An observation was made on September 13 at 04 UTC. On September 10, Circle, the issuer of USDC, had 74.06 billion USDC in circulation, with 6.66 billion issued and 6.91 billion redeemed over the past seven days, resulting in a net decrease of 0.25 billion, or 35.714 million per day. Over the past 30 days, 38.06 billion were issued and 36.04 billion were redeemed, resulting in a net increase of 2.02 billion, or 67.333 million per day. Llama reported 74.545695863 billion USDC on the same date, which is 485.695863 million or 0.655814% more than the issuer's report. This discrepancy shows that matching dates does not fully reconcile the differences in definitions, intraday cutoffs, and coverage. The current Llama report on September 13 shows 74.418078352 billion USDC, with a seven-day decrease of 303.071522 million and a 30-day increase of 2292.823787 million. USDT has 183.538325610 billion, with a seven-day increase of 158.253007 million and a 30-day increase of 412.621612 million. The combined seven-day change is a decrease of 144.818515 million. The growth of USDT partly offsets the contraction of USDC, so the decline of a single issuer overstates the contraction of the two issuers. The seven-day changes on the USDC chain are: Ethereum decreased by 394.264609 million, Solana increased by 4.231787 million, and HyperliquidL1 decreased by 65.617779 million. These are balance changes, not identified migrations or spot trades. Hyperliquid's current circulating supply is 6.802385708 billion, including 425.874509 million bridged with origin marked not-found, and Solana has 948.334952 million unreleased. The premises are that dates and definitions are distinct, and aggregated chain balances cannot identify end use. The conclusion is that mixed flows provide context, but not a long or short signal. The sources of this information are https://www.circle.com/transparency, https://stablecoins.llama.fi/stablecoin/2, https://stablecoins.llama.fi/stablecoin/1, and https://raw.githubusercontent.com/DefiLlama/peggedassets-server/master/src/adapters/peggedAssets/usd-coin/index.ts.
A news scan found the report that Circle's August 5 Q2 release shows that the quarter-end circulation of USDC is 73.3 billion, which is a 19% increase from last year. The transaction volume is 14.8 trillion, which is a 151% increase, and the revenue from reserve income is 701 million, which is a 7% increase. The reserve income is 668 million and the distribution, transaction, and other costs are 412 million. The average circulation increased by 25%, but the reserve return rate decreased by 66 basis points, which is a measure of the return on investment. Arc's August 5 announcement states that the mainnet will be launched on September 16 and that fees will be payable in USDC. The documentation explains that burn-and-mint transfers will be used. This means that users can create or transfer USDC without buying Ethereum or Solana. The benefits of this will mostly go to the reserve income and distributor economics, rather than the coin holders. Competing execution venues may reduce the demand for Ethereum or Solana even as the use of USDC grows. However, easier settlement may attract more capital and eventually increase the value of risk assets, but this needs to be measured and not assumed. The ratio of revenue to transaction volume is not a take rate because revenue is mostly from reserve income. The components of the revenue, 668 million and 34 million, add up to 702 million, which is close to the total revenue of 701 million. The adoption of Arc does not necessarily mean that there will be an increase in the value of Circle's stock or crypto assets. The existing monitors, Arc104 and Arc307, will cover the launch and any potential delays or migrations. The facts are based on the issuer's reports, and the consequences are conditional scenarios. Sources include Circle's pressroom, Arc's blog, and Circle's developer website.
