The fund manager has decided to retain $235.86 in cash after a review. The fund has a total of $850.99 and there are no open, pending, or closing trades for Bitcoin, with 10 units closed. The goal is to achieve repeatable net profit, with a binding constraint of validated net expectancy. The premises for this decision are: 1. Recorded hourly holdouts for Bitcoin, Ethereum, and Solana from November 2 to November 8 and November 9 showed losses of 14.9605%, 15.5393%, and 6.6888% respectively, with all 36 variants losing and daily negative results. 2. Recomputed quarter Kelly criteria showed negative results for all, with unresolved historical construction and reused holdout issues. 3. Fresh quotes at 12:32 have roundtrip fee and spread hurdles of 5.18%, 5.26%, and 6.19% for Bitcoin, Ethereum, and Solana respectively, with top ask depth of approximately $77, $81.7, and $95.8, which cannot assume full execution at the best ask price of $212.75. The conclusion is to make no orders, limits, or exit adjustments, and to retain $235.86 in cash. The validity of this decision is based on failed gates justifying zero exposure, not price forecast. A counterexample of reconstructed Ethereum and Solana daily winners and new Liquid blocks could coincide with a rally, but neither rescues the negative hourly tests. There will be no rerun or retuning of the unchanged rule on the trading run, and the tests remain recorded, not claimed as fresh validation. Independent frozen prospective evidence and reconciled history are needed before a positive Kelly criterion, venue caps, and fee/gap aware 8.5099 risk limit can be considered. The $349.01 shortfall has no role in this decision. The sources for this decision are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://runway.adityaperswal.workers.dev/data/crypto-snapshots, backtests from November 2 to November 8 and November 9, and observations from November 7 and November 8.
The European Central Bank made a primary decision on September 10 at 12:15 UTC to raise rates by 25 basis points, effective September 16, due to an inflation forecast increase for 2027/28 and growth forecast increase for 2026/27. Meanwhile, Liquid's primary tip advanced 12 blocks by 12:32 compared to the 12:01 collector, with the secondary timeout and operator hash remaining unchanged and authorized recovery unverified. Hourly payoffs were negative. As a result, euro financing is tightening and the explorer now reports new blocks. It is assumed that higher cash yields can raise crypto opportunity costs and chain activity could restore transfer capacity. Further assumptions suggest that risk allocation or confidence could change, but this can be offset by FX, expectations, and actual settlement. Those who benefit from this situation are cash yield recipients and users if settlements work, although issuance and liquidity do not ensure token price capture. A strong counterargument is that resilient growth could support risk assets and chain progress could remove overhang, but neither establishes a costed spot edge. The decision is to retain cash. This information comes from a news release found on the European Central Bank's website, a data line from Blockstream's Liquid API, and a raw script output from x.com/Blockstream.
A news scan found the following report: Premises: 1. Readback confirms all 24 observation groups containing 144 experiment cells end with their footer and are 1229–1323 characters. 2. Old 174/175 collectors saved 6 complete numeric payloads, but quote gaps were 15/30/30 minutes; cutoff-only output is not data. 3. At 08:14 Sep 10 replacement 178/179 are accepted active with last Run/output/exit null; remote execution remains unverified. Conclusion: retain cash decision 2198 and explicit collector gap; monitor 182 checks actual receipt at 12:30, 122/181 cover PPI/CPI. Daily 14/25 preserved. No open or pending crypto orders on final query; no exits or stop changes required. Run about 13 minutes against 43 planned/45 hard cap: audit completed within 9 min, catalyst work overlapped fetches, analysis completed early; final recording/review reserved and performed before report. No thread overran its allowance. Sources https://runway.adityaperswal.workers.dev/data/crypto-bars ; https://runway.adityaperswal.workers.dev/data/crypto-snapshots ; list_jobs fund=crypto ; query_research fund=crypto ; query_trades fund=crypto.
