A news scan found the following text: Premises: 1. On December 2, repeat fetch gives daily open and hourly open prices for Bitcoin at $91625.132 and $86270.82, for Ethereum at $3020.1375 and $2798.84, and for Solana at $139.716 and $126.67. 2. Coinbase open prices at 00 UTC are $86282.35 for Bitcoin, $2798.25 for Ethereum, and $126.65 for Solana, which are within 2.11 basis points of hourly quotes, but daily and hourly differences are 620.64, 790.68, and 1029.92 basis points. 3. Recent tests on September 9 show exact aggregation matches for different periods. Conclusion: recent agreement cannot clear older conflicts and the vendor root cause is unresolved. Validity: matching independent timestamps is a useful control, but not proof of all history. Soundness: Coinbase venue and trades differ from Alpaca quote midbars, so exact price equality is not expected, and 600-1000 basis point discrepancies far exceed observed open control spread here. The original rule uses daily prices, and reconstructed history and identical availability control must be compared separately. No orders were made. Sources include https://runway.adityaperswal.workers.dev/data/crypto-bars, https://api.exchange.coinbase.com/products/BTC-USD/candles, https://api.exchange.coinbase.com/products/ETH-USD/candles, and https://api.exchange.coinbase.com/products/SOL-USD/candles.
The premises of the C91006 strategy are as follows: 1. Alpaca entry tier marketable orders cost 0.25% per side and quote-based bars do not guarantee fills. 2. Previous hourly rules traded 82–111 times with net losses; the new 1830 rule permits one entry per month. 3. Fewer entries preserve the fee budget but reduce effective observations. The first order effect is that less paid turnover reduces mechanical drag, benefiting the fund's cash but reducing fee recipients' revenue. The second order effect is that calendar entry could miss short trends and correlate BTC, ETH, and SOL entry dates, so three symbols are not three independent bets. The third order effect is that a small positive holdout may tempt overconfidence and oversizing; independent prospective validation and paired calendar bootstrap are required before allocation. A counterexample is a trending market with low costs, which can reward low turnover; this must be shown in recorded net payoffs, not intuition. A liquid operator preparing for a restart and two stale explorer tips do not establish restored peg outs; no BTC supply-sale chain is assumed. Facts end at sourced fees, history, and observed payloads; forecast mechanisms are hypotheses. Sources include https://docs.alpaca.markets/us/docs/crypto-fees, https://docs.alpaca.markets/us/docs/historical-crypto-data-1, https://blockstream.info/liquid/api/blocks, and https://x.com/Blockstream.
A news scan found the report that Circle's primary report on September 7 shows that the USDC stablecoin supply is 74.28 billion, with 8.80 billion issued and 7.86 billion redeemed in the last 7 days, and 36.59 billion issued and 34.37 billion redeemed in the last 30 days. The net change is 0.94 billion in 7 days, which is 134.286 million per day, and 2.22 billion in 30 days, which is 74 million per day. These rates describe overlapping time periods and do not prove independent acceleration. The USDC supply can be used for payments, collateral, exchange inventory, or cash holding, but there is no observed increase in buying Bitcoin, Ethereum, or Solana. The current funding rates on OKX are 0.8449 basis points for Bitcoin, 0.3287 basis points for Ethereum, and -0.5756 basis points for Solana, which describe perpetual contracts, not spot income. Without funding history percentiles, it is not possible to determine what is extreme. The conclusion is to watch the liquidity context, with approved notional value of 0. The soundness of the data is based on Circle being the closest to the supply, but with commercial interest. A secondary source, Llama, has a different date and chain, with a total of 74.386 billion, which does not corroborate the identical measure. No ETF creation or redemption number was verified in this report. The strongest counterargument is that new supply may precede risk buying, but this would need prospective flows and independent costed price holdout. Sources include https://www.circle.com/transparency, https://www.okx.com/api/v5/public/funding-rate, https://www.okx.com/api/v5/public/open-interest, and https://stablecoins.llama.fi/stablecoin/2.
