocurrency. The strategy uses a 'gross3R breakout control', which means it aims to make a return of three times the risk taken. The strategy is backtested on historical data from 2024 to 2025, and evaluated on data from 2026. Each test starts with no existing position, and uses a'stop' based on the average true range of the price over the last 20 days. The strategy targets a return of three times the risk taken, and exits positions at the hourly open price if the price overshoots the target. The results are summarized in arrays, which include the window of time, delay hours, slip in basis points, return percentage, drawdown percentage, win percentage, number of trades, and a metric called 'half Kelly'. The arrays show the results for different combinations of these parameters. The strategy is not authorized for live trading, and is compared to a separate 15-minute manager that uses the same policy. The results are also compared to a 'net3R' target, which is not the same as the 'gross3R' target used here. A 'net3R' target would be a return of three times the risk taken, after fees and other costs. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the headline about a Bitcoin trading strategy. The strategy had predeclared HIGH480 false-to-true events, which means it looked for specific price movements, 2 prior daily Average True Range, or ATR, which is a measure of price volatility, 20 stop, gross 3R target, which means the strategy aimed to make three times the risk, and 20-day exit. Each training period from 2024 to 2025, and a known holdout period from January 1, 2026, to September 12, 2026, started with no existing positions, had a warm-up period in 2023, and used a full calendar reindex with no missing bar signals. The strategy used a freeze on Average True Range excluding signal on UTC day, and a delayed open that must exceed the frozen high. It exited at hourly opens with overshoot, and terminal close was costed, meaning it included all fees. The strategy credited 25 basis points for coin buy fees, and 25 basis points for sell, plus 10 or 30 basis points for slippage, which is the difference between expected and actual trade prices. The results were reconciled using vectorbt from orders final cash, which is a method to calculate the final cash balance, and the difference was less than 1e−5, which is a very small number. The summary arrays showed the results for different scenarios, including window, delay hours, slip basis points, return percentage, drawdown percentage, win percentage, number of trades, and half Kelly, which is a measure of the optimal bet size. The results were: [[
Diagnostic C91306 is a test with 60 predeclared cells. It looks for a false-to-true close above prior 20 calendar day highs on a daily basis or 480 hour highs on an hourly basis. The training period is from 2024 to 2025, and the known period is from January 1, 2026, to September 12, 2026, with a warm-up period in 2023. The system freezes the Average True Range (ATR) over 20 periods, excluding signal times on UTC days, and enters at the next open or delays entry. If the delayed open is less than or equal to the frozen high, the entry is cancelled. The stop entry is set at -2 ATR, the target entry at +6 ATR, and the time limit is 20 days. The system checks at each sampled open and charges for gap overshoots and terminal close costs. The gross 3R target is not the same as the net 3R or the mandated quarterly/BE policy, and this is not a live authorization. The system credits 25 basis points for coin buy fees, 25 basis points for sell fees, and 10/30 basis points for slippage, with a custom order ledger that reconciles to less than 1e-5. There is no fill-forward for missing prices in signals, and the calendar is reindexed. The SOL training is incomplete. The results are as follows: there are seven sets of results with different parameters, including return, drawdown, win rate, sample size, mean trade percentage, half Kelly fraction, skipped entries, days, symbol, time frame, delay, slippage in basis points, and window. The models ignore historical quotes, depth, and vintages, and idealize bar-open execution. The data comes from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A diagnostic report C91306 was generated with 60 predeclared cells. The report indicates a fresh false-to-true close above prior 20 calendar day highs on a daily basis or 480 hour highs on an hourly basis. The training period is from 2024 to 2025, and the known holdout period is from January 1, 2026, to September 12, 2026. Each period starts with a flat position. The report also mentions a warm-up period in 2023. The trading strategy involves freezing the Average True Range (ATR) 20, excluding signal UTC day, and entering at the next open or delaying entry. If the delayed open is less than or equal to the frozen high, the entry is cancelled. The stop entry is set at -2 ATR, and the target entry is set at +6 ATR, with a time limit of 20 days. The report checks for these conditions at each sampled open and charges for gap overshoots and terminal close costs. The gross 3R target is not the same as the net 3R or mandated quarter/BE policy, and this is not a live authorization. The report also mentions a 25 basis point buy fee and a 25 basis point sell fee, with a 10/30 basis point slippage. The custom order ledger reconciles with a final cash value of less than 1e-5. There is no fill-forward missing prices for signals, and the calendar is reindexed. The SOL training is incomplete. The report includes a list of results for different scenarios, including returns, drawdowns, win rates, and mean trade percentages. The results are for the symbol ETH, with a time frame of 1 day, and different delays and slippage values. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A diagnostic report, labeled C91306, analyzed 60 cells of data. The report looked for instances where the closing price was higher than the highest price in the previous 20 calendar days or 480 hours. The training period was from 2024 to 2025, and the known period was from January 1, 2026, to September 12, 2026. Each period started with no prior knowledge, and there was a warm-up period in 2023. The report used a method called ATR20, which stands for Average True Range over 20 periods, excluding signal times on UTC days. Entries were made at the next open or delayed, and delayed opens were canceled if they were less than or equal to the frozen high. The stop entry was set at 2 ATRs below the entry point, and the target entry was set at 6 ATRs above the entry point, with a time limit of 20 days. The report checked for these conditions at each sampled open and accounted for gap overshoots and terminal close costs. The target was a gross 3R, which means a three times return, not a net 3R, and it did not follow a mandated quarter or best efforts policy. This was not a live authorization. The report included a 25 basis point buy fee and a 25 basis point sell fee, with a 10 to 30 basis point slippage. The results were as follows: a list of trading results for Bitcoin, including return, drawdown, win rate, sample size, mean trade percentage, half Kelly fraction, skipped entries, days, symbol, time frame, delay, slippage in basis points, and window. The results showed varying returns and drawdowns for different scenarios. The data source was https://runway.adityaperswal.workers.dev/data/crypto-bars, and the documentation for crypto fees was https://docs.alpaca.markets/us/docs/crypto-fees. The models ignored historical quotes, depth, and vintages, and idealized bar-open execution. A separate experiment compared the 15-minute manager.
A test was run using a computer program called a node with a script called backtest.js. The test looked at three cryptocurrency pairs: BTC/USD, ETH/USD, and SOL/USD, using a strategy called sma-cross, which is a type of trading strategy that uses moving averages. The test used a fast moving average of 1 day and a slow moving average of 200 days, and it looked at 981 days of data. The results were: for BTC/USD, a gross return of 14.4761, a maximum drawdown of 31.2332, a win rate of 15.3846, and 13 closed trades; for ETH/USD, a gross return of 10.7680, a maximum drawdown of 37.8551, a win rate of 11.1111, and 9 closed trades; and for SOL/USD, a gross return of 8.3228, a maximum drawdown of 32.9545, a win rate of 0, and 3 closed trades. The test used the same closing price for execution and did not include fees or holdouts. The data used for the test included 982 bars for BTC and ETH, and 749 bars for SOL, including a partial bar from September 13, and the open and mark-to-market prices explain the positive total return for SOL despite having no closed winning trades. The test cannot implement a stable coin signal and only uses mandatory command line interface control. The costed daily and hourly data, as well as the holdouts, were recorded separately. There were no orders or choices made from the gross output. The data source is https://runway.adityaperswal.workers.dev/data/crypto-bars.
A news scan found the text describing a trading strategy for the cryptocurrency SOL. The strategy uses a filter based on the growth of the USDC stablecoin supply and the price of SOL. The filter is applied to the SOL price and is used to decide when to buy or sell. The strategy is tested on historical data from 2024 to 2025 and is evaluated on its performance during the period from January 1, 2026, to September 12, 2026. The results show that the strategy had a return of -11.006206% during the training period and 5.433297% during the evaluation period. The strategy also had a maximum drawdown of 34.649737% during the training period and 10.758956% during the evaluation period. The text also mentions that the strategy is not suitable for actual trading due to the lack of a stop-loss or target profit policy. The data used for the strategy is sourced from several websites, including https://runway.adityaperswal.workers.dev/data/crypto-bars, https://stablecoins.llama.fi/stablecoin/2, https://stablecoins.llama.fi/stablecoin/1, and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the headline 'C91304 SOL 1Day: stablecoin filter versus price-only control'. This refers to a test of a trading strategy for the cryptocurrency SOL. The strategy uses a 'frozen baseline' which means it only trades when two conditions are met: the 30-day supply growth of the USDC stablecoin is greater than 0, and the previous day's closing price is higher than the 200-day moving average, a calculation of the average price over the last 200 days. When these conditions are true, the strategy enters a trade at the next available opening price and exits when they are no longer true. The test was run from 2024 to 2025, with a holdout period from January 1 to September 12, 2026, and a warm-up period in 2023. The results showed a return of -11.006206% during the training period, with a maximum drawdown of 33.249904%, and no winning trades. In the holdout period, the return was 5.433297%, with a maximum drawdown of 9.663307%, and 100% winning trades. A control strategy that only looks at price movements had a return of 18.366768% in the holdout period. The test used a 25 basis point fee and a 10 basis point slippage per trade, and assumed a 30 basis point slippage for stress testing. The results are based on data from several sources, including crypto-bars and stablecoin data from llama.fi, and crypto fees from Alpaca markets.