The fund manager has made a pre-open decision to retain $235.86 in cash and make no orders or exit changes. The fund currently has $235.86 in cash and a total equity of $850.99, with no open or pending orders. The goal is to achieve repeatable net profit, with a binding constraint of independently validated executable expectancy. There are three premises: first, 144 compression breakout cells were recorded, but all 36 hourly holdouts lost, with baseline prices of BTC -14.9605%, ETH -15.5393%, and SOL -6.6888% on November 9; second, all current compression and breakout signals are false, and historical OHLC faults and 15-minute revenue exit gaps remain; third, recent drift Monte Carlo sign reverses after demeaning, and one actual operator liquidation is not an edge. The conclusion is to make no proposals, queue no limits or stops, and make no adjustments, keeping $235.86 in cash. The validity of this decision is based on failed eligibility gates that warrant zero allocation, not a forecast of declining prices. The soundness of this decision is based on a conservative history mask that can miss profitable trades, as ETH and SOL reconstructed daily holdouts won 1.8163% and 2.8607%, but corresponding hourly holdouts lost 6.4361% and 1.9359%. The decision will be changed only after reconciled history and frozen independent cost-stressed daily, hourly, and 15-minute edge with uncertainty resolved. Then, the position size will be set to the minimum of quarter Kelly times $235.86, $212.7475 position cap, $235.86 fund cash, and $8.5099 fee-and-gap-aware loss fraction, with at most three new lots and a correlated risk check. Macro outcomes may change the watch, but not this gate. The PPI 122, CPI 181, and ECB handoff 182 are armed, and collectors 178 and 179 are scheduled, preserving 14, 25, and 104 Arc and 152 GME. A $349.01 shortfall will never enter the size. The sources of this information are https://runway.adityaperswal.workers.dev/data/crypto-bars, https://docs.alpaca.markets/us/docs/crypto-fees, and https://www.bls.gov/schedule/2026/09_sched.htm.
A four-day risk simulation for the C91008 fund has changed its outlook when the recent drift is removed. The simulation is based on two premises. First, it generates 10,000 joint 96-hour paths in 24-hour blocks from the last 60 days of log returns, with a seed of 9100804, and preserves cross-asset dependence. It stops when the target is 1.5 times the average daily range, observes and fills the hourly close, and times out after 96 hours, with a 25 basis point fee per side and a 10 basis point slippage. Second, the observed drift means that the net returns for Bitcoin, Ethereum, and Solana are +0.3551%, +0.8279%, and +1.2283% respectively. However, when the drift is removed, these numbers change to -0.6744%, -0.9049%, and -0.5181% respectively. The probabilities of reaching the target first are 19.58%, 16.22%, and 11.75% for the demeaned targets, and the timeouts are 49.21%, 51.48%, and 71.91% respectively. For the full fund with an equal sleeve, the demeaned mean is -$1.649, the 5th percentile is -$13.197, and the loss probability is 62.42%. For the 25% and 50% funds, the 5th percentiles are -$3.299 and -$6.598 respectively. The conclusion is that the drift assumption drives optimism, and these are risk scenarios, not backtest win probabilities or edge. The fact ends at observed returns, and stationarity, block choice, and the next four days are thought-experiment assumptions. The model misses intra-hour tails, next open fill, +1R partial, and breakeven, and venue 15-minute checks, and nominal stops are not loss bounds. The result was approved with no timeframe or target widening for shortfall. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars, and the statistics were generated using stats.py, with observations from 21562 to 21573.
A news scan found the following analysis: The current majors, BTC, ETH, and SOL, have completed closes on September 9 of 78283.41, 2467.70, and 101.5535, which are below their prior 7-day highs of 82233.50, 2545.60, and 107.35. The 7-day fractional ranges of 7.6626%, 7.6398%, and 9.8850% exceed the 60-day medians of 5.7400%, 7.4744%, and 8.0627%, which means compression also fails. The Average Daily Range, or ADR, which is a measure of price volatility, is 2598.8987, 101.5504, and 6.3270, or 3.3199%, 4.1152%, and 6.2302% of the close. The positive 7-day momentum of 1.2551%, 3.1698%, and 1.1237% does not override the gates. As a result, there is no fresh trigger, and no catch-up orders should be queued. At a 1 ADR nominal stop, the 1% equity budget of 8.5099 permits a gross notional of 256.33, 206.79, and 136.59 before fees, gaps, and venue caps, but the approved size is zero. The target of 1.5 ADR is a tested research parameter, not a recommended order or guaranteed weekend protection. This information comes from a data source at https://runway.adityaperswal.workers.dev/data/crypto-bars, based on observations 21555-60.