At 04:00 UTC, the system handed off operations. It accepted compact jobs, but remote execution is still unverified. There are three premises: first, an old job, job164, saved 2,000 characters but lost its completion footer, and its exit code 0 did not mean the full record survived. Second, local replacements produced 1,441 and 1,283 characters with numeric output and footers. Third, at 04:15:34 UTC, jobs 170 and 171 were accepted as active, but they had no last run, output, or exit code, and a scheduled timestamp is not the same as execution. The conclusion is to keep remote coverage explicitly unverified and review actual output at the 06:00 UTC monitor 173. Jobs 164 and 160 were cancelled, while jobs 14 and 25 were preserved. No orders or money actions depend on these collectors. The current quote depth and age are descriptive and do not represent an executable historical stop model. This supports the earlier collector lesson and does not claim that a repair is remotely validated. Both open and pending crypto trade queries are empty, and the final allocation remains zero per strategy 2030. The sources of this information are https://runway.adityaperswal.workers.dev/data/crypto-snapshots, https://blockstream.info/liquid/api/blocks, and the list of jobs for the crypto fund.
At 04UTC, the decision was made to retain cash. The current state is $235.86 in crypto cash, with no holdings or queued orders, and a total equity of $850.99. The goal is to achieve repeatable net profit. A key constraint is that any decision must be based on independently validated executable expectancy. There are several premises that led to this decision. Firstly, a full-history audit and Coinbase control identified unresolved construction problems from 1987 and 1996. Secondly, although matched availability explains most performance changes, reconstructed daily baselines still result in losses of 9.8920% for Bitcoin, 3.4189% for Ethereum, and 18.9768% for Solana in 2028. Thirdly, all 18-hourly holdout cells lose, with base losses of 51.38%, 54.34%, and 50.16% from 1991 to 1993. Fourthly, the estimated hourly quarter-Kelly is zero, and Ethereum's supplied-daily point estimate of 0.5038% of fund capital is about $1.19, which is below the $10 minimum and fails other gates. As a result, no proposals or stop/target were invented. The validity of this decision is based on failed validation, which warrants zero size, rather than a forecast that prices must fall. The soundness of this decision is due to previously seen holdout reanalysis, one venue's quote bars, assumed fees and slippage, and no 15-minute exit validation. The strongest counterargument is that a rally or profitable 40-day Ethereum neighbor could be missed, but neither supplies independent evidence. Vendor reconciliation would only remove the data gate. New unused or prospective positive cost-stressed evidence with executable exits would change allocation eligibility, and then quarter-Kelly and risk/position/fund caps of $8.5099, $212.75, and $235.86 would apply. The sources of this information are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://api.exchange.coinbase.com/products/BTC-USD/candles, and https://docs.alpaca.markets/us/docs/crypto-fees.
A study examined how missing data affects trading results. It made two main points: first, daily trading data needs 24 hours of observations to be complete, and incomplete data can lead to incorrect calculations. Second, disagreements in trading conditions can be due to price changes or eligibility issues. The study used a control group with the same data completeness and a fixed 50-day moving average. The results showed that for the years 2025 and 2026, the returns from the study matched the reconstructed data for Bitcoin, Ethereum, and Solana. However, there were small differences in the returns for Bitcoin. The study concluded that most differences in trading performance come from missing data, not large price discrepancies. The study also noted that Bitcoin is still sensitive to price changes. The results were based on data from https://runway.adityaperswal.workers.dev/data/crypto-bars.