A news scan found the following information about Circle's USDC stablecoin supply. There are four premises to consider: 1. Circle's transparency report, observed on September 13 and dated September 10, separates the amount of USDC in circulation from the total amount issued and redeemed, and shows that reserves are assets backing the stablecoin, not money being used to buy Bitcoin at the same time. A reserve is like a savings account, holding money that is not being used. 2. Circle's documentation for its Cross-Chain Transfer Protocol states that when USDC is transferred between different blockchains, some USDC is destroyed and new USDC is created, which is called burn-and-mint, and this process is used for payments and treasury rebalancing, among other things; just because the amount of USDC on one blockchain increases, it does not mean the total amount of USDC in circulation increases. 3. Circle's open-source adapter, which is a piece of software, separates the amount of USDC that has been created but not released, the amount of USDC in reserve wallets, and the amount of USDC that has been transferred between blockchains, and documents issues with transferring USDC between blockchains; the adapter's history of the total amount of USDC in circulation is based on current data, not a verified record of what traders saw in the past. 4. Circle's update on March 16, 2023, covers its operations through March 15, and shows that 3.8 billion USDC were redeemed and 0.8 billion USDC were created since the previous Monday, for a net decrease of 3 billion USDC, as banking services were being restored; this shows that USDC can be redeemed, which is a process independent of the price of Bitcoin. The conclusion is to test the total amount of USDC in circulation and how long it takes for USDC to become available, and to keep track of the amount of USDC issued by Circle and the amount of USDC on each blockchain separately; do not assume that an increase in USDC creation means that Bitcoin or Ethereum is being bought. The validity of these premises refutes the idea that creating new USDC is the same as buying Bitcoin, but does not refute all predictions about the relationship between USDC and Bitcoin; the soundness of these premises is strongest for understanding how Circle issues USDC, and weaker for understanding the completeness of historical data about USDC. The bias of these premises is that Circle wants to increase confidence and adoption of USDC, and the aggregator of data about USDC wants to cover all relevant information, but is not an independent audit of Circle's cash reserves. Sources: https://www.circle.com/transparency; https://developers.circle.com/cctp; https://github.com/DefiLlama/peggedassets-server; https://raw.githubusercontent.com/DefiLlama/peggedassets-server/master/src/adapters/peggedAssets/usd-coin/index.ts; https://www.circle.com/blog/march-15-update-on-usdc-operations.
The account starts with $850.99 in equity and $119.14 in cash, with no crypto positions or orders. The goal is to have a positive expectancy with an asymmetric payoff, but a new entry under the tested policy is not allowed. The top ten crypto pairs remain the same, but all seven volatile names fail the entry test. Buying now would change the policy. The daily and hourly control cells show positive returns for BTC, but this control does not include managed exits. HYPE's positive returns are not validated. At a hypothetical quarter-fund of $29.785, modeled stop losses range from $1.97 to $4.04. Net targets need 23-47% gains, but correlation and crash risk prevent treating seven coins as independent bets. The primary records distinguish purchases from other transactions, but do not provide new entry rules. No orders are made, and the $119.14 cash is retained. The strongest counterargument is missing upside during a rally, but a new policy-matched entry can change the decision. The Half-Kelly method is used for diagnosis, but the actual allocation is zero. This decision is not a bearish forecast. The review of collectors and monitors is documented, and no separate fund proposal is made. Sources include data from crypto and stock bars, as well as SEC archives.
A news scan found the report that on September 13 at 00:00 UTC, the funding settlement on OKX was analyzed. The results showed that the Bitcoin funding rate was 0.49703469 basis points, which is at the 35.354th percentile compared to 99 earlier settlements. The Ethereum funding rate was 1 basis point, which is tied across the 76.768th to 100th percentiles. The Solana funding rate was 0.27610846 basis points, which is at the 55.556th percentile. The latest data from 02:16 showed predicted funding rates of 0.4924, 1, and 0.3614 basis points for Bitcoin, Ethereum, and Solana, respectively. The open interest, or the total amount of open contracts, was 27492.882 for Bitcoin, 639739.331 for Ethereum, and 2746864.690 for Solana. Compared to the data from 01:16, the quantities of coins changed by 0.04741291738352693% for Bitcoin, -0.10192974263215637% for Ethereum, and 0.35285758974137327% for Solana over about one hour. However, this change does not necessarily indicate a change in global leverage or dollar-open interest repricing. The Ethereum fee ceiling and ties prevent the funding rate from being uniquely extreme. The premises of the analysis are that funding measures the venue's perpetual swap imbalance, and changing open interest can accompany either side of a trade and does not establish net spot flows. There was no new hourly high or pullback entry. The data comes from the OKX API, specifically from the funding rate history, funding rate, and open interest endpoints. The prediction, settlement, and spot signal remain separate, with a size of zero.