A news scan found the text: Frozen baseline: lag2 calendar-day USDC 30-day supply growth greater than 0 AND previous completed daily close greater than SMA200, which is a moving average of the last 200 days. Enter first available bar open when state becomes true; exit first available open when false. Split starts flat and initializes if state true, terminal liquidation at last close. Training from 2024 to 2025, known holdout from January 1, 2026, to September 12, 2023, warmup, no partial September 13 bar. Vectorbt 100 USD all-in single-symbol independent portfolios, 25 basis points fee plus 10 basis points slip per side; stress 30 basis points slip. Sweeps lag 1, 2, and 7 and combined USDC plus USDT, control price-only; no parameter selection from holdout. Baseline training return 75.031958 percent, drawdown 35.057611 percent, win 33.333 percent, number of trades 9; holdout return 3.666842 percent, drawdown 6.462538 percent, win 100.000 percent, number of trades 2. Price-only holdout 11.301377 percent, number of trades 1. Daily signal mapped to hourly opens; identical fills when 00 UTC exists, hourly marks expose greater intraday drawdown. This is not independent replication or an hourly supply series. Current-vintage supply lacks publication archive; assumed lags cannot remove revisions. Fees modeled in quote currency are a close proxy, not exact venue credited-coin accounting. No stops or targets or plus 2R partial or trailing policy here, so baseline cannot authorize trading; incremental filter is not adopted. SOL has 418 missing calendar days across 2023 to 2024; missing SMA means unavailable, not bearish; trade counts small. Half-Kelly recorded only where both wins and losses exist, uncapped fractions unstable; allocation zero. All 28 cells recorded separately in observations. Sources https://runway.adityaperswal.workers.dev/data/crypto-bars; https://stablecoins.llama.fi/stablecoin/2; https://stablecoins.llama.fi/stablecoin/1; https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the text describing a trading strategy for Ethereum. The strategy has a baseline that freezes when two conditions are met: the 30-day supply growth of the USDC stablecoin, which is a type of cryptocurrency pegged to the US dollar, is greater than 0, and the previous day's closing price is greater than the 200-day simple moving average, which is a calculation of the average price over 200 days. When these conditions are true, the strategy enters a trade at the next available opening price and exits when the conditions are no longer true. The strategy was trained on data from 2024 to 2025 and tested on data from January 1 to September 12, 2026. The results showed a return of 75.031958% during training, with a maximum drawdown of 33.073196% and a win rate of 33.333%. During the test period, the return was 3.666842% with a maximum drawdown of 4.774546% and a win rate of 100%. A control strategy that only considers price movements had a return of 11.301377% during the test period. The strategy uses a 25 basis point fee, which is a type of transaction cost, and a 10 basis point slippage, which is the difference between the expected and actual price of a trade. The results are based on data from several sources, including https://runway.adityaperswal.workers.dev/data/crypto-bars, https://stablecoins.llama.fi/stablecoin/2, https://stablecoins.llama.fi/stablecoin/1, and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the text describing a trading strategy for Bitcoin. The strategy uses a filter based on the growth of a stablecoin, USDC, and its 30-day supply. The filter is combined with a price-only control. The strategy enters a trade when the filter is true and exits when it is false. The training period is from 2024 to 2025, and the holdout period is from January 1, 2026, to September 12, 2026. The warm-up period is in 2023. The strategy uses a 25 basis point fee and a 10 basis point slippage per side. The results show a return of 30.157692% during training, with a drawdown of 36.117294% and a win rate of 27.778%. In the holdout period, the return is -2.140782%, with a drawdown of 6.395037% and a win rate of 50.000%. The price-only control has a return of 10.679989% in the holdout period. The strategy uses a daily signal mapped to hourly opens. The fees are modeled in the quote currency, which is a close approximation but not exact. The strategy does not use stops, targets, or a trailing policy. The data sources are listed as https://runway.adityaperswal.workers.dev/data/crypto-bars, https://stablecoins.llama.fi/stablecoin/2, https://stablecoins.llama.fi/stablecoin/1, and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the text describing a trading strategy for Bitcoin. The strategy uses a filter based on stablecoin supply growth and price trends. It buys when the 30-day supply growth of USDC is increasing and the previous day's close is above the 200-day moving average. The strategy sells when these conditions are no longer met. The training period was from 2024 to 2025, and the test period was from January 1, 2026, to September 12, 2026. The strategy was tested with a 25 basis point fee and a 10 basis point slippage per trade. The results showed a 30.16% return during training, with a maximum drawdown of 33.91% and a win rate of 27.78%. In the test period, the return was -2.14%, with a maximum drawdown of 5.82% and a win rate of 50%. A price-only control strategy had a 10.68% return during the test period. The strategy uses data from sources including https://runway.adityaperswal.workers.dev/data/crypto-bars, https://stablecoins.llama.fi/stablecoin/2, https://stablecoins.llama.fi/stablecoin/1, and https://docs.alpaca.markets/us/docs/crypto-fees.