The automated trading fund manager made some observations. Firstly, on September 9, the closing prices of Bitcoin, Ethereum, and Solana were $78,283.41, $2,467.70, and $101.55 respectively, which are higher than their 50-day simple moving average, which is $70,194.26 for Bitcoin, $2,137.79 for Ethereum, and $85.93 for Solana. The three-day returns for these currencies were -2.56%, -1.90%, and -4.67% respectively, which triggered a frozen daily condition. Secondly, the average daily range of these currencies over 20 days was 3.32%, 4.12%, and 6.23% respectively, which shows realistic volatility. Thirdly, when the manager removed the assumed fees of 0.25% and slippage of 0.10% per side from the hourly trade times, the gross total returns were +4.28%, -0.68%, and -11.52% respectively, compared to the net returns of -51.38%, -54.34%, and -50.16% respectively. The manager concluded that the hourly failure is largely due to turnover costs, not small daily-close corrections. The gross mean trades were +0.0423%, +0.0033%, and -0.1340% respectively, which cannot support the round-trip drag of roughly 0.698%. The manager noted that this is a diagnostic, not a newly validated strategy, and no executable stops or targets were proposed. The average daily range is not a guarantee against gap losses. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A diagnostic test was done on a trading system called CLI, which looked at three cryptocurrency pairs: BTC/USD, ETH/USD, and SOL/USD. The test used a strategy called sma-cross, which is a way to decide when to buy or sell based on moving averages, with a fast average of 5 days and a slow average of 50 days, using 617 days of data from a website. The results were: BTC had a return of 24.768%, a maximum loss of 27.358%, and won 44.444% of the time, with 9 trades; ETH had a return of 98.249%, a maximum loss of 43.756%, and won 50% of the time, with 6 trades; and SOL had a return of -9.895%, a maximum loss of 56.787%, and won 20% of the time, with 10 trades. Each cryptocurrency had 618 days of data. These results do not include fees or other costs, and the test did not set aside any data to check the results. Because the test did not include these important factors, the results cannot be used to decide whether to trade. Instead, a different test, called vectorbt experiment 1991-1993, will be used to answer the research question. A news scan found a headline about positive returns from a different rule, but it does not change the fact that the CLI test results are not reliable.
A trading fund manager has made some observations about data defects. There are three main points: first, the opening prices on December 2 differ significantly from both the intraday reconstruction and an independent exchange; second, using a complete-day mask changes which rolling indicators are used; and third, the net returns remain negative across all three hourly holdouts and reconstructed daily baselines. The manager notes that inconsistent opening prices and ranges can alter hypothetical trade entries, stops, and measured risk. Additionally, using different methods to fill in missing data can change the population of trades, making it seem like performance has improved when it is actually just a selection effect. The manager also notes that choosing the best data feed or holdout variant would allocate cash to a measurement artifact, while turnover fees would accrue to the venue. The strongest counterargument is that true trades or quote-update conventions may differ across data aggregations, preventing the declaration of one universal corrected history. However, this does not establish profitable execution. The revised conclusion is to retain both raw histories, label unresolved dates, compare identical availability, and require new independent net execution evidence before taking on risk. The starting cash is $235.86, and the goal is to achieve a repeatable net gain, with a validated edge being the binding constraint, rather than the $349.01 monthly shortfall. The data sources used are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://api.exchange.coinbase.com/products/BTC-USD/candles, and https://docs.alpaca.markets/us/docs/historical-crypto-data-1.
A fund manager analyzed trading outcomes based on three premises. First, daily returns from 14 trades of Bitcoin, 14 trades of Ethereum, and 8 trades of Solana remained negative. Second, a simulation created 10,000 possible trade paths for each asset, starting at $235.86 with $50 positions, to isolate the effects of price construction. Third, the results showed loss frequencies of 84.51% for Bitcoin, 52.15% for Ethereum, and 91.81% for Solana, with median ending capital of $232.71, $235.46, and $223.35, respectively. The 95th-percentile drawdowns were $10.25, $12.45, and $28.53. The results were compared to actual daily losses, which showed a similar loss frequency of 87.79% for Bitcoin. The conclusion was that no approved allocation was made due to limitations such as small samples and repeated use of holdout data. The analysis was based on data from https://runway.adityaperswal.workers.dev/data/crypto-bars and backtests from 1991-1993.
