EMA/RSI vs Grid Trading · 6 months of real Coinbase data · Generated 2026-02-24 18:44:23
Solid lines = 15-min · Dashed = 5-min · Grey dashed = $1,000 baseline
| Strategy | Final $ | Return | Trades | Win% | Max DD | Best | Worst |
|---|---|---|---|---|---|---|---|
| ETH 15min | $1,006.14 | +0.61% | 183 | 23.5% | -0.89% | +4.00% | -2.00% |
| ETH 5min | $980.81 | -1.92% | 510 | 21.2% | -3.00% | +4.00% | -2.00% |
| BTC 15min | $996.51 | -0.35% | 172 | 29.1% | -0.84% | +4.00% | -2.00% |
| BTC 5min | $976.14 | -2.39% | 505 | 22.0% | -2.48% | +4.00% | -2.00% |
| SOL 15min | $1,001.07 | +0.11% | 169 | 21.9% | -2.31% | +6.00% | -2.46% |
| SOL 5min | $992.89 | -0.71% | 459 | 22.0% | -2.64% | +6.00% | -1.81% |
| Strategy | Total Cross-Ups | RSI<55 | Min RSI | Avg RSI |
|---|---|---|---|---|
| ETH 15min | 419 | 183 | 48.5 | 56.2 |
| ETH 5min | 1,254 | 510 | 49.1 | 56.4 |
| BTC 15min | 401 | 172 | 49.2 | 56.1 |
| BTC 5min | 1,272 | 505 | 49.0 | 56.4 |
| SOL 15min | 398 | 169 | 49.3 | 56.3 |
| SOL 5min | 1,260 | 459 | 48.8 | 56.5 |
Yellow = RSI 40–55 (entry zone) · Blue = RSI > 55 (filtered out)
The EMA/RSI strategy attempted to buy ETH, BTC, and SOL at moments when short-term momentum appeared to be turning bullish — specifically when the 9-period EMA crossed above the 21-period EMA — while the asset was in a relatively non-overbought state (RSI below 55). The strategy targeted modest 4% gains with tight 2% stop losses (6%/3% for the more volatile SOL), implying a 2:1 reward-to-risk ratio. Positions were traded on both 15-minute and 5-minute candles across a 6-month window of live Coinbase data.
Results ranged from -2.4% to +0.6% over the 6-month period, with win rates hovering between 21% and 29% across all six variants. This is a critical finding: a 2:1 reward/risk strategy requires at least a 33% win rate to break even. Every single variant tested here fell below that threshold, meaning the strategy systematically lost ground to transaction costs and spread even without fees being modeled.
The root cause is signal crowding. EMA crossovers and RSI are among the most widely traded indicators in all of crypto — millions of automated bots and retail algos fire on the same signals simultaneously. This creates a feedback loop where the "edge" of the signal is arbitraged away almost instantly. Short-term 15-minute and 5-minute timeframes amplify this problem: noise dominates signal at that resolution, and EMA crossovers frequently whipsaw in both directions without producing the directional follow-through needed to reach the 4% take-profit target.
Grid range: ±20% from starting price · 10 levels · $80 per grid order · Grey dashed = $1,000 baseline
| Strategy | Final $ | Return | Grid Trades | Realized Grid P&L | Unrealized P&L | Max DD | Start Price | Grid Range |
|---|---|---|---|---|---|---|---|---|
| BTC Grid | $778.63 | -22.14% | 33 | $+46.40 | $-267.77 | -25.29% | $108,827.93 | $87,062.34 – $130,593.52 |
| ETH Grid | $775.07 | -22.49% | 43 | $+68.87 | $-293.80 | -27.48% | $4,374.58 | $3,499.66 – $5,249.50 |
The grid trading strategy deployed $1,000 into each of BTC and ETH, setting up 10 evenly-spaced buy/sell orders across a ±20% price band centered on each asset's starting price. The idea is mechanical and elegant: profit from volatility by automatically buying dips and selling rips within the defined range. Every completed "round trip" (buy at level L, sell at level L+1) generates a small, predictable profit proportional to the grid spacing.
Unfortunately, the backtest period started in late August 2025 near local price highs for both BTC (~$108,800) and ETH (~$4,375). Over the following 6 months, both assets experienced significant drawdowns — BTC and ETH both fell well below the lower bounds of their respective grids for extended periods (BTC: 28 out-of-range days, ETH: 108 out-of-range days). When price exits the grid range entirely, the strategy pauses — no new trades fire, and the account just holds open long positions at a loss. This is the grid strategy's core vulnerability: it turns into an accidental "buy the dip" that keeps holding as the dip becomes a cliff.
The realized grid profits were actually positive ($46 for BTC, $69 for ETH) — confirming the strategy does capture small profits on oscillations within the range. But those profits were overwhelmed by the unrealized loss on open positions stuck below the lower bound. The total return for both strategies landed around -22%, driven almost entirely by the directional bear move rather than any flaw in the grid logic itself.
■ Best EMA/RSI (ETH 15min, +0.61%) · ■ BTC Grid (-22.14%) · ■ ETH Grid (-22.49%) · Grey dashed = $1,000 baseline
| Strategy | Type | Final $ | Return | Max DD | Trades | Verdict |
|---|---|---|---|---|---|---|
| ETH 15min | EMA/RSI | $1,006.14 | +0.61% | -0.89% | 183 | ⚠️ Marginal |
| BTC Grid | Grid | $778.63 | -22.14% | -25.29% | 33 | ❌ Bear market casualty |
| ETH Grid | Grid | $775.07 | -22.49% | -27.48% | 43 | ❌ Bear market casualty |
On pure return, the EMA/RSI strategy's best performer (ETH 15min at +0.61%) dramatically outperformed both grid strategies (-22%) over this 6-month period — but this is largely a story of risk management, not edge. The EMA/RSI strategy's tight stop losses (2%) and small position sizes (10% of balance per trade) meant it could never lose catastrophically. The grid strategy, by contrast, deployed capital into buy orders that became stranded long positions when the market trended down hard.
The comparison reveals a fundamental tension in algo trading: strategies that are "always in the market" (like grids) capture more upside in bull markets but suffer dramatically in bear markets. Strategies with explicit exits (like EMA/RSI with stop losses) sacrifice upside but limit downside. Neither approach generated meaningful returns here — the best result was barely above flat, while the worst lost more than a fifth of the starting balance.
What this backtest really shows is how hard it is to beat a simple buy-and-hold in a volatile trending market, even with sophisticated rules. BTC went from ~$108K to significantly lower over this period — any long-biased strategy that held through that move was going to struggle. The real question for any strategy is not "did it make money in this one period?" but "does it have a verifiable edge that holds across many different market regimes?"