A news scan found the headline 'C91008 historical construction remains unresolved despite recent agreement'. This refers to a problem with the historical data of a trading system. The data was re-fetched from October 1, 2024, to September 9, 2026, which includes 709 daily rows and 17014, 17014, and 17009 hourly rows for Bitcoin, Ethereum, and Solana, respectively, with 2, 2, and 7 hours missing. The daily and hourly Open, High, Low, Close prices, which are the prices at the start, highest point, lowest point, and end of a trading period, differed by more than 0.01 basis points on 300, 295, and 295 days, with a maximum difference of 584.37, 732.74, and 1014.05 basis points. A basis point is a unit of measurement for interest rates and prices. Coinbase, a cryptocurrency exchange, showed discrepancies in the supplied opening prices on December 2, while the maximum differences on September 9 were 3.94, 7.17, and 10.45 basis points. The conclusion is that the recent agreement cannot confirm the accuracy of the historical data. The reconstructed studies are sensitivity checks, not verified truth, and the filters used to exclude missing days also change the sample. There are examples where legitimate price differences between venues exist, so these samples alone do not identify the party at fault. Large differences in old opening prices still undermine the simulation. The Solana data was recovered with slower pagination and no synthetic fill. Independent cash checks of 268 baseline closed rows matched the vectorbt data within 4.51e-16. The data sources include https://runway.adityaperswal.workers.dev/data/crypto-bars, https://api.exchange.coinbase.com/products/BTC-USD/candles, and corresponding Ethereum and Solana endpoints, with observations from 21474 to 21479 and 21552 to 21554.
A news scan found the headline 'C91008 pre-open drift is smaller than costs; majors remain correlated'. Premises are as follows: on 64 weekdays in the last 90 days, the mean returns from 08UTC open to 12UTC open were BTC +0.1194%, ETH +0.1451%, and SOL +0.0684%. These are gross mean returns, which means they are the average returns without considering any costs. The gross mean bootstrap 95% intervals were [-0.0653, 0.3068]%, [-0.0910, 0.3761]%, and [-0.2033, 0.3634]%, all of which span zero, meaning the returns could be positive or negative. With 25 basis points received-asset fees per side and 10 basis points slippage, the mean returns become -0.5796%, -0.5541%, and -0.6302%. Basis points are a unit of measurement, where 1 basis point is equal to 0.01%. Slippage refers to the difference between the expected price and the actual price of a trade. The last 60 completed UTC days provide 1439 aligned hourly log returns, which show a correlation between BTC and ETH of 0.8470, between BTC and SOL of 0.7557, and between ETH and SOL of 0.7590. Correlation measures how much two things move together. The ETH and SOL regressions on BTC give betas of 1.1536 and 1.1072, respectively. Beta is a measure of volatility, or how much an asset moves compared to another asset. In conclusion, pre-open activity alone does not justify entry, and the three sleeves share substantial market risk. This analysis has limitations, including a fixed sample of majors, a recent regime, and missing other venues and events. The inference is descriptive, not serial-dependence-adjusted, meaning it does not account for the dependence between consecutive observations. This is a distribution diagnostic, not a traded time-of-day strategy. The source of this information is https://runway.adityaperswal.workers.dev/data/crypto-bars, stats.py, and observations 21555-61.
A trading fund manager ran a test of a breakout strategy on a computer program called CLI. The test used data from the last 730 days and looked back 7 days to make decisions. The results showed that the strategy would have made 30.1279% profit with Bitcoin, 33.8668% with Ethereum, and 23.4302% with Solana, with a total of 214 trades. The manager also looked at the engine that made the trades and found that it used a daily same-close entry, did not account for fees or slippage, and did not hold out any data for testing. The manager concluded that these results cannot be used to confirm the success of the strategy or an order. The manager also noted that the results are not adjusted for costs and are only for diagnostic purposes. A separate test of a buy-and-hold strategy showed profits of 35.4970% with Bitcoin, 3.4305% with Ethereum, and a loss of 25.4054% with Solana. The data used for the test can be found at https://runway.adityaperswal.workers.dev/data/crypto-bars and the code for the engine is at /app/agent/dist/backtest/engine.js.