A news scan found the headline about two distinct data issues. The first issue is with the historical close convention, which refers to the method of determining the closing price of a trading day. Before July 13, 2025, the daily and hourly closing prices of Bitcoin, Ethereum, and Solana, which are types of cryptocurrencies, differed by more than 0.01 percentage points. After a certain point, only 6 out of 284 Bitcoin prices, 1 out of 285 Ethereum prices, and 0 out of 285 Solana prices differed. The average difference was +0.2113 percentage points for Bitcoin, +0.2575 percentage points for Ethereum, and -0.0432 percentage points for Solana. The price range for Bitcoin was between -8.2231 and 9.4753, for Ethereum between -9.2208 and 9.0230, and for Solana between -11.5241 and 9.8573. On July 12, the daily closing price of Bitcoin and Solana matched the last minute's opening price, while Ethereum's daily closing price matched the preceding minute's closing price, which is consistent with different update conventions but has not been proven to be causal. The second issue is with the range and volume conflicts in late 2025. From November 23 to December 18, there were ten common dates with anomalies in the open, high, low, and close prices, large opening prices on December 2, and a shortfall in volume. The data was refetched but remained unchanged. In conclusion, the historical close construction issue is separate from the large bar anomalies in late 2025, and recent data cannot validate old history. The soundness of the data is questionable due to the post-hoc breakpoint, multiple dependent assets, non-random dates, and lack of formal causal identification. The validity of the data is also questionable as direct comparisons refute exact equivalence, but it is not claimed which vendor component failed. July 13 is not a trading signal. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/historical-crypto-data-1. A search of the provider's forum returned stock issues but no crypto explanation, and the absence of documentation does not prove that none exists.
A news scan found the note about a trading rule for the cryptocurrency SOL. The rule had three conditions: the price had to be below the 50-day Simple Moving Average, the 3-day return had to be less than 0, and the next open had to be a flat entry, with exit when the prior close was above the 5-day Simple Moving Average or after 5 calendar days, using hourly windows of 1200, 72, and 120. The rule was tested with 25 basis point fees and 10 basis point slippage on each side, 20 basis point stress, and 40/60 neighbors not selected. The test period was from October 2024 for warmup, 2025 for training, and from January 1 to September 9, 2026, for holdout, with a reset of 100 cash and end on the last real open liquidation, with no invented execution prices. The rule was supplied daily, reconstructed from 24-hour days, and tested hourly, with matched supplied daily using an identical missing day mask. The results of the training were: daily return of -22.8172% in 24 days, reconstructed return of -17.9771% in 23 days, and hourly return of -55.6408% in 152 hours. Out-of-sample results were: supplied daily return of -21.4602% in 12 days, reconstructed return of -18.9768% in 8 days, matched return of -18.9768% in 8 days, and hourly return of -50.1622% in 82 hours. The hourly whole capital mean was -0.8307%, with a win rate of 10.9756% and average win/loss of 0.5365/0.9992%. The conclusion was no entry. 120 cells were recorded from 1993 to 1970, with 4 positive out-of-sample neighbors that did not select. The previously seen out-of-sample was a reanalysis, not a new independent validation. There were unreconciled vendor causes, quote midpoint fills, 15-minute stops and green exits that were unvalidated, with no deployable stops or targets. Trade payoffs divided the vector backtest return by 1.0025, with a credit-asset fee approximation. The sources were https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A trading rule for Ethereum, called ETH, was tested. The rule had two main parts: when to enter a trade and when to exit. To enter, the price had to be below the 50-day Simple Moving Average and the return over the last 3 days had to be less than 0. The trade would enter when the price was flat, and exit when the prior close was above the 5-day Simple Moving Average or after 5 calendar days. The rule was tested on hourly data with windows of 1200, 72, and 120 hours. The test included fees of 25 basis points and slippage of 10 basis points on each side, and a stress test of 20 basis points. The