Transaction fees are the ultimate odds: Insights from a real backtest of a high-frequency crypto strategy

Have you ever wondered why the same strategy can perform vastly differently across various exchanges? A real backtest based on $100,000 principal reveals a harsh truth: in crypto trading, transaction fees are the “universal odds”—they indiscriminately suppress the returns of all strategies, sometimes even determining whether you profit or lose. This is not an exaggeration but a direct insight from the Squeeze Momentum strategy’s one-year operational data on BTC and ETH.

From 0.04% to -50% Loss: How Universal Odds Can Reverse Everything

A complete backtest of the popular TradingView strategy Squeeze Momentum, using Long Only mode, simulated three typical fee scenarios: 0% (ideal baseline), 0.02% (Maker/limit order fee), and 0.06% (Taker/market order fee). The results are a shocking set of data:

15-Minute Time Frame: The Cost Trap of High-Frequency Trading

On the most trading-intensive 15-minute cycle (600-800 trades per year), the power of the universal odds is amplified to the extreme.

This is the true face of the universal odds: a mere 0.04% difference in fees (from 0.02% to 0.06%) causes ETH’s performance to flip from a 47.34% profit to a 13.81% loss. This is not a problem with the strategy itself but a fundamental change in the cost structure that rewrites the game rules.

Can Volatility Overcome Universal Odds?

Behind the data lies an interesting phenomenon: not all assets can withstand the suppression of universal odds.

BTC’s Dilemma: Even with the lowest fee of 0.02%, BTC still loses 14.45% on the 15-minute level. This isn’t because the strategy logic is flawed—at 0% fees, it profits 21.47%. The issue is that BTC’s relatively low volatility (Beta) cannot cover the fixed costs generated by frequent trading. With 600-800 trades annually, each requiring an “entry ticket,” the accumulated costs become an insurmountable gap.

ETH’s Comeback: In contrast, ETH shows stronger explosive power. Its ideal return of 68.66% far exceeds BTC, and this high volatility allows ETH to maintain a 47.34% profit under a 0.02% Maker fee. But once the strategy switches to market orders (0.06% fee), even capturing ETH’s big moves, the accumulated $76,536 in fees can push the account into loss.

Core Insight: Universal odds are more damaging to low-volatility assets. Under fixed fees, volatility becomes the only weapon against cost erosion, but this weapon has a ceiling.

Why Extending the Cycle Doesn’t Save: The Parameter Myth

There’s a common intuition: increasing the time cycle reduces trading frequency, thus diminishing the impact of universal odds. But backtests at the 1-hour level completely overturn this expectation.

Using the same Squeeze Momentum strategy on a 1-hour chart, both assets suffer deep losses (BTC -37.33%, ETH -34.49%). Even more counterintuitive, when ignoring fees entirely (0%), both still lose money (BTC -12.29%, ETH -11.51%).

This counterintuitive phenomenon points to a key insight: parameters are not a universal key. The default parameters (Bollinger Band length 20, standard deviation multiple 2.0) perform well on short cycles but lag significantly on longer ones. When the “compression release” signal confirms on a 1-hour chart, the trend has often already started, leading to entries at local highs and subsequent pullbacks.

This reminds us that blindly applying parameters across different timeframes is highly risky—the universal odds will cause secondary damage when parameters fail.

Cost Structure Determines Life and Death: The Math of Break-Even

Squeeze Momentum is a typical trend breakout strategy, with a generally low win rate (backtests show 26%-40%), relying mainly on risk-reward ratios for profitability. But transaction fees mathematically raise the breakeven point directly.

Take ETH on the 15-minute chart: $76,536 in fees means each trade (regardless of profit or loss) implicitly costs about $92 as an “entry ticket.” This cost doesn’t vanish when you get the direction right; it directly erodes potential profit per trade.

For strategies executing over 600 trades annually, universal odds become the primary factor determining success or failure, rather than the indicator’s predictive power. Worse, continuous wear from high fees accelerates capital depletion. BTC on the 15-minute chart at 0.06% fees can have a maximum drawdown of 58.32%, often leading to liquidation or mental breakdown in live trading.

Practical Strategies to Break the Universal Odds Curse

Since universal odds are an objective reality, how can we survive and profit under this constraint?

Strategy 1: Prioritize Fee Structure

In live trading, strategies that can reliably execute Maker (limit order) trades are more feasible. Implement passive order logic—such as placing orders at the best bid or within the order book—rather than market taker orders. Running such strategies on exchanges with high taker fees (>0.05%) requires extreme caution, as the impact of universal odds is magnified.

Strategy 2: Choose High-Volatility Assets

Compared to BTC, Squeeze Momentum strategies are better suited for ETH or other high-beta altcoins. BTC’s gradually “asset-like” low volatility makes it less cost-effective for short-term breakout strategies. Higher volatility assets can better resist the erosion caused by universal odds.

Strategy 3: Introduce Filtering Mechanisms

Frequent entries in sideways markets are a major source of losses. Incorporate indicators like ADX (e.g., ADX > 20) to confirm trend strength, avoiding trades in choppy markets where universal odds can wear down the strategy. Additionally, before opening on a 15-minute chart, confirm higher timeframe trends (1-hour or 4-hour) are aligned, favoring big trend direction over small fluctuations, reducing ineffective trades.

Strategy 4: Dynamic Parameter Adjustment

Different timeframes require tailored parameters. Optimizing Bollinger Band length (BB Length) and standard deviation multiplier (MultFactor) can reduce signal lag and mitigate chasing high entries, helping to hedge against the suppressive effect of universal odds.

Final Takeaway

As an open-source strategy, Squeeze Momentum’s trend-following logic remains effective. But this backtest clearly shows that success in quantitative trading depends not just on finding a magical indicator but on meticulous control of execution costs and a deep understanding of market microstructure.

In the crypto market, universal odds are quietly waging a “cost war” against all high-frequency traders. Optimizing code is just the first step; optimizing fee tiers, choosing liquidity providers wisely, and precisely controlling trading frequency often have a greater impact on profitability than parameter tuning. Those who can remain profitable under the constraints of universal odds are not necessarily the smartest but the most cost-aware.