Strategy Parameters Explained

Entry rules

Entry rules define the conditions that trigger a new position. These can be based on price levels, indicator values, pattern recognition, or combinations thereof. The key design decision is specificity — rules that are too loose generate too many trades (high commission drag, low selectivity), while rules that are too tight generate too few trades (insufficient statistical sample).

• Common entry rule types:
• Price crosses above/below a moving average
• Indicator reaches an overbought/oversold threshold
• Breakout above/below a defined range
• Combination of multiple conditions (all must be true simultaneously)

Exit rules

Exit rules define when an open position is closed. Multiple exit rules can coexist — the first one triggered closes the position.

• Stop loss — closes the position at a defined loss threshold to limit downside. This is the most important risk management parameter.
• Profit target — closes the position at a defined gain threshold to lock in profit
• Time-based exit — closes the position after a defined number of periods regardless of profit or loss
• Signal-based exit — closes the position when entry conditions reverse or a separate exit signal triggers

Position sizing

Position sizing determines how much capital is allocated to each trade. This parameter has an outsized impact on backtest results — the same entry and exit rules can produce dramatically different outcomes depending on position size.

• Common approaches:
• Fixed percentage — risk a fixed percentage of current equity per trade (e.g., 2%)
• Fixed amount — risk a fixed dollar amount per trade
• Volatility-adjusted — adjust position size based on current market volatility (larger positions in calm markets, smaller in volatile markets)

Timeframe

Timeframe has two components:

• Data resolution — the granularity of each data period (daily, hourly, etc.). Higher resolution means more data points and potentially more trades, but also more noise.
• Historical window — how far back the test runs. Longer windows provide more statistical significance but may include market regimes that no longer apply.

Parameter sensitivity

A robust strategy should produce reasonable results across a range of parameter values, not just at one specific setting. If changing a stop loss from 2% to 2.5% transforms a winning strategy into a losing one, the strategy is fragile and likely overfit to the specific parameter choice. SDB's multi-configuration comparison (Pro) helps identify parameter sensitivity.