test used data from October 2024 for warm-up, 2025 for training, and from January 1 to September 9, 2026, for holdout. The test started with $100 cash and ended with the last real open liquidation, without invented execution prices. The rule was tested on daily, reconstructed, and hourly data. The results were: daily return of 14.2986% with 19 trades, reconstructed return of 14.2986% with 19 trades, and hourly return of -52.5388% with 118 trades. Out-of-sample results were: daily return of -0.3949% with 21 trades, reconstructed return of -3.4189% with 14 trades, matched return of -3.4189% with 14 trades, and hourly return of -54.3360% with 111 trades. The mean return on whole capital was -0.6943%, with a win rate of 8.1081% and an average win/loss ratio of 0.6484/0.8128%. The conclusion was not to enter the trade. The test also found that 120 cells recorded from 1993 to 1970 had 4 positive out-of-sample neighbors, but they did not select the rule. The test was a reanalysis, not a new independent validation. The vendor cause was unreconciled, and quote midpoint fills, 15-minute stops, and green exits were unvalidated. There were no deployable stops or targets. Trade payoffs were divided by 1.0025, which is a credit-asset fee approximation. The data sources were https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A trading rule for Bitcoin was tested. The rule had three conditions: the price must be below the 50-day moving average, the 3-day return must be less than 0, and the next open must be when the price is flat. The rule also had conditions for exiting a trade, which was when the prior close was above the 5-day moving average or after 5 calendar days. The test used hourly data with 1200, 72, and 120 windows. The test also included fees of 25 basis points and slippage of 10 basis points on each side, as well as a stress test of 20 basis points. The test was run from October 2024 for warm-up, 2025 for training, and from January 1, 2026, to September 9, 2026, for holdout. The results showed returns of -9.67% for daily data, -4.33% for reconstructed data, and -55.64% for hourly data. Out-of-sample testing showed returns of -5.00% for daily data, -9.89% for reconstructed data, -10.70% for matched data, and -51.38% for hourly data. The hourly data also showed a mean return of -0.66%, a win rate of 9.17%, and an average win-to-loss ratio of 0.26 to 0.75. The conclusion was to not enter a trade. A total of 120 cells were recorded from 1993 to 1970, but only 4 positive out-of-sample neighbors were found, which is not enough to select the rule. The test also found that previously seen out-of-sample data was a reanalysis, not new independent validation. The test had some limitations, including unreconciled vendor causes, unvalidated quote midpoint fills, and 15-minute stops and green exits. The trade payoffs were divided by 1.0025 to approximate the credit and asset fees. The data sources were https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the text: Premises from 2024 October 1 to 2026 September 9 downloaded 709 daily bars each, 17014/17014/17009 hourly, with 0 duplicates and 2/2/7 missing hours. Only 24-hour days were compared. Every 25 offset comparison, ranging from -12 to 12, had the best mean OHLC error at UTC, with a 2025 maximum of 584.37/732.74/1014.05 basis points for BTC/ETH/SOL. On December 2, a repeat of the daily and hourly analysis showed the same results, and minute aggregates reproduced the hourly OHLCV. An independent 24-hour control on Coinbase had opens of 86282.35/2798.25/126.65, compared to Alpaca hourly opens of 86270.82/2798.84/126.67, which were within 2.11 basis points. The supplied daily data had opens of 91625.132/3020.1375/139.716, which were 619.22/792.95/1031.66 basis points away from the Coinbase data. No match of minute-open or minute-tail volume could reproduce the supplied daily data. The conclusion is to quarantine the supplied daily execution and range inputs on flagged dates, as simple timezone, missing 24 hours, transient fetch, and simple tail explanations failed. The inference is that intraday opens are more plausible on December 2, but this is not proof that every hour is correct. A counterexample of SOL hourly low 124.3 versus Coinbase 126 shows differing quotes and venue extrema, with an unresolved vendor cause, and it is advised not to replace all history blindly. The sources of the data are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://api.exchange.coinbase.com/products/BTC-USD/candles, with the same paths for ETH-USD and SOL-USD. The observations were made from 19902 to 16.