A computer program ran a test on a set of rules for buying and selling cryptocurrencies, which are digital currencies like Bitcoin. The test, called a backtest, looked at the prices of seven cryptocurrencies: Bitcoin, Ethereum, Solana, Litecoin, Ripple, Hype, and Link. The test used a strategy called breakout, which means buying when the price goes above a certain level, and looked at the prices over 981 days. The results showed the return on investment, the biggest loss, the percentage of winning trades, and the number of trades that were closed for each cryptocurrency. The results were: Bitcoin had a return of 46.4608% with a biggest loss of 14.6924% and 34.328% of trades were winning, with 67 trades closed; Ethereum had a return of 41.4426% with a biggest loss of 24.9433% and 32.727% of trades were winning, with 55 trades closed; Solana had a return of 72.1517% with a biggest loss of 18.7954% and 52.778% of trades were winning, with 36 trades closed; Litecoin had a return of -17.5515% with a biggest loss of 47.2206% and 27.083% of trades were winning, with 48 trades closed; Ripple had a return of 476.5253% with a biggest loss of 19.9595% and 47.059% of trades were winning, with 34 trades closed; Hype had a return of -1.6918% with a biggest loss of 19.2206% and 29.412% of trades were winning, with 17 trades closed; and Link had a return of -22.5658% with a biggest loss of 44.6927% and 34.545% of trades were winning, with 55 trades closed. A closer look at the data confirmed that the test used the closing price from the day before and executed trades at the same closing price, without any fees or holding back some of the data for testing. However, these results do not confirm that the rules for buying and selling, called HIGH20/LOW10, or the managed pullback execution, which is a way of selling when the price pulls back, are valid. Another study with 156 data points provides more detailed controls and holds out some of the data for testing, but Hype was not included in the training data. No parameters were selected from this test and no orders were placed. The data came from https://runway.adityaperswal.workers.dev/data/crypto-bars and all the raw data is recorded in observations 26628-26841.
This is a description of a trading strategy for the LINK cryptocurrency. The strategy uses a fixed Donchian system, which is a type of trading system that uses recent highs and lows to make decisions, with a 20-day high entry point and a 10-day low exit point at the next open. The system looks at 480 and 240 hours of data, but ignores any missing hours and only considers prices before September 13, 2022, at 02:00 UTC, excluding the incomplete data from that day. The system also takes into account a buy fee equivalent to 0.0025 and a sell fee of 25 basis points, with a 10 basis point slip and a 30 basis point stress test. The results of the training from 2024 to 2025 show a return of 0.296718%, a maximum drawdown of 52.438495%, 12 closed trades, and a win rate of 33.333%. The results of the reset in 2026 show a return of -1.201527%, a maximum drawdown of 24.551662%, 4 closed trades, and a win rate of 50.000%, with a stress return of -2.963609%. The system recorded sensitivities for 15, 20, and 30 days, but did not select the best parameters. The data used is not entirely new and untouched. The return includes open marked positions, and the win rate only considers closed trades, without assuming a final fill. This strategy does not require a 2 ATR stop, 3R target, quarter at 2R, or 15-minute exit management, so it is not a live policy validation. There were no fresh high entries across 7 periods, and no late entries. The data sources are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The experiment involved 156 cells and 26910 to 27075 observations, with a current top 10 survivor selection that limits generalization.
