Loading US stock market status…
➜
HOW TO START
Complete the full system setup in just a few minutes.
Open Quick Start Guide →
Public catalog · DEVIOLAB

TRADING STRATEGIES & BOTS

Choose a trading strategy and activate a bot that will trade automatically by its rules.
A strategy defines the buying and selling rules. A trading bot executes those rules through the API of a supported exchange. You can also use the selected strategy as a signal bot with Telegram and email notifications.
FILTERS
Choose Core 1 for a balanced start, select an exchange for trading and find the ticker you need. Filters work together.
Trading exchange?Shows instruments available for SPOT trading against USDT according to the latest normalization. Click the selected exchange again to show all exchanges.
Selected strategy overview

CAKEUSDT

Crypto market · Binance
CAKE 215000 +14118.35% 1TRAD-HXN3
Archived strategy
98Trades
74.5%Win rate
+6.77%Avg trade
+71.14%Best trade
-44.63%Worst trade
+141.0%Annualized
Strategy analytical profile · 9c7a3256c325a65b

Quantitative Strategy Analysis: CAKE · CAKE 15m Timeframe Evaluation

Comprehensive quantitative evaluation of the CAKE algorithmic strategy across 5.48 years of historical data, highlighting a cumulative return of 14118.35%, a 74.49% win rate, and a 57.44% maximum drawdown across 98 completed trades.

Analysis as of 13.08.2026. Strategy data is updated separately.
Read full analysis

Strategy profile

The CAKE trading strategy, designated as CAKE 215000 +14118.35% 1TRAD-HXN3, is designed for the spot cryptocurrency market on a 15-minute timeframe. Over the complete historical testing window of 5.48 years between February 19, 2021, and August 13, 2026, the algorithm achieved an overall cumulative gain of 14118.35%, representing an annualized performance of 141.02%. It holds a DevioLab score of 37.53, ranking second among available configurations for the CAKE asset. The system completed 98 trades over the entire dataset, reflecting a selective approach to trade generation.

Trading rhythm and position duration

Although the algorithm evaluates market price action on 15-minute chart intervals, it registers an average frequency of approximately 17.88 trades per year. This demonstrates a macro swing or position-style hold rather than intraday scalping. Detailed metrics for average holding hours and median days between exits are not recorded in the available dataset. However, executing only 98 trades across nearly 5.5 years confirms that entry triggers are strict and designed to filter out short-term noise.

Quality of historical results

The historical performance comprises 73 winning trades against 25 losing trades, producing a high win rate of 74.49%. The overall profit factor stands at 2.50, demonstrating that cumulative gross profits were two and a half times greater than cumulative gross losses. The average trade gain was 6.77%, with a median trade return of 7.39%. Return concentration is notably well-balanced: the top three winning trades generated just 16.35% of total gross profit, despite the single best trade returning 71.14%. This confirms that long-term profitability was driven by broad consistency rather than an isolated fortunate trade.

Risk, drawdown and losing behavior

While cumulative returns are high, the strategy carries significant historical exposure to drawdowns. Peak-to-trough equity decline reached 57.44%, and the worst single trade loss recorded was -44.63%. Losing periods remain infrequent, as evidenced by a maximum losing streak of only 2 trades compared to a maximum winning streak of 13 trades. Nevertheless, the magnitude of the maximum loss shows that open positions can experience substantial adverse movement prior to trade closure.

Behavior through time and yearly stability

Over the 5.48-year evaluation history, specific year-by-year performance breakdowns are omitted in the source statistical dataset. Nevertheless, the total trade volume of 98 completed signals across the timeline indicates a steady baseline rhythm of roughly 17.88 trades annually. Given the low trade frequency, periods of extended inactivity between trades are a structural characteristic of this quantitative model.

Strengths and limitations

Primary strengths of this strategy include its 74.49% win rate, a strong profit factor of 2.50, and a healthy profit structure where the top 3 trades account for only 16.35% of gross profits. Its main limitations lie in downside risk parameters, marked by a 57.44% max drawdown and a worst trade of -44.63%. Furthermore, the overall sample size of 98 trades over 5.48 years is relatively compact, and zero signals since June 2024 highlight operational inactivity in recent market conditions.

DevioLab analytical conclusion

Carrying a DevioLab score of 37.53 and a rank of 2 for CAKE, this algorithm highlights a strong historical edge combined with high return capture. While its high win rate and consistent gain distribution are major strengths, the elevated maximum drawdown of 57.44% and recent trade inactivity require disciplined risk management.

Data scope and methodology

This analysis is based on historical backtested trade results for CAKE from February 19, 2021, to August 13, 2026, calculated on 15m spot market data. All quoted metrics describe past simulated performance, do not reflect live execution on an exchange account, and offer no guarantee of future trading performance.

Full strategy analysis