A provider, Alpaca, offers historical crypto data, which includes quote midpoints and can have zero volume. The data is documented in multiple locations and requires pagination. The lowest tier fees are 15 basis points for makers and 25 basis points for takers, charged in the credited asset. Due to differing scope and versions, the historical overview and newer location list may not match. The proxy source location has not been independently verified. Therefore, 25 basis points baseline fees and next-open slippage should only be used as a research approximation, not as proof of historical midpoint fills. A crosscheck of BTC, ETH, and SOL prices on December 2 at minute and hourly intervals, as well as a separate Coinbase control, will investigate prices, not liquidity or account fills. The venue benefits from collecting turnover fees, while the trader needs an edge greater than the roundtrip cost. No token cash-flow valuation is inferred from vendor data, as a cash-only venue cannot monetize perpetual funding directly. This analysis addresses measurement economics, not a new BTC valuation thesis. The source dates are September 10, 04:03 UTC, with the fees page updated 12 months ago and the reference page updated 4 months ago. The actual account tier was not queried.
The automated trading fund manager made a final decision at 02UTC. The manager started with $235.86 in crypto cash and $850.99 in equity, with one closed forced Bitcoin trade and no holdings or queued orders. The goal is to achieve repeatable net profit with a binding constraint of independently positive executable edge. The manager considered 13,160 whole listing names, which resulted in 186 crypto matches, plus 2 movers and 188 IEX snapshots, and a 36-pair census. A broader search without verified stock edge was conducted, but it did not yield positive results. The manager also conducted 1,719 backtests from 1949 to 1956, which resulted in 180 cells, 96 holdout, and all 48 hourly losses. The base hourly returns were -51.3779% for Bitcoin, -54.336% for Ethereum, -50.1622% for Solana, -37.9921% for XRP, -56.1992% for Link, -41.1922% for Hype, -49.6762% for Litecoin, and -58.0976% for Uniswap. The manager also considered the daily returns for Hype, which were +17.983% with a mean of [-1.3935, 3.6092]. However, the historical training feed mismatches and current quotes partial freshness and depth, as well as 15-minute execution unvalidated, raised concerns. The primary flows and corporate cash showed dated quantities and financing constraints, and the Solana lower-tail funding did not validate price entry. A simulation of 10-trade blocks resulted in a loss probability of 83.7-99.99%, which reinforced the decision to retain cash. The conclusion is that no proposals were made, and the fund remains in cash with $235.86. The validity mandate gates failed due to limited feed history, fees approximation, survivorship, and regime selection. A strong counterargument is that the uptrend resumes and cash misses the rally, but the manager needs a new prospective net edge with positive uncertainty bound and verified venue exits, not capital shortfall. The rate and total failed hourly net means were -0.4456 to -0.9391% per trade, with a monthly shortfall of $349.01. The monitors 122, 104, and 152, as well as daily 14 and 25, were preserved, and the 04 handoff was renewed with collector status separately. The sources used were https://runway.adityaperswal.workers.dev/data/crypto-bars, https://www.circle.com/transparency, https://www.okx.com/api/v5/public/funding-rate-history, and https://blockstream.info/liquid/api/blocks.
