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BTC Sniper Strategy

Quick shot rebound

average rating is 4.1 out of 5

Published:

October 24, 2025

DEVELOPED BY

MICHAŁ ZAREMBA

Experience sniper precision and lightning-fast execution with a strategy that leverages extreme GBTC movements, closing in alignment with market dynamics. Would you like to see the results?

Inspirations


With an inverse correlation to other systems, an impressive 44% CAGR, and low average exposure, it offers a unique risk profile, making it a valuable addition to a portfolio.


Key Components

  • Utilizes BTC volatility to identify potential turning points and fast rebounds.

  • Two rules for Entry and one for Exit, along with excellent results in other markets, confirm the system's robustness.

Backtest 1 - Fixed $ Money Management


As part of this test variant, a fixed amount of $100,000 was invested.

  • Invested capital: $100,000

  • Date range: 06.2015-2025

  • Testing period: 10 years

  • Tested ETF instrument: GBTC

Illustration 1: Capital curve of the strategy from 2015 to the end of 2025 and the corresponding maximum open drawdowns in $. Open Equity is the red line.
Illustration 1: Capital curve of the strategy from 2015 to the end of 2025 and the corresponding maximum open drawdowns in $. Open Equity is the red line.
Illustration 2: Basic statistics and results of the BTC Elite Sniper strategy, month by month (by closed trades).
Illustration 2: Basic statistics and results of the BTC Elite Sniper strategy, month by month (by closed trades).

 In the table, we highlighted the moment when the strategy was published.


Illustration 3: Strategy efficiency in $ month by month (by closed trades).
Illustration 3: Strategy efficiency in $ month by month (by closed trades).
Illustration 4: Graphical representation of the strategy's profit and loss distribution, including monthly, daily, and weekly results, plus transaction statistics and effectiveness by close time.
Illustration 4: Graphical representation of the strategy's profit and loss distribution, including monthly, daily, and weekly results, plus transaction statistics and effectiveness by close time.


Click the button to see the latest backtest:




Backtest 2 - % Money Management


In this variant, 100% of the current capital was used in the strategy, meaning the position value changed in proportion to the account balance.


Illustration 5: Comparison of capital curves of strategy and benchmark for MM%. Yellow lines represent the benchmark.
Illustration 5: Comparison of capital curves of strategy and benchmark for MM%. Yellow lines represent the benchmark.
Illustration 6: Strategy performance table compared to benchmark.
Illustration 6: Strategy performance table compared to benchmark.
Illustration 7: Basic statistics of the strategy with percentage capital management.
Illustration 7: Basic statistics of the strategy with percentage capital management.
Illustration 8: Monthly strategy results as percentages compared to the benchmark (open daily equity is used).
Illustration 8: Monthly strategy results as percentages compared to the benchmark (open daily equity is used).


Trading Strategy Analysis

 

Net Profit & CAGR


The net profit and CAGR of the strategy clearly outperform the SPY, demonstrating a strong pace of capital accumulation with aggressive performance dynamics.


Drawdown & Return/Open Drawdown Ratio


Despite experiencing deeper drawdowns than SPY, the profit-to-open drawdown ratio is more favorable, indicating greater efficiency relative to the risk taken.


Exposure


The strategy's average exposure is 22.76% compared to 100.0% in the benchmark. This difference provides a substantial opportunity to integrate with other systems in the portfolio.


Illustration 9: Max and average daily exposure $ and percentiles.
Illustration 9: Max and average daily exposure $ and percentiles.

Winning Percent


The transaction success rate stands at almost 77%, indicating strong signal quality and consistent short-term rebound performance.


SL & TP


No defined Stop Loss or Take Profit orders are set. The exit condition ensures a swift exit from the position, typically after an average of four days. A Stop Loss can be added based on individual preferences and the strategy's role in the portfolio. You'll be able to learn more about my approach to Stop Loss here.


Market Regime


The strategy has been tested across all fundamental market regimes, incorporating any filters applied accordingly. Read more about market regimes.


Trading Costs


The tests incorporated transaction costs and slippage, utilizing data from the broker Alpaca. You can review our latest research on transaction costs with Alpaca here. With a diversified stock portfolio and strategy, transaction costs can significantly impact your profit or loss, so it's crucial to test and select the right broker.


Robustness


The strategy was tested over the past 10 years on the GBTC instrument, resulting in a total of 138 transactions. Its simple rule structure and minimal parameters, two entry rules and one exit rule, enhance its robustness.

 

The strategy has also proven effective across various ETFs, such as SPY and QQQ, highlighting the universality of the applied rules. To further validate this universality, we conducted additional backtests on:


Illustration 10: Backtest the BTC Sniper strategy on the SPY and QQQ ETFs.
Illustration 10: Backtest the BTC Sniper strategy on the SPY and QQQ ETFs.


Recommended Instruments


The strategy was initially developed for the GBTC ETF, but as demonstrated by the examples above, it is also applicable to other markets.


Pattern Day Trader


The strategy does not meet the Pattern Day Trader (PDT) criteria because, during the tested period, it did not open and close any positions on the same day. This means the strategy can be used without the need to maintain a minimum balance of $25,000 in a real account and without restrictions on the number of trades per day. You can read all about PDT in our article.


Correlation


Strategy is offering a negative monthly correlation to other strategies in our suite, giving a different profile, which can be of great value.



Checking correlation helps prevent duplicating risks in a portfolio and optimizes the combination of systems with different profiles. You can learn more about correlation here.


Summary


Strengths of the Strategy


  • Amazing historical CAGR (44%) delivering an exposure-adjusted return of over 194% is an exceptional result, reflecting the unique history and characteristics of cryptocurrencies. If you believe in BTC's future potential, this strategy is for you.

  • A negative correlation with other strategies in our suite gives this strategy a distinct profile, which can be of great value.

  • High win rate of 77% and an exceptional payout ratio, comparable to the average gain-to-loss ratio in reversal strategies.

  • Low average exposure facilitates integration with other systems within a single portfolio.

Weaknesses of the Strategy


  • Deep drawdowns during open position phases (maximum open drawdown of 55%) require a greater tolerance for volatility and strategic placement within a broader portfolio.

  • Focusing on a single instrument raises specific risk and reliance on that asset's market conditions.

Summary


BTC Sniper focuses on seizing quick rebounds after local supply overloads and capitalizes on the initial strong breakout. The results show a notable edge in CAGR and higher efficiency per unit of drawdown compared to SPY, with much lower exposure. This tactical portfolio module requires accepting larger drawdowns but can deliver rapid capital growth in return.



What you get in the package for this strategy:

 

  • An eBook describing detailed rules and results of the strategy.

  • The SQX file is ready to use on the Algocloud and StrategyQuant platforms.

  • Pseudocode that describes all the rules in an easy-to-understand way.


Disclaimer

 

The results obtained from historical data do not guarantee future outcomes. The effectiveness of a strategy can change over time. Backtesting is a tool that allows for the analysis and evaluation of an investment strategy based on historical data. Various factors, such as market changes or economic conditions, can influence the effectiveness of a strategy over time.

Investing always involves risk. This material is not investment advice. We share our experience and algorithms for educational purposes. We make efforts to ensure that our algorithms are error-free, but neither we nor the tools we use guarantee the absence of technical issues. Any decisions to use a particular strategy are made at your own risk and should be preceded by careful understanding and verification. You should always carefully consider your investment goals and risk tolerance before making investment decisions.

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