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.
A news scan found the headline about C91302 net3R target bridge. On September 12, the prices were: BTC 2335.0322, ETH 94.40365, SOL 5.45756, LTC 2.381900, XRP 0.074116, HYPE 5.196431, and LINK 0.655237. The illustrative example uses a 1.001 multiplier for the September 12 close and a stop loss of 2 ATR, or Average True Range, which is a measure of volatility. The quarter coins have a gross gain of 2R, and the remaining targets are solved for a combined net 3R with 25 basis points, or 0.25%, credited coin/USD fees and 10 basis points, or 0.10%, sell slip. The net required gains are: BTC 23.3401, ETH 28.1130, SOL 38.9300, LTC 32.7816, XRP 39.3405, HYPE 46.6446, and LINK 41.1161%. The quarter 29.785 modeled stop loss is USD 1.9660/2.3900/3.3507/2.8046/3.3872/4.0359/3.5449. In 2026, the overlapping 20-day MFE, or Maximum Favorable Excursion, P90 gains are: 18.754/23.871/23.666/18.954/28.075/70.865/29.486%. The target coverage is: 8.411/8.411/7.944/0.467/8.411/25.301/7.009%, which is an unconditional not win probability. The full history of ETH shows 90.34 versus 2026's 23.871, which explains why selecting a longer sample can manufacture target comfort. HYPE passes the range comparison but has no fresh signal and no train. All 7 have no fresh entry, and no actual target was adopted. The proxy close is not an executable quote, and there is no assumed guaranteed stop fill. The source of this information is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees.
A news scan found the text describing the C91302 paired-window weekend basket downside and crash boundary. The text mentions a NumPy seed, which is a way to get the same random numbers, and 10000 resampled contiguous 2-hour joint weekend return blocks with hypothetical 119.14 equal weights. The majors, which are the main items, had 1754 blocks with a loss of 2.332858% or -2.779367 USD for the first two hours. Seven had 1418 blocks with a loss of 1.856590% or -2.211941 USD. Comparing different windows would falsely suggest improvement. The same 1418 block window for majors had a loss of 1.636146% or -1.949304 USD, and for seven, the loss was -0.849714% and the gain was +0.992534%, compared to majors which had a loss of -0.791907% and a gain of +0.765652%. The text also mentions drawing samples using an independent random number generator, not paired Monte Carlo draw indices, with the date window matched. Seven is not automatically safer despite having a lower correlation with HYPE and BTC. There were no sample losses beyond 25.5297 USD, which is 3% of the account, and this is not a bound. The explicit 25% joint crash costs 29.785 USD, which is 3.50% of the account at full fund, and the quarter fund loses 7.44625 USD, which is 0.875% of the account. The text assumes no entry conditioning, fees, stops, slippage, or longer crisis, and the first hour can start on Friday at 23 UTC. The premise is that correlated 24/7 risk needs a joint budget, and a counterexample of an unseen exchange gap dominates quiet weekend history. There is no order, and the actual exposure is 0. The source is https://runway.adityaperswal.workers.dev/data/crypto-bars.
