Rsrs

class backtide.strategies.Rsrs(period=18)

Resistance Support Relative Strength trend-detection strategy.

Uses linear regression of high vs. low prices (Resistance Support Relative Strength) to detect when support is strengthening. Buys when the RSRS indicator signals that the support floor is rising faster than resistance, indicating a potential upward breakout. Useful for quantitative trend detection based on price structure.

Parameters	period : int, default=18 Look-back window for the linear regression.
Attributes	name : str Human-readable strategy name. is_multi_asset : bool Whether this is a multi-asset strategy.

