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
A smart system for an ETF on BTC that accurately identifies pullbacks and exits after the first significant rebound. Instead of pursuing long trends, this strategy targets quick, statistically repeatable retracement moves. With an inverse correlation to other systems, an impressive 46% 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: 2015-31.10.2025
Testing period: 10 years
Tested ETF instrument: GBTC
Backtest 2, % Money Management
In this variant, 100% of the current capital was utilized in the strategy, meaning that the value of the position changed proportionally to the account balance.
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
Due to the nature of the BTC, the strategy may experience a much larger drawdown than usual. It is recommended to incorporate it within a broad portfolio of low-correlated strategies.
Exposure
The strategy's average exposure is 22.0%, compared to 100.0% in the benchmark. This difference provides a substantial opportunity to integrate with other systems in the portfolio.
Winning Percent
The transaction success rate stands at 77%, indicating strong signal quality and consistent short-term rebound performance.
SL & TP
No defined Stop Loss or Take Profit orders are set inside the strategy. 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 your 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 135 transactions. Its simple rule structure and minimal parameters, two entry rules and one exit rule, enhance its robustness.
The same strategy also proves effective across various ETFs, including indices, underscoring the universality of the applied rules. To further validate the strategy's universality, we conducted additional backtests on:
The 100 most popular ETFs:
On SPY:
On QQQ:
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 maintaining 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 (46%) delivering an exposure-adjusted return of over 208% 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 76% 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 Elite 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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