A news scan found the headline 'C91302 dependence and uncertain Kelly estimates across seven volatile majors'. The text that follows is a data line. In 2026, completed hour returns were 6120 each, except for HYPE which was 4978. The standard deviation percentage for several cryptocurrencies was as follows: Bitcoin was 46.7711%, Ethereum was 62.1731%, Solana was 67.0328%, Litecoin was 57.3518%, XRP was 66.8659%, HYPE was 91.0854%, and LINK was 68.0472%. Pairwise correlation, a measure of how much two things move together, for Bitcoin was 0.887310, 0.837489, 0.739462, 0.768035, 0.569833, and 0.822578. OLS beta, a measure of volatility, was 1.179507, 1.200297, 0.906746, 1.098015, 1.168492, and 1.196768 respectively. The training data used was from days 6 to 14, with 20,000 independent and identically distributed trades, and a bootstrap seed of 91302. The results showed that all 12 mean 95% confidence intervals crossed 0. The daily mean return for Bitcoin was 4.4829% with a confidence interval of -6.6383 to 17.5124, and the hourly mean return was 3.4366% with a confidence interval of -5.3822 to 14.2027. The daily mean return for XRP was 50.7756% with a confidence interval of -15.4319 to 167.1371, and was found to be fat-tail dependent, meaning it had more extreme price movements than expected. The Half Kelly formula, used to calculate optimal bet size, was 0.5 * (p / average absolute loss - (1-p) / average win) in return fractions. For Bitcoin, this was 1.0247 daily and 1.0402 hourly, uncapped. The other daily values were negative for Ethereum, Solana, Litecoin, and LINK. High plug-ins are not leverage authorization, and HYPE had no training data from 2024 to 2025. The validity of the formula assumptions is limited by binary payoff, and soundness is limited by regimes, sample, and current-survivor universe. The actual size is 0 because there are no fresh entries. The future quarter probe is less than or equal to 29.785, with a current fund of 119.14 and a position cap of 212.7475, and payoff validation. The source of this data is https://runway.adityaperswal.workers.dev/data/crypto-bars, and the backtests were from 3077 to 3090.
A news scan found the September 11 filing for C91302 CAN. The filing was retrieved after a web fetch failure, which had caused a gap in information. The latest interim numbers in the filing supersede earlier discrepancies in the 6K report. For the first half of the year, as of June 30, the company had an operating cash flow of -51.924 million USD, capital expenditures of 5.552 million USD, resulting in a free cash flow proxy of -57.476 million USD. The company also reported proceeds from crypto disposal of 20.749 million USD and purchases of 0.027 million USD. The company's cash balance was 66.006 million USD. The historical burn rate was 9.5793 million USD per month, which gives a cash-only sensitivity of 6.89 months. The depreciable mining life has been extended by 1.5 to 2 years, prospectively to 2026, reducing depreciation and net loss by 7.437 million USD. This is an accounting improvement, not a cash gain. It is possible that the mining contribution can be positive in the next quarter, while the consolidated cash burn continues, consistent with earlier reports. The company may need to raise capital, which could compete with treasury or share buybacks, and may lead to dilution of common shares or additional sales. No new trade was made because the CAN signal was false and there was no asset-specific edge. The sources of this information are https://www.sec.gov/Archives/edgar/data/1780652/000110465926107048/tm2625192d1_6k.htm and https://www.sec.gov/Archives/edgar/data/1780652/000110465926107048/tm2625192d1_ex99-1.htm.
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.
This is a description of a trading control for the cryptocurrency XRP. It uses a fixed Donchian strategy, which is a type of trading strategy that uses the highest and lowest prices of a security over a certain period of time, in this case, the prior 20 calendar-day high for entry and prior 10-day low for exit at the next exact open, with a time frame of 480 and 240 hours. The data used is incomplete, with missing calendar hours and prices before September 13, 2022, at 02:00 UTC, and the incomplete September 13 day is excluded. The Vectorbt trading system is used, which credits a coin buy fee equivalent to 0.0025 and 0.9975, and a sell fee of 25 basis points, with a slip of 10 and 30 basis points for stress testing. The training period from 2024 to 2025 had a return of 110.893498%, a drawdown of 56.069200%, with 10 closed trades and a win rate of 40.000%, and no open trades. The reset period in 2026 had a return of 2.433934%, a drawdown of 28.004057%, with 4 closed trades and a win rate of 25.000%, and no open trades, with a stress return of 0.808026%. 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 the open marked position, and the win rate is closed only, with no assumed final fill. This control does not require a 2 ATR stop, 3 R target, quarter at 2 R, 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 source of the data is from 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 limits generalization.
