DASHUSDT
Crypto market · BinanceDASH · DASH Quantitative Strategy Analysis: Evaluating a Low-Frequency, Extended-Hold System on 15-Minute Data
This empirical evaluation dissects the historical performance profile of the quantitative trading strategy for DASH · DASH operating on 15-minute price data across a 6.09-year observation period from June 2020 through August 2026. Despite its intraday data feed, the system functions as a selective swing-to-position trading model, executing just 60 completed trades over six years at an average rate of 9.86 trades per year. The statistical evidence reflects a high win rate of 73.33 percent paired with an average trade return of +10.55 percent and a profit factor of 3.13. Holding periods average 323.67 hours (13.49 days) with exits occurring roughly once every 36.10 days. Risk metrics reveal a maximum historical drawdown of 37.83 percent and a worst single trade of -32.44 percent, highlighting significant open-market exposure during position holding. Recent execution since June 1, 2024, accounts for 22 completed trades generating a cumulative +229.96 percent return, demonstrating continued sample activity across varying market cycles.
Analysis as of 22.08.2026. Strategy data is updated separately.Read full analysis
Strategy profile
The quantitative trading system designated for DASH · DASH evaluates 15-minute price activity within the cryptocurrency market to generate position signals. Operating across a historical dataset spanning 6.09 years from June 30, 2020, to August 1, 2026, the strategy recorded a total of 60 completed round-trip trades. This results in a overall historical cumulative trade return sum of 15,271.71 percent across all closed positions, corresponding to a high mathematical annualized rate under constant compounding models. Within DevioLab's comparative ranking architecture, the strategy achieves a DevioLab score of 62.19, ranking it 6th among strategies evaluated for the DASH ticker. The operational footprint is characterized by exceptional selectivity; despite processing high-frequency 15-minute data bars, the strategy executes fewer than ten trades per calendar year on average. This stark contrast between bar frequency and trade generation indicates a filter structure that ignores minor intraday fluctuations, requiring substantial structural market setups before committing capital. The broad parameters indicate a strategy built around extended position holding rather than rapid turnover.
Trading rhythm and position duration
Analyzing the temporal dynamics of the strategy reveals a distinct long-horizon profile that diverges sharply from conventional intraday 15-minute systems. Over the 6.09-year evaluation history, the system averaged 9.86 completed trades per year, which translates to approximately 1.36 trades per active calendar month. The spacing between trade exits reflects this low frequency, with an average interval between exits of 36.10 days and a median interval of 28.02 days. In practice, long stretches of market monitoring occur without trade terminations. When positions are initiated, holding times are remarkably extended. The average position holding duration spans 323.67 hours, or approximately 13.49 days, while the median holding duration sits at 182.13 hours, or roughly 7.59 days. The divergence between median and average holding times demonstrates a positively skewed distribution, indicating that while typical positions resolve within one to two weeks, a subset of trades remains open for multiple weeks to fully capture persistent price trends. The strategy consequently exposes capital to multi-day macro price movements while entirely bypassing short-term market noise.
Quality of historical results
The statistical distribution of closed trade outcomes points to a robust historical payoff architecture characterized by consistent baseline profitability and balanced gain distribution. Out of 60 completed trades, 44 resulted in positive returns while 16 ended in losses, yielding a overall win rate of 73.33 percent. The profit factor stands at 3.13, indicating that gross profits generated by winning positions were more than three times larger than the gross losses incurred by losing positions. Expected value per trade is strong, with an average trade return of +10.55 percent and a median trade return of +8.47 percent. The close alignment between average and median outcomes demonstrates that profitability is grounded in structural expectation rather than being distorted by isolated extreme outcomes. Furthermore, the top three largest winning trades cumulatively accounted for 21.34 percent of total gross profits. This moderate concentration ratio confirms that while large trend rides occur—exemplified by a best single trade return of +67.36 percent—the strategy does not rely exclusively on a handful of anomalous trades to maintain profitability.
Risk, drawdown and losing behavior
While the strategy exhibits strong historical win metrics, its downside profile underscores the inherent volatility of extended holding periods in cryptocurrency markets. The maximum historical drawdown reached 37.83 percent, representing a material capital decline during unfavorable market regimes. This equity drop aligns logically with the strategy's worst single trade loss of -32.44 percent, demonstrating that individual position adverse excursions can exert meaningful pressure on portfolio values. The strategy's risk mitigation primary strength rests in its execution consistency and short losing sequences: the longest consecutive losing streak observed across the entire 6.09-year history was limited to just 2 trades, whereas the longest winning streak extended to 8 consecutive positive trades. However, because position holding times average over 13 days, a single losing trade can subject capital to several weeks of open drawdowns. The risk profile is therefore characterized not by frequent small paper cuts, but by infrequent, deep price retracements during broad market reversals.