A fund manager analyzed data and found that all hourly holdout means were negative and the quarter-Kelly allocation was 0. Using a numpy seed of 91003, the manager drew 3 trade circular blocks from each asset's actual holdout returns, creating 10,000 paths with 10 trades and a fixed amount of 50 USD, starting at 235.86. The whole capital returns were adjusted for a vbt entry fee denominator of 1.0025. The probabilities of a loss below the starting point were: BTC 99.95%, ETH 98.63%, SOL 99.86%, XRP 99.05%, LINK 98.12%, HYPE 83.70%, LTC 99.99%, and UNI 88.53%. The median end points were between 231.47 and 233.86. The loss odds were based on the empirical sample, not future calendar risk or probability bound. The 95th maximum drawdown was: 5.93 USD for BTC, 7.94 for ETH, 12.20 for SOL, 8.98 for XRP, 7 for LINK, 8.21 for HYPE, 8.16 for LTC, and 11.85 for UNI. No joint portfolio simulation was done and unseen regimes or 15-minute overshoots were not represented. The daily quarter-Kelly point estimate for HYPE was 6.66%, which would not qualify without training, cross cadence, and a positive confidence interval. The daily quarter-Kelly point estimate for ETH was 0.50%, which is approximately 1.19 USD below the 10 minimum. The approved allocation is 0 and cannot be increased to meet the minimum or 349.01 shortfall. The validity bootstrap reflects negative means, but the soundness is limited by selection, serial structure, and block length. The data sources are https://runway.adityaperswal.workers.dev/data/crypto-bars and backtests from 1949 to 1956.
A news scan found the headline 'UNI frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency UNI. The strategy had two conditions to enter a trade: the closing price was higher than the 50-day Simple Moving Average, which is a measure of the average price over 50 days, and the 3-day return was less than 0. The strategy would exit a trade when the previous closing price was higher than the 5-day Simple Moving Average or after 5 calendar days. The strategy used a 1-hour and daily time frame, with specific rules for when to open and close trades. The strategy was tested using historical data from 2025, with a holdout period from January 1, 2026, to September 9, 2024, and a warm-up period in October 2024. The results showed a return of -58.0976% for the hourly time frame and -17.5305% for the daily time frame. The strategy also had a drawdown, which is the maximum loss from a peak to a trough, of 58.8265% for the hourly time frame and 19.0732% for the daily time frame. The win percentage, which is the percentage of trades that were profitable, was 33.0189% for the hourly time frame and 63.6364% for the daily time frame. The strategy was not validated for 15-minute exits or stops and is not deployable. The data was sourced from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'LTC frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency Litecoin (LTC) that was tested and rejected. The strategy was based on two premises: the closing price being higher than the 50-day Simple Moving Average (SMA), and a 3-day return less than 0. The strategy entered the market at the next available bar open when the conditions were met, and exited when the previous close was higher than the 5-day SMA or after 5 calendar days. The hourly window for trading was set at 1200, 72, and 120.2. The strategy used a 25 basis point fee and 10 basis point slippage on each side, with a 20 basis point stress test. The training data was from 2025, with a holdout period from January 1 to September 9, 2024, and an October warm-up period. The results showed a daily return of -19.69% and a hourly return of -49.68%. The daily win rate was 35.71%, while the hourly win rate was 9.64%. The strategy was not validated for 15-minute venue exits or stops, and is not deployable. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'HYPE frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy called HYPE that was tested and found not to work. The strategy was based on two premises: when the price of a stock was higher than its average price over the last 50 days and the return over the last 3 days was less than 0, the strategy would enter the market at the next available opening price. The strategy would exit the market when the previous closing price was higher than the average price over the last 5 days or after 5 calendar days. The strategy used a technique called vector backtesting with 25 basis points fees and 10 basis points slippage on each side, and 20 basis points stress. The strategy was trained on data from 2025 and tested on data from 2026 from January 1 to September 9, with a warm-up period in October 2024. The strategy used a cash reset of 100 and would liquidate at the last available opening price. The strategy excluded missing bars and did not fill them for execution or signals. The strategy had distinct daily and hourly patterns. The training data had limits on inference from 1937 and did not include pre-2026 training data for HYPE. The strategy did not validate 15-minute venue exits or stops and was not deployable. The results of the strategy were as follows: for the hourly strategy, the return was -41.19%, the drawdown was 41.61%, and the win percentage was 36.84%. For the daily strategy, the return was 17.98%, the drawdown was 13.42%, and the win percentage was 62.5%. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'LINK frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency LINK. The strategy has two main rules: it enters the market when the closing price is higher than the 50-day Simple Moving Average and the 3-day return is less than 0, and it exits when the previous closing price is higher than the 5-day Simple Moving Average or after 5 calendar days. The strategy uses a 1-hour and daily time frame, with a 1.2% fee and 0.1% slippage on each trade. The training data is from 2025, and the holdout period is from January 1, 2026, to September 9, 2024, with a warm-up period in October 2024. The results show a return of -56.20% for the hourly time frame and -12.67% for the daily time frame, with a drawdown of 56.57% and 23.29% respectively. The win percentage is 14.39% for the hourly time frame and 47.37% for the daily time frame. The strategy uses a concept called 'quarter Kelly', which is a measure of the optimal fraction of the portfolio to invest in a trade. The results also show that the capital return is not exactly credited to the asset ledger due to fees and trade returns. The source of the data is from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'XRP frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency XRP. The strategy had two conditions to enter a trade: the closing price had to be higher than the 50-day Simple Moving Average, and the 3-day return had to be less than 0. The strategy would exit a trade when the previous closing price was higher than the 5-day Simple Moving Average or after 5 calendar days. A Simple Moving Average is a way to smooth out price data over a certain period. The strategy used a 25 basis point fee and 10 basis points of slippage on each side of a trade, with a 20 basis point stress test. A basis point is a unit of measurement for interest rates and fees. The strategy was trained on data from 2025 and tested on data from January 1 to September 9, 2024, with a warm-up period in October 2024. The results showed a daily return of -10.12% and a hourly return of -37.99%. The strategy also had a daily drawdown of 16.52% and a hourly drawdown of 39.38%. A drawdown is the percentage decrease in value from a peak to a trough. The strategy was not validated for 15-minute exits or stops and is not deployable. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'SOL frozen trend-pullback daily/hourly holdout rejected'. This refers to a trading strategy for the cryptocurrency SOL. The strategy had two conditions to enter a trade: the closing price had to be higher than the 50-day Simple Moving Average, which is a way to smooth out price data over time, and the 3-day return had to be less than 0. The strategy would enter a trade at the next available opening price when these conditions were met and the previous day's closing price was higher than the 5-day Simple Moving Average, or after 5 calendar days. The strategy used hourly time frames with specific settings, including a 25 basis point fee and 10 basis point slippage, which refers to the difference between expected and actual trade prices. The strategy was trained on data from 2025 and tested on data from 2026, with a warm-up period in October 2024. The results showed a daily return of -21.46% and a hourly return of -50.16%, with a drawdown of 28.08% and 51.02% respectively. The strategy was not validated for 15-minute exits or stops and is not deployable. The data was sourced from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.
A news scan found the headline 'ETH frozen trend-pullback daily/hourly holdout rejected'. This refers to a type of investment strategy that uses a trend, or a pattern of price movement, and a pullback, or a brief reversal of that trend. The strategy was applied to Ethereum, a type of cryptocurrency, and was rejected. The strategy had two main rules: it would enter the market when the closing price was higher than the 50-day simple moving average, which is a way to smooth out price fluctuations, and the 3-day return was less than 0. It would exit the market when the previous closing price was higher than the 5-day simple moving average or after 5 calendar days. The strategy was tested on hourly and daily time frames, which are periods of time used to analyze price movements. The test used a type of simulation called a vector backtest, which is a way to test an investment strategy using historical data, and included fees of 25 basis points, which is a way to measure a small percentage, and slippage of 10 basis points, which is the difference between the expected price and the actual price of a trade. The test also included a stress test, which is a way to simulate the performance of an investment strategy during difficult market conditions, of 20 basis points. The strategy was trained on data from 2025 and tested on data from 2026, and the results showed that the strategy did not perform well. The daily time frame had a return of -0.3949 and a drawdown, which is the maximum amount of money lost, of 14.3784. The hourly time frame had a return of -54.3359 and a drawdown of 54.6961. The results also showed that the strategy had a low win percentage, which is the percentage of trades that were profitable, and a high average loss, which is the average amount of money lost per trade. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-trading.