A news scan found the note: C91008 SOL compression breakout fails daily/hourly validation. The strategy was to enter a trade when the price closed above the prior 7-day high, but only if the prior 7-day fractional range was less than the trailing 60-day median. The plan was to enter the trade at the next open, with a stop loss at 1 times the average daily range of the last 20 days and a target at 1.5 times the average daily range of the last 20 days, with a 7-day timeout. The daily and hourly close threshold observations were followed by next-open fills, with one lot and no filled-forward execution. The fees were 25 basis points per side on the received asset, with a slippage of 10 basis points as the baseline and 20 basis points as the stress test. The training data was from 2025, the holdout data was from January 1, 2026, to September 9, 2026, and the warmup data was from October to December 2024. The premises were: 1. The supplied daily and hourly holdout returns were -3.5641% and -6.6888%, and the hourly training return was -10.9322%. 2. The reconstructed daily and hourly holdout returns were 2.8607% and -1.9359%, and changing the completeness of the data changed the sample, not the pure price attribution. 3. All 36 hourly holdout cells across 3 majors, 40, 60, and 80 median windows, two histories, and two costs lost. The conclusion was to reject the strategy because there was no positive independent executable edge. The baseline supplied hourly data showed 8 trades, with a win rate of 50.0000%, an average win of 3.8428%, an average loss of 5.3172%, and a mean return of -0.7372%, with a 95% confidence interval of -4.2210% to 2.6310% using 10,000 independent and identically distributed bootstrap samples. The windows and costs were diagnostics, not selected winners, and history faults, reused holdout, and 15-minute plus 1R exit gaps remained. All 144 cells were stored in 24 groups from 21505 to 21550. There is no current signal. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars, and the test and verification scripts are test.py and verify.py.
A news scan found the note: a trading strategy for Ethereum, or ETH, failed to work as expected. The strategy was to buy ETH when its price closed above its highest price in the last 7 days, but only if the price range in the last 7 days was smaller than the average price range in the last 60 days. The plan was to sell ETH when its price reached a target price or after 7 days. The strategy was tested using historical data from 2025 and the first 9 months of 2026, with the last 3 months of 2024 used to prepare the system. The results showed that the strategy did not work well, with losses of 9.5346% and 15.5393% in daily and hourly tests. Even when the strategy was adjusted, it still did not perform well. The conclusion is that this strategy does not have a positive effect and should be rejected. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and the test scripts are test.py and verify.py.
A news scan found the note: a trading strategy called C91008 for Bitcoin, or BTC, did not work as expected. The strategy was to buy when the price closed above the highest price of the last 7 days, but only if the price had not changed much in the last 60 days. The plan was to sell when the price went up by 1.5 times the average daily range of the last 20 days, or to sell after 7 days. The strategy was tested using data from 2025 for training, from October to December 2024 for warm-up, and from January 1 to September 9, 2026, for validation. The results were: a loss of 8.6832% and 14.9605% for daily and hourly trades, and a loss of 1.1218% for hourly training. Another test showed a loss of 0.5559% and 9.0164% for daily and hourly trades. The conclusion is to reject this strategy because it did not show any independent advantage. The test used fees of 25 basis points, or 0.25%, per trade, and a slippage of 10 basis points, or 0.10%, as a baseline, and 20 basis points, or 0.20%, as a stress test. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and the test scripts are test.py and verify.py.
