Effectiveness of Grid Strategies: Analysis and Test Results
Grid trading strategies are highly popular due to their apparent versatility. However, they are associated with significant risks, especially during prolonged unfavorable price movements. The main issue with grid strategies is that when the price moves against our position, the amount of the loaded deposit increases exponentially. As a result, during a continued adverse market movement, the deposit load can reach 100-fold or even higher levels.
There are many variations of averaging algorithms, including percentage-based, dynamic, time-based, and other methods. However, sooner or later, any algorithm will encounter a situation where the price continues to decline, preventing the position from being closed in the positive zone. In this article, we explore the effectiveness of a grid strategy based on averaging when the price drops by a certain percentage.
Testing Conditions and Goals
For the analysis, the difficult market year of 2022 was chosen, characterized by high volatility and prolonged downward price movements. Analyzing "favorable" years, where strategies show outstanding results, is not meaningful in this context. Our goal is to evaluate the strategy's behavior under maximum risk conditions.
Testing period: 2022
Instruments: BTC, BCH, ETH
Algorithm: Averaging when the price drops by a certain percentage (rbPercent), which will be optimized.
Initial market entry: $100
Test Results
The graphs show the test results for the selected coins:
Bitcoin (BTC):
Ethereum (ETH):
Bitcoin Cash (BCH):
Interpretation of Results
Let's analyze the results for the Bitcoin Cash (BCH) coin with the parameter rbPercent = 7. The calculations use a leverage of 50 (some exchanges allow leverage up to 100, but such pairs are rare, and exchanges often reduce leverage by setting position size limits).
- Maximum position: $15,435.09. With a leverage of 50, our balance should be $15,435.09 / 50 = $309.
- Maximum drawdown: $1,707.93. The deposit should be $1,707.93 + 10% (for margin call) = $1,876.
- Profit: $480.73 - $57.2 = $423 (22%).
This result is unsatisfactory because the risk is disproportionate to the reward. For grid strategies, the minimum profit should be 110% for the expected value to be positive. Additionally, the recovery factor (RF) is 0.28, indicating that the strategy may not recover at some point and risks losing more money than it earns.
Key Conclusions
The effectiveness of a grid strategy depends on the deposit's ability to withstand maximum drawdowns when the price moves against the position. In most cases, positions aren't heavily loaded, but during deep drawdowns, significant additional investments may be required.
When optimizing parameters across different instruments, the following observations were made:
- Bitcoin (BTC): The maximum drawdown occurred at rbPercent = 11.
- Ethereum (ETH): The worst drawdown was recorded at rbPercent = 13, and the maximum deposit load occurred at rbPercent = 5.
It is important to note that even though Bitcoin performed well with rbPercent = 5% in 2022, this does not guarantee similar behavior in, for example, 2025. Volatility and market conditions constantly change, making precise parameter tuning difficult.
One interesting result from optimization was that with rbPercent = 9%, all strategies showed moderate results. This suggests the potential of batch trading—testing a large number of coins simultaneously—which will be discussed in more detail in the next article.
RF Interpretation
RF 0.5 - The strategy recovers only half of its losses. Low efficiency, likely to experience sustained losses.
RF 0.75 - The strategy recovers about 75% of its losses. Optimization is required to improve efficiency.
RF 1 - The strategy recovers all losses but does not generate extra profit. On the edge of sustainability.
RF 1.5 - The strategy recovers 1.5 units of profit for every unit of loss. Moderately effective strategy.
RF 2 - The strategy recovers twice as much profit as it loses. Highly effective and sustainable strategy.