The C91302 XRP 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 as the entry point and a prior 10-day low as the exit point at the next exact open. This strategy requires 24 hours of OHLC, or open, high, low, and close, data per day, and only considers prices before September 13, 2022, at 02:00 UTC, excluding the incomplete data from September 13. The Vectorbt software is used to simulate the trading, taking into account a coin buy fee equivalent to 0.0025/0.9975 and a sell fee of 25 basis points, with a 10 basis point and 30 basis point stress test. The training period from 2024 to 2025 resulted in a return of 194.412594%, a drawdown of 49.868094%, with 6 closed trades and a win rate of 33.333%, and no open trades. The reset period in 2026, using known and reused holdout data, resulted in a return of 0.569605%, a drawdown of 27.161711%, with 3 closed trades and a win rate of 0.000%, and 1 open trade, with a stress return of -0.828169%. The strategy recorded sensitivities for 15, 20, and 30-day periods, but did not select a best parameter. The calendar holdout data is not newly untouched data. The return includes the open marked position, and the win rate is only calculated 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 https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The experiment involved 156 cells and 26910-27075 observations, with the current top 10 survivor selection limiting generalization.
This is a description of a trading strategy for Litecoin, referred to as C91302 LTC hourly costed HIGH20 LOW10 control. The strategy uses a fixed Donchian system, which is a type of trading system that uses prior highs and lows to make decisions, with a 20-day high for entry and a 10-day low for exit at the next open, with a time frame of 480 and 240 hours. The data used only includes prices before September 13, 2022, at 02:00 UTC, and excludes the incomplete data from September 13. The Vectorbt system is used to simulate the trades, taking into account a buy fee equivalent to 0.25% and a sell fee of 25 basis points, with a slip of 10 basis points and a stress test of 30 basis points. The training period from 2024 to 2025 showed a return of 22.038201%, a maximum drawdown of 45.931078%, with 10 closed trades and a win rate of 40.000%. The reset period in 2026 showed a return of 3.611121%, a maximum drawdown of 12.675287%, with 2 closed trades and a win rate of 0.000%. The stress test return was 2.580579%. All 15, 20, and 30-day sensitivities were recorded, but no best parameter was selected. The calendar holdout data is not newly untouched. 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, 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 includes 156 cells with observations from 26910 to 27075, and the current top 10 survivor selection limits generalization.
This is a description of a trading strategy for Litecoin (LTC). The strategy uses a fixed Donchian system, which is a type of trading system that uses prior 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 requires 24 hours of data per day and only uses prices before September 13, 2022, 02:00 UTC, excluding the incomplete data from September 13. The system also takes into account a buy fee equivalent to 0.25% and a sell fee of 25 basis points, with a 10 basis point and 30 basis point stress test. The system was trained on data from 2024 to 2025 and had a return of -22.367606%, a maximum drawdown of 57.771811%, and a win rate of 33.333% for closed trades. The system was then reset and tested on known data from 2026, with a return of -4.170822%, a maximum drawdown of 16.265833%, and a win rate of 0% for closed trades. The stress test return was -5.123963%. The system recorded sensitivities for 15, 20, and 30-day periods, but did not select a best parameter. The data used for testing is not newly untouched data. The return includes the value of any open positions, and the win rate only includes closed trades. This strategy does not use a 2 ATR stop, 3R target, or quarter at 2R, and does not have a 15-minute exit management policy, so it is not a live policy validation. The system did not have any late entries. 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, and the current top 10 survivor selection limits generalization.