A news scan found the following pre-open event chains. The goal is to achieve repeatable profit, with a validated payoff as the binding constraint. There are three premises: 1. The Bureau of Labor Statistics (BLS), which is a government agency that tracks economic data, schedules the release of the Producer Price Index (PPI) for September 10 and the Consumer Price Index (CPI) plus real earnings for September 11 at 12:30 UTC, but the outcomes are not yet known. 2. The European Central Bank (ECB), which is a central bank, confirms its meeting on September 10 and will release information on its website at 14:15/14:45 CET, but the actual publication timestamp must be converted from Central European Time (CET) to account for daylight saving time (DST) in Berlin. 3. A liquid operator, which is a company that provides financial services, says its software has been deployed and is preparing to restart, with an explorer tip that is 270885 seconds old, but the recovery has not been verified. The first-order effect is that the price prints and ECB decision may alter the expected interest rates, and the actual Liquid restart could restore the utility of asset transfers. The second-order effect is that interest rates and foreign exchange (FX) rates, as well as collateral mobility, may change the demand for leveraged assets and liquidity, and funding can flip while cash spot earns no interest. The third-order effect is that venue spreads and correlated risk can overwhelm the net returns of major assets, and the recipients of fees can benefit from turnover regardless of the profit and loss (PnL) of the fund. A counterargument is that benign inflation and a confirmed restart could spark a rally that was missed in cash, but neither of these outcomes provides an independent probability of winning. If the data is favorable, it will be recorded prospectively, and if it is adverse or absent, uncertainty will be retained, with both branches resulting in no automatic entry. The context includes the wholesale data on September 10 at 14 UTC, the Energy Information Administration (EIA) data at 16 UTC, and the Oracle data after the close, as well as the Pixclara date only on September 11. No causal crypto edge is assumed. The sources of this information include the BLS website, the ECB website, Blockstream, and the Liquid API. Detailed calendar observations are from 21417 to 23, and monitors are 122, 181, and 182.
The issuer's shares increased by 240,000, or 0.01729655%, from 1,387,560,000 on September 8 to 1,387,800,000 on September 9. This implies an indicative issuance proxy of $10.6524 million based on the September 9 net asset value of 44.38499. Circle reported 74.28 billion USDC on September 7, with a net increase of 0.94 billion over 7 days. OKX forecasts a 0.7542% increase in BTC and a 0.3478% increase in ETH, but a 0.3043% decrease in SOL. The liquidity context is mildly expansionary, but there is no calibrated spot edge. The soundness of the issuer is unchanged, with multiple pages having the same origin, and users can hold stablecoins rather than buy majors. Prior cash remains unchanged. An upgrade in fundamental watch would require sustained matched-date primary net issuance and attributable incremental usage, as well as an independent price edge. Sources include iShares and Circle transparency reports, and OKX funding rate API.
The C91006 operational handoff has been verified. There are two premises for this verification: first, a final readback confirms that all 36 observation groups, containing 216 cells, are complete, with each cell having 1015-1408 characters and a footer. Second, old quote and funding collectors, numbered 170 and 171, saved numeric remote payloads, but their quote coverage had gaps of roughly 30 minutes, and their cutoff-only output is not considered a new observation. Replacement collectors, numbered 174 and 175, were accepted and locally tested at 1460 and 1283 characters, but their last run details were null at 06:15:42 UTC. As a result, the new remote execution will be kept unverified until it is monitored at 08 UTC to check for actual receipt and primary-source changes. Other records, including daily census and integrity checks, and dated PPI, Arc, and GME data, have been preserved. There are no open or pending cryptocurrency lots, and a cash decision, numbered 2127, remains unchanged. This information comes from several sources, including a news scan that found the following links: https://runway.adityaperswal.workers.dev/data/crypto-snapshots, https://blockstream.info/liquid/api/blocks, and https://www.okx.com/api/v5/public/funding-rate, as well as a list of jobs related to cryptocurrency funding.
The fund started with $235.86 in cash and a total equity of $850.99, with no holdings or pending orders. The goal is to achieve repeatable net profit, with a binding constraint of independent executable expectancy. There are three premises: first, all cells are recorded, but there are no completed trades in the holdout sample; second, training data for Bitcoin is sensitive to timing, and data for Ethereum and Solana loses value when used together; third, historical price construction is unresolved, and current funding and supply snapshots are context, not a tested edge. Based on these premises, no proposals were made, and the approved quarter-Kelly size is zero because the required out-of-sample win probability and average win/loss are unavailable. The training-only quarter-Kelly for Bitcoin is 1.7815% of the fund, which is approximately $4.20, below the $10 minimum for crypto transactions. The validity of this decision is based on the lack of evidence, which warrants holding cash, but does not forecast falling prices. The soundness of this decision is based on conservative completeness, which may miss a rally, and censored trades could later win. The decision will be revisited if new evidence becomes available, including reconciled primary history and positive cost-stressed outcomes. The sources used for this decision include 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.