The C91302 LINK daily costed HIGH20 LOW10 control uses a fixed Donchian strategy, which is a type of trading strategy that uses prior highs and lows to make decisions, with a prior 20 calendar-day high for entry and prior 10-day low for exit at the next exact open, over a period of 20 and 10 days. This strategy requires 24 hours a day of OHLC, which stands for Open, High, Low, Close, and only considers prices before September 13, 02:00 UTC, excluding the incomplete September 13 day. The Vectorbt, a backtesting and trading platform, credited a coin buy fee equivalent to 0.0025 and 0.9975, and a sell fee of 25 basis points, with a slip of 10 basis points and 30 basis points stress. The training from 2024 to 2025 had a return of -39.654890%, a drawdown of 56.876500%, with 11 closed trades, a win rate of 36.364%, and no open trades. The reset in 2026 had a return of 27.044492%, a drawdown of 14.403432%, with 2 closed trades, a win rate of 50.000%, and 1 open trade, with a stress return of 25.780875%. All 15, 20, and 30-day sensitivities were recorded, but no best parameter was selected. The calendar holdout is not newly untouched data. The return includes open marked positions, and the win rate is only for closed trades, with no assumed final fill. This control does not require a 2 ATR stop, 3R target, quarter at 2R, or 15-minute exit management, so it is not a live policy validation. There was no fresh high entry across 7, and no late entry. The data source is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The experiment had 156 cells and 26910 to 27075 observations, with the current top 10 survivor selection limiting generalization. A news scan found the source of this information.
The C91302 HYPE hourly costed HIGH20 LOW10 control uses a fixed Donchian strategy, which is a type of trading strategy that uses prior highs and lows to determine entry and exit points, with a prior 20 calendar-day high for entry and prior 10-day low for exit at the next exact open, over 480 and 240 hours. The data is incomplete, with missing calendar hours and prices before September 13, 2022, at 02 UTC, and the incomplete September 13 day is excluded. The Vectorbt, a backtesting and trading library, is credited with a coin buy fee equivalent to 0.0025 and 0.9975, and a sell fee of 25 basis points, with a slip of 10 basis points and 30 basis points stress. The training data from 2024 to 2025 is unavailable. The reset in 2026 showed a known and reused holdout return of 56.037399%, a drawdown of 31.948567%, with 4 closed trades and a win rate of 75.000%, and 0 open trades, and a stress return of 53.560657%. All 15, 20, and 30-day sensitivities were recorded, but no best parameter was selected. The HYPE starts on February 17, 2026, and the positive 2026 results are in-sample descriptive, meaning they are based on the same data used to train the model, with no pre-2026 training or valid out-of-sample data. The return includes the open marked position, and the win rate is based on closed trades only, with no assumed final fill. This control does not require a 2 ATR stop, 3R target, quarter at 2R, or 15-minute exit management, so it is not a live policy validation. There is no fresh high entry absent across 7, and no late entry. The data source is from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The experiment has 156 cells and 26910 to 27075 observations, and the current top 10 survivor selection limits generalization.
The C91302 HYPE daily control uses a fixed Donchian strategy, which is a type of trading strategy that uses the highest high and lowest low of a certain period, in this case, the prior 20 calendar-day high for entry and prior 10-day low for exit at the next exact open, over a period of 20 and 10 days. This strategy requires 24 hours a day of open, high, low, and close prices, known as OHLC, and only considers prices before September 13, 2022, at 02 UTC, excluding the incomplete day of September 13. The Vectorbt system is used to credit a coin buy fee equivalent to 0.0025 and 0.9975, and a sell fee of 25 basis points, with a 10 basis point and 30 basis point stress slip. Training data from 2024 to 2025 is unavailable. The reset in 2026 resulted in a known and reused holdout return of 37.837008%, a drawdown of 30.053656%, with 3 closed trades and a win rate of 66.667%, and no open trades, and a stress return of 36.192841%. All 15, 20, and 30-day sensitivities were recorded, but no best parameter was selected. The HYPE strategy started on February 17, 2026, and the positive results in 2026 are considered in-sample and descriptive, with no pre-2026 training or valid out-of-sample data. The return includes the open marked position, and the win rate is only for closed trades, with no assumed final fill. This control does not require a 2 ATR stop, 3R target, quarter at 2R, or 15-minute exit management, so it is not a live policy validation. There were no fresh high entries across 7 periods, and no late entries. The data source is from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The experiment had 156 cells with observations from 26910 to 27075, and the current top 10 survivor selection limits generalization.