Behavior through time and yearly stability
A year-by-year examination of closed trade performance illustrates how the strategy navigated distinct crypto market cycles from 2020 through mid-2026. In 2020, during the initial half-year sample, the strategy completed 3 trades (2 wins, 1 loss) for a win rate of 66.67 percent and a net trade sum of -0.79 percent. The system captured its largest aggregate returns during 2021, generating +214.31 percent across 14 trades with a 71.43 percent win rate. Performance remained positive during the 2022 bear market environment, producing +82.29 percent across 11 trades with a 72.73 percent win rate, illustrating resilience during broader sector declines. In 2023, trade frequency slowed to 5 trades, but efficiency rose to an 80.00 percent win rate and +81.76 percent total return. Calendar year 2024 delivered 9 trades with an 88.89 percent win rate yielding +117.58 percent, followed by 2025 which saw 12 trades, a 75.00 percent win rate, and +116.33 percent in cumulative returns. In the partial year of 2026 up to August 1, the system recorded 6 trades with a 50.00 percent win rate and +21.24 percent net return. Aside from the minor negative start in 2020, every full calendar year delivered positive net closed trade performance.
Recent period since 2024-06-01 versus full history
Evaluating performance in the recent sample window beginning June 1, 2024, provides insight into how the strategy has functioned under contemporary market conditions. Within this sub-period, 22 completed trades were recorded, accounting for more than one-third of the total 60 trades observed across the entire 6.09-year history. These recent trades produced a cumulative closed return sum of +229.96 percent. The heightened trade generation rate during this recent interval—22 trades over approximately 26 months—reflects a slightly higher operational pacing compared to the historical full-sample average of 9.86 trades per year. The historical evidence demonstrates that the strategy's high-win, extended-hold logic remained active and capable of capturing multi-day price expansions throughout the recent 2024 to 2026 market phase. The substantial sample of 22 recent trades confirms that the strategy's recent historical record is backed by direct trade completions rather than sparse or stale historical observations.
Strengths and limitations
The analytical evidence highlights clear structural advantages alongside undeniable trade-offs. Primary strengths include a high historical win rate of 73.33 percent, an exceptional profit factor of 3.13, and a well-distributed payoff structure where the top three trades account for only 21.34 percent of gross profit. Short losing streaks capped at 2 trades provide psychological and operational stability. Conversely, primary limitations center around sample size and deep position exposure. With only 60 total completed trades over six years, statistical power is constrained compared to high-frequency models. Furthermore, an average holding duration of 323.67 hours paired with a worst trade of -32.44 percent and a maximum drawdown of 37.83 percent means positions remain vulnerable to major overnight volatility and swift adverse trend shifts. The low frequency of roughly 9.86 trades per year also demands patience, as multi-month periods can elapse with minimal closed trade activity.
DevioLab analytical conclusion
The quantitative profile of DASH 215000 +13374.71% 1TRAD-GNM1 on DASH · DASH represents an intriguing paradox: it utilizes a fine 15-minute data granularity to execute a slow, macroeconomic-style position holding strategy. Achieving a DevioLab score of 62.19 and ranking 6th for its asset, the system relies on high signal filtering to achieve a 73.33 percent win rate and a +10.55 percent average return per trade. Its historical performance shows consistent multi-year profitability across bull and bear crypto regimes, reinforced by a robust recent period contributing +229.96 percent across 22 trades since mid-2024. However, market participants evaluating this historical research must account for the substantial 37.83 percent maximum drawdown and the extended holding times averaging nearly two weeks per position. The system's edge historically stems from capturing large multi-day structural trends while tolerating severe price swings within open positions.
Data scope and methodology
This analysis is based entirely on historical backtested closed trade statistics for the strategy on DASH · DASH across 15-minute price data covering June 30, 2020, through August 1, 2026. All cited metrics—including completed trades, win rates, drawdowns, holding durations, profit factors, and annual breakdowns—reflect mathematical summaries of simulated closed positions. Transaction fees, execution slippage, funding costs, and live order book dynamics are not modeled in these historical figures unless explicitly noted. The metrics presented describe historical simulated performance and do not constitute financial advice, investment recommendations, or guarantees of future performance.