
Not every signal is worth acting on. SPY Hike waits for the right moment and hits the profit 76 out of 100 times. See how a strategy with simple yet robust logic can leave the benchmark behind.

Inspiration
The SPY Hike strategy is designed to capitalize fully on short-term market moves. It is built on simplicity and a logical yet effective approach to setting entry points and managing positions.
Key Components
A long position is opened after the market shows strength
ATR is used to precisely determine the entry level
A dynamic exit condition ensures a quick and effective exit from the position
Backtest 1, Fixed $ Money Management
In this test variant, a fixed amount of $100,000 was invested.
Capital: $100,000
Testing period: 30 years
Date range: 1994 – 06.2025
Tested instrument: SPY





Backtest 2, % Money Management
In this variant, 100% of the current capital was used in the strategy, which means that the value of the position changed proportionally to the account balance.

The equity chart for this test looks as follows. The chart includes a benchmark.

Basic statistics resulting from the test:


Please note that the differences in the results of individual months in the MM$ and MM% tables are due to the separate use of Closed Equity in MM$ vs. Open Equity in MM%.
Net profit and CAGR
Net profit amounted to $4,835,301, representing an annual CAGR of 13.4%. In comparison, SPY achieved $2,222,557 in the same period with a CAGR of 10.7%.
Drawdown and Return/Open Drawdown Ratio
The strategy achieved a lower drawdown level (31%) compared to the benchmark (55%). However, it is not a very small result, which should be taken into account when combining this strategy with others. The profit to open drawdown ratio was 7.5 (SPY: 5.17).
Exposure
The average exposure of the strategy is 53%, which allows it to be used in parallel with other systems without excessive capital utilization.

Winning percent
The effective transaction rate exceeded 76%, indicating a very high accuracy of the adopted entry and exit assumptions.
SL & TP
The strategy does not use traditional SL/TP orders (here's why I often don't use them). If you feel more comfortable with them, you can implement them after conducting tests.
Market regime
The strategy has been tested in all basic market regimes and includes any filters implemented on this basis. Read more about market regimes.
Trading costs
The tests included transaction costs and slippage, using data from the broker Alpaca. You can check our latest research on transaction costs using the broker Alpaca here. With a diversified stock portfolio and strategy, transaction costs can determine your profit or loss, so take the time to thoroughly test and choose a broker.
Robustness
The strategy was tested over a long time horizon on a single instrument (SPY), with a total of 1400 trades. The simple structure of rules and a very limited number of parameters (two entry rules and two optional exit rules) positively affects its robustness.
Additionally, a robustness test was conducted by optimizing the applied parameters, which included 84 different strategy parameter variants. All of them ended with a profit (100% positive results), confirming the system's high robustness to parameter changes. The average profit amounted to $109,824.90, and the best result did not exceed the acceptable limits of statistical deviation. The tests also showed an even distribution of results, with no signs of overfitting.

The SPY Hike strategy demonstrates high effectiveness not only on its primary vehicle, SPY, but also across other widely traded ETFs, underscoring its versatility and robustness in varying market conditions. Back-tests on EWJ, VPU, QQQ, and DIA reveal winning percentages ranging from 70.94% to 75.02%. A hit rate above 70% in every case points to the strategy’s strong potential for generating steady profits. In addition, despite the differing characteristics of each instrument, the strategy preserves favorable parameter values, attesting to its robust risk management.


Recommended Instruments
The strategy was specifically designed for ETF SPY.
Optional: EWJ, VPU, QQQ, DIA
Pattern Day Trader
During the 30-year test period, the strategy generated 1,400 transactions, of which 489 were closed on the same day, although only 3 cases met the PDT classification conditions for the strategy itself. Although the strategy can be used without the need for a minimum balance of $25,000 in a real account, using SPY Hike in a portfolio containing other strategies that close transactions on the same day may lead to meeting PDT conditions. Therefore, if your account is below 25k, consider whether this strategy is suitable for your portfolio! You can check all your strategies and the portfolio using our PDT Finder.

Correlation
To check the correlation of the strategy with others, visit the correlations page.
Summary & Strengths and Weaknesses of the strategy
Strengths of the Strategy
High signal accuracy (over 76% profitable)
Simple and effective entry and exit logic
Outperforms the benchmark in terms of both profit and risk (risk-adjusted return is 25% vs. 10% in the studied period)
The strategy performs well even in declining markets
Weaknesses of the Strategy
The Max Open Drawdown was 31%, which is nearly half less than the benchmark but still worth noting.
There are instances of larger individual losses (the average loss is greater than the average gain), which, however are usually quickly compensated by the strategy's high win rate.
Summary
SPY Hike is a strategy with an exceptionally simple structure but impressive results. High effectiveness, limited exposure, and an advantage over the benchmark make it a solid candidate for an investment systems portfolio.
What you get in the package for this strategy:
Ebook describing detailed rules and results of the strategy.
SQX file 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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