The automated trading fund manager made some observations about the performance of certain cryptocurrencies. They looked at the prices of Bitcoin, Ethereum, and Solana at different times, either daily or hourly, and saw how they changed. The manager found that from the supplied history in 2025, the daily and hourly returns were 11.0372% and 1.2896% for Bitcoin, -22.9129% and -14.5782% for Ethereum, and -0.5283% and -2.0384% for Solana. The manager also found that the average hourly change in Bitcoin's cash price was 0.2771%, but this number could be between -3.0491% and 3.2910%. The manager concluded that just reducing the number of trades does not make the entry points more reliable, and the performance of Bitcoin changes depending on when it is observed. The manager also noted that neither the daily nor hourly observations could reproduce certain behaviors, such as 15-minute stops or partial profits. The manager reminded that these observations are sensitive to the model used and do not represent protected loss limits. The manager also clarified that the reconstruction control and matched masks used do not validate the price history. No orders, stops, or targets are recommended based on this analysis, which used data from https://runway.adityaperswal.workers.dev/data/crypto-bars.
A joint monthly sizing bootstrap analysis for C91006 showed losses at every nonzero illustrative allocation. The analysis was based on three premises: first, there were no closed 2026 holdout trades, so an out-of-sample trade-payoff Monte Carlo analysis was not possible, which is a statistical method to estimate potential outcomes. Second, a separate 2025 training exercise used 17 completed trades, divided into three equal cash sleeves, with 12 monthly observations and 10,000 joint circular three-month resamples, using a seed value of 9100602 for reproducibility. Third, the actual training portfolio return was -4.8278%, with a monthly mean confidence interval of -1.0938% to +0.2693%, which is a range of expected average returns. The simulated median annual return was -1.0327% at 25% of fund capital, -2.1304% at 50%, and -4.5639% at 100%, with a loss probability of 85.21%, 86.55%, and 88.38%, respectively, and a 95th percentile monthly-observed drawdown of 3.9160%, 7.7296%, and 15.1195%. The conclusion is that no nonzero illustrative allocation is supported, and these results are training diagnostics, not predictions of future probabilities. The full-fund median dollar loss is $10.76 on $235.86, which is not an estimate of this month's result. The analysis has limitations, including repeated overlapping months, few regimes, supplied-bar faults, fixed sleeve rebalance, and no intramonth drawdown or venue exit model. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars.
A news scan found the report that on September 9, the closing prices of Bitcoin, or BTC, at 78,283.41, Ethereum, or ETH, at 2,467.70, and Solana, or SOL, at 101.5535, were higher than their Simple Moving Average, or SMA, over 200 days, which were 69,921.47, 2,046.77, and 82.7251, respectively. The returns over 90 days were 23.1589 percent for BTC, 47.6390 percent for ETH, and 51.9190 percent for SOL. However, the monthly rule only allows entries on the first day of the month, so September 10 cannot be used as a catchup entry. Also, a missing hour of data on March 12 makes the SMA200 calculation invalid until that point. The report concludes that the positive trend is descriptive, but not a trigger for action, nor independent validation. The change to zero eligible trades is due to the mask, not evidence that repaired prices create alpha, or excess return. The audit found discrepancies in the data, with a maximum of 620.64, 790.68, and 1128.48 basis points, or 0.01 percent, over 569, 567, and 329 days, respectively. The strongest counterargument is that assuming one missing hour is conservative, and filling it requires justified information, not just choosing the feed that wins, according to the source https://runway.adityaperswal.workers.dev/data/crypto-bars.
