Direct answer
Strategy hopping is a decision pattern where someone repeatedly stops one set of trading rules and starts another, usually because performance or conditions look different than expected. In a worked example, the goal is not to predict future profit, but to show—numerically—how outcomes can change when the rules change.
Mechanism and definition (what changes when you hop)
To make the term concrete, treat a “strategy” as a rule-set that determines, for example, entry timing, exit timing, stop distance, take-profit distance, and position sizing. “Hopping” means those rules are altered between trades (or between periods) even though the market is still the same underlying instrument and price process.
A worked example should separate stable mechanics from variable conditions:
- Stable mechanics: your accounting method (e.g., per-trade profit/loss), transaction cost model, and fixed position size per trade (unless stated otherwise).
- Variable conditions: the chosen strategy’s expected price movement and the realized move during each trade window, plus costs and execution differences.
Because the reader should be able to independently verify the arithmetic, every calculation must declare assumptions such as fixed spread/commission per trade and whether you assume full fills.
Worked numerical example (with explicit assumptions)
Below is one transparent scenario with a sequence of five trades. It shows how switching strategies mid-sequence can change total results.
Assumptions
- Trades are independent for bookkeeping, with identical position size each time: 1,000 units.
- Profit/loss is measured in “price units per position,” using a simplified conversion: P&L = (exit_price − entry_price) × units.
- Each trade has the same transaction cost modeled as a fixed loss of 0.20 price units (already converted into P&L units per the same simplified scheme). This is a modeling assumption.
- Strategy A and Strategy B differ only in the assumed realized move they “aim for” through their rules:
- Strategy A rule-set: attempt to capture a +0.60 price-unit move per trade when conditions align.
- Strategy B rule-set: attempt to capture a +0.30 price-unit move per trade when conditions align.
- We are not claiming these are true forecasts. We are using them to generate a scenario and then computing results.
Scenario
Realized moves (what actually happened in this hypothetical sequence):
- Trade 1: +0.60
- Trade 2: +0.60
- Trade 3: +0.30
- Trade 4: +0.30
- Trade 5: +0.60
Strategy choice (this is the “hopping” part):
- Trades 1–2 use Strategy A.
- Trades 3–5 switch to Strategy B.
Calculations
Per trade, simplified P&L = (realized move) × 1,000 − 0.20 × 1,000.
- Trade 1: 0.60×1,000 − 0.20×1,000 = 600 − 200 = +400
- Trade 2: +400
- Trade 3: 0.30×1,000 − 0.20×1,000 = 300 − 200 = +100
- Trade 4: +100
- Trade 5 (even though realized move is +0.60): 0.60×1,000 − 0.20×1,000 = +400
Total P&L for the sequence = 400 + 400 + 100 + 100 + 400 = +1,400 (in the simplified units).
What this example is meant to show
If you kept Strategy A for all five trades under the same realized moves and same cost model, trades where realized move is only +0.30 would still produce: 0.30×1,000 − 200 = +100 (same arithmetic), but a full real-world strategy difference would likely alter exits and therefore realized move distribution. In other words, the example isolates “rule switching” as the key variable and demonstrates that even in a simple model, results depend heavily on realized moves, costs, and how your rules map to those moves.
Limitations and risks (failure modes you can verify)
Even when the arithmetic is correct, strategy hopping has material limitations:
- Overfitting to recent outcomes: switching rules after observing a short streak can make the selection look good by chance rather than by stable performance. 2) Hidden inconsistencies: if position sizing, stop/limit placement, or execution assumptions change between strategies, then comparing totals becomes misleading. 3) Transaction costs and slippage sensitivity: frequent switching can increase trade frequency or make exits less favorable, and costs can dominate small edge.