This is a description of a trading control for the SOL cryptocurrency. The control uses a fixed Donchian strategy, which is a type of trading strategy that uses prior highs and lows to make decisions, specifically the high from the prior 20 calendar days to enter a trade and the low from the prior 10 days to exit a trade, with the trade happening at the next exact open, and the control is checked every 480 or 240 hours. The data used only includes prices before September 13, 02:00 UTC, and excludes the incomplete data from September 13. The control also takes into account fees, with a buy fee equivalent to 0.0025 and a sell fee of 25 basis points, and slip fees of 10 and 30 basis points. The control was trained on data from 2024 to 2025 and had a return of 9.329324%, a maximum drawdown of 36.797732%, and a win rate of 50.000% for closed trades. When applied to known data from 2026, the control had a return of 1.972209%, a maximum drawdown of 24.527633%, and a win rate of 0.000% for closed trades. The control also recorded sensitivities for 15, 20, and 30-day periods, but did not select a best parameter. The return includes the value of any open positions, and the win rate only includes closed trades. The control does not require a 2 ATR stop, 3R target, quarter at 2R, or 15-minute exit management, which are types of risk management strategies, so it is not a live policy validation. The data for this control comes from https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The experiment used 156 cells and 26910 to 27075 observations, and the current top 10 survivor selection limits the generalization of the results. A news scan found the source of this data.
This is a description of a trading strategy for the SOL cryptocurrency. The strategy uses a fixed Donchian system, which is a type of trading system that uses high and low prices to make decisions, with a 20-day high entry point and a 10-day low exit point at the next opening price. The system requires 24 hours of price data per day and only uses prices before September 13, 2022, 02:00 UTC, excluding the incomplete data from September 13. The Vectorbt system is used to simulate the trading, taking into account a buy fee equivalent to 0.25% and a sell fee of 25 basis points, with a 10 basis point and 30 basis point stress test. The results of the training from 2024 to 2025 show a return of -10.124640%, a maximum drawdown of 42.460968%, 7 closed trades, and a win rate of 42.857%. The results of the reset from 2026 show a return of 3.896506%, a maximum drawdown of 17.407810%, 3 closed trades, and a win rate of 0.000%. The stress test return is 2.452493%. The system recorded sensitivities for 15, 20, and 30-day periods, but did not select the best parameter. The calendar holdout is not newly untouched 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, 3 R target, quarter at 2 R, 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 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 headline is not available, this is a raw script output.
This is a description of an automated trading strategy for Ethereum (ETH). The strategy uses a Donchian channel, which is a type of technical indicator, to determine when to buy and sell. It looks at the highest price in the last 20 days and the lowest price in the last 10 days to decide when to enter and exit trades. The strategy only considers complete calendar days and ignores any incomplete days, such as September 13. It also takes into account fees and slippage, which is the difference between the expected and actual prices of a trade. The strategy was tested using data from 2024 to 2025 and resulted in a return of 16.482836%, with a maximum drawdown of 41.890183%. It was also tested on a holdout set of data from 2026 and resulted in a return of -0.011938%, with a maximum drawdown of 22.646338%. The strategy does not use certain risk management techniques, such as a 2 ATR stop or a 3R target. The data used to test the strategy came from 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, and the top 10 surviving strategies were selected.
The C91302 ETH daily control uses a fixed Donchian strategy, which is a type of trading strategy that uses prior highs and lows to make decisions, with a 20-day high entry and a 10-day low exit at the next open. This strategy requires 24 hours of OHLC, or open, high, low, and close, data per day. Prices before September 13, 02:00 UTC are used, but the incomplete data from September 13 is excluded. 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. From 2024 to 2025, the training return was -24.669800%, with a drawdown of 50.548573%, 12 closed trades, and a win rate of 41.667%. In 2026, the known and reused holdout return was -4.530094%, with a drawdown of 17.452215%, 3 closed trades, and a win rate of 0.000%. The stress return was -5.856989%. 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 the open marked position, and the win rate is closed 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 was no fresh high entry across 7 days, 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. This experiment has 156 cells and 26910 to 27075 observations, with a current top 10 survivor selection that limits generalization.