A news scan found the headline about a monthly trend for the SOL cryptocurrency. The automated trading fund manager used a simple moving average, or SMA, which is a way to smooth out price changes over time. The manager looked at the prior close price being greater than the SMA 200, which is the average price over 200 days, and a positive 90-day return, which is the profit made over 90 days. The manager also considered the first day of the month and the next open price after a close cross, which is when the price crosses above or below a certain level. There was a 28-day timeout, which is a period of time when no trades were made. The manager used data from 2024 for warm-up, 2025 for training, and 2026 from January 1 to September 9 for holdout, which is a period of time when the manager does not make trades. The manager used quote-based bars, which are a way to show price changes, and fees of 25 basis points, or bps, which is a unit of measurement for interest rates and fees, on the received asset, and a slippage of 10 basis points, which is the difference between the expected price and the actual price of a trade. The manager also used a stress test, which is a way to simulate difficult market conditions, with a base of 20. The manager used a system called vectorbt, which is a way to backtest and evaluate trading strategies. The results of the training period showed a return of -0.5283% and a drawdown of 12.3606%, which is the maximum loss of value during a certain period. There were 4 trades made, with 0 open trades, which means that all trades were closed. The win rate was 50%, which means that half of the trades were profitable. The average win was 11.2285% and the average loss was -10.3158%. The results of the hourly training period showed a return of -2.0384% and a drawdown of 11.8227%. The holdout period showed a return of -1.8358% and a drawdown of 6.3791%, but there were 0 closed trades, which means that no trades were made during this period. The manager concluded that the trade qualification should be rejected and the notional, which is the total value of the trades, should be 0. The manager also noted that there was no monthly catch-up on September 10. The manager mentioned that there were missing vendor reconciliations, unseen validations, and partial executions, which are trades that are not fully completed. 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 monthly trend for the Ethereum cryptocurrency, or ETH. The automated trading fund manager used a set of rules to decide when to buy or sell ETH. These rules included looking at the price of ETH compared to its average price over the last 200 days, which is called a Simple Moving Average, or SMA. The manager also looked at the return on investment over the last 90 days. The manager only considered buying ETH on the first day of each month. The manager used a stop-loss order, which is an order to sell a stock when it falls to a certain price, and a target price, which is the price at which the manager wants to sell the stock. The manager also set a time limit of 28 days for each trade. The manager used data from 2024 to warm up the system, data from 2025 to train the system, and data from January 1, 2026, to September 9, 2026, as a test set. The manager used a type of analysis called vectorbt and assumed that the cost of buying or selling ETH would be 25 basis points, or 0.25%, of the value of the trade, and that the price of ETH might be different from the expected price by 10 basis points, or 0.10%. The manager also assumed that there might be additional stress or uncertainty in the market. The results of the analysis are as follows: for daily trades, the return on investment was -22.91%, the maximum loss was 29.60%, and there were 6 trades, with 0 trades still open. The win rate was 33.33%, the average return per trade was -3.84%, the average return per winning trade was 8.31%, and the average loss per losing trade was -9.91%. For hourly trades, the return on investment was -14.58%, the maximum loss was 21.20%, and there were 6 trades, with 0 trades still open. The win rate was 33.33%, the average return per trade was -2.38%, the average return per winning trade was 6.63%, and the average loss per losing trade was -6.89%. For the test set, there were no closed trades, so it is not possible to calculate the win rate or average return per trade. The manager concluded that the system did not work well and did not approve any trades. The manager also noted that there were some missing data and that the system needs more validation. The data used for this analysis came from the following sources: https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the headline 'C91006 BTC monthly trend: zero closed holdout trades prevents edge calibration'. This refers to a trading strategy for Bitcoin, denoted as BTC, where a 'holdout' is a set of data not used in training, a 'SMA200' is a Simple Moving Average over 200 days, and 'ADR' stands for Average Daily Range. The strategy had certain conditions, such as the prior close being above the SMA200, a positive 90-day return, and specific rules for stopping and targeting trades. The data was divided into warm-up, training, and holdout periods, specifically 2024 for warm-up, 2025 for training, and January 1 to September 9, 2026, for the holdout. The training used daily and hourly data, with fees of 25 basis points and a slippage of 10 basis points. The results for the daily training included a return percentage of 11.0372%, a drawdown percentage of 10.6879%, and a win rate percentage of 57.1429%. For the hourly training, the return percentage was 1.2896%, the drawdown percentage was 12.2081%, and the win rate percentage was also 57.1429%. However, the holdout period for hourly data showed a return percentage of -0.7073% and no closed trades, which means win probability and average win/loss are unavailable. The conclusion was to reject trade qualification due to missing vendor reconciliation and unseen validation. The source data came from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A study of three major cryptocurrencies, Bitcoin, Ethereum, and Solana, found that they share a large market exposure. The study was based on three premises: first, the daily returns of these cryptocurrencies from 24-hour aggregates are highly correlated, with correlation coefficients of 0.91395 between Bitcoin and Ethereum, 0.88286 between Bitcoin and Solana, and 0.88250 between Ethereum and Solana. Second, a statistical analysis called ordinary least squares, or OLS, against Bitcoin showed that Ethereum has a beta of 1.24655 and an R-squared of 0.83530, while Solana has a beta of 1.20728 and an R-squared of 0.77945. Third, the annualized sample volatility of these cryptocurrencies is 46.72% for Bitcoin, 63.73% for Ethereum, and 63.89% for Solana. The conclusion of the study is that dividing cash across these three symbols is not three independent investment edges, and investors should consider bootstrapping entry months jointly and budgeting combined risk. The study notes that its validity is based on common dates that remove availability differences in this descriptive comparison, but its soundness is limited by a short 2026 sample, regime-dependent correlation, and quote-based close and OLS point estimates, which do not imply causation or forward beta guarantee. The intercepts of -0.02128%/day for Ethereum and -0.03004%/day for Solana are in-sample estimates, not short recommendations. The study also notes that idiosyncratic protocol shocks can break correlation, which strengthens the need for liquidity and risk limits rather than assuming a hedge. The data for this study came from https://runway.adityaperswal.workers.dev/data/crypto-bars.
A news scan found the headline 'C91006 CLI momentum90 is a gross benchmark, not monthly strategy validation'. Required CLI was executed on September 10 at 06:03 UTC, with a momentum lookback of 90 days, using 617 and 618 bars. The results were as follows: Bitcoin had a return of -2.5390% with a drawdown of 25.7377% and 33.333% wins out of 3; Ethereum had a return of +17.8630% with a drawdown of 40.3609% and 33.333% wins out of 6; Solana had a return of -25.4192% with a drawdown of 43.3791% and 25% wins out of 12. The premises of this test were that the CLI continuous same-close momentum is not frozen, and it uses a 1830 monthly-entry rule, with no fees, slippage, or holdout, and includes the partial current day. The conclusion is that the positive Ethereum benchmark does not authorize entry, and it should be reported only as a harness diagnostic. The source of this data is https://runway.adityaperswal.workers.dev/data/crypto-bars, which is a data line.
A news scan found the text: Premises: Each asset contributes 2160 recent hourly returns over 2154 overlapping 6-hour blocks, with 10,000 paths per model, over 28 days, and a seed of 9100601. The stop is set at 1 ADR 20, with a target of 1.5 ADR 20, using the gross reference of the September 9 close, and fees of 25 basis points and a slip of 10 basis points per side. Empirical drift versus demeaned target hit BTC at 54.51 and 40.09 percent, ETH at 58.63 and 39.87 percent, and SOL at 63.99 and 40.96 percent, with net means of plus 0.6116 and minus 0.6963 percent, plus 1.4099 and minus 0.6895 percent, and plus 3.3789 and minus 0.4621 percent. The conclusion is that a positive path forecast depends heavily on assuming recent drift persists, and it cannot be used for Kelly probability. The validity is based on common random draws and an isolated drift assumption. The soundness is based on unconditional recent returns, overlapping blocks, and a close fill on the first hourly threshold cross, not the next open, with no 15-minute venue or plus 1 R partial, and forecasts are conditional scenarios. A no-gap nominal 1 percent equity risk notional of 211.70, 176.73, and 122.79 is not a loss guarantee, and 5th percentile losses of 5.08, 6.32, and 7.98 percent exceed ADR plus cost. The sources are https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.