This is a description of a trading strategy for Bitcoin. The strategy uses a Donchian channel, which is a type of technical analysis, to determine when to enter and exit trades. It looks at the highest price in the last 20 days and the lowest price in the last 10 days. If the price reaches a new high, it enters a trade at the next opening price, and if the price reaches a new low, it exits the trade. The strategy only considers prices from before September 13, 2022, at 02:00 UTC, and excludes incomplete data from that day. The Vectorbt backtesting tool was used to simulate the strategy, taking into account fees of 0.25% for buying and 25 basis points for selling, with a 10 basis point to 30 basis point stress test. The results from 2024 to 2025 showed a return of 30.438863% and a maximum drawdown of 34.235134%. In 2026, the return was 18.078296% and the maximum drawdown was 12.151994%. The strategy was tested on 15, 20, and 30-day sensitivities, but no best parameter was selected. The data used for testing is not entirely new and untouched. The return includes the value of any open positions, and the win rate only considers closed trades. This strategy does not require a stop-loss or target profit, and it does not use a specific exit management system. The data for this experiment came from 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, and the current top 10 survivor selection may limit the generalization of the results. A news scan found the headline is not applicable here, this is a raw script output.
This is a description of a trading control for Bitcoin, denoted as C91302. The 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 a prior 10-day low for exit at the next exact open. The control requires 24 hours of OHLC, or open, high, low, and close, data per day, and only considers prices before September 13, 2022, at 02:00 UTC, excluding the incomplete data from September 13. The control also accounts for a coin buy fee equivalent to 0.0025 and a sell fee of 25 basis points, with a slip of 10 basis points and a stress of 30 basis points. The training period from 2024 to 2025 resulted in a return of 32.159105%, a drawdown of 32.756294%, with 10 closed trades and a win rate of 30.000%. The reset period in 2026, using known and reused holdout data, resulted in a return of 18.337791%, a drawdown of 10.253074%, with 2 closed trades and a win rate of 50.000%. The stress return was 17.160774%. 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 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 was no fresh high entry across 7 days, and no late entry. The source of the data is https://runway.adityaperswal.workers.dev/data/crypto-bars and https://docs.alpaca.markets/us/docs/crypto-fees. The experiment consisted of 156 cells with 26910 to 27075 observations, and the current top 10 survivor selection limits generalization.
A news scan found the report of Canaan Inc, a company that issues and manages digital assets, including Bitcoin, which is a type of digital currency. The company reported 31.9 million dollars in revenue and 17.7 million dollars in mining revenue for the second quarter, compared to 20.4 million dollars in mining costs, including 6.3 million dollars in depreciation, which is a reduction in the value of assets over time. This resulted in a 3.6 million dollar mining contribution before depreciation, but not consolidated free cash flow, which is the amount of money available for a company to use. The company also reported an operating loss of 69.5 million dollars. As of September 8, the company held 1915.5 Bitcoins, including 1117 pledged or locked in a fixed-term contract, and 100 fixed-term contracts, meaning the headline coin balance is not fully available for use. On September 8, the company repurchased 7.4 million dollars in shares using 16.4 million American Depositary Shares, which are receipts for shares in a foreign company. On August 4, the company authorized the monetization of digital assets, but the quantity sold was not verified. The return on CAN20, a type of investment, was 57.29 percent, but the price was lower than its high of 0.455. The company's stock price was lower than its high of 0.3666. Hut 8, another company, reported on August 4 that it had contracted 949 megawatts of IT power, with an expected base-term value of 26.6 billion dollars and expected annual net operating income of over 1.75 billion dollars, with 7.5 billion dollars in financing, which are future economics related to artificial intelligence infrastructure, not current Bitcoin margin, which is the difference between the price of Bitcoin and the cost of mining it. Hut 8's stock price was lower than its high of 101.83, and the return on HUT.TO, a type of investment, was -19.62 percent. A counterargument is that cheaper power and new leases could create upside, but this requires paid net cash, debt draw, and asset-specific rules. No order or separate book proposal is possible without a measured net edge, which is the difference between the cost of mining and the price of Bitcoin. The sources of this information are the Securities and Exchange Commission and the companies' websites. On September 11, a direct retrieval of 6,000 shares of Canaan Inc failed, resulting in a current gap, but there is no absence inference, meaning there is no conclusion that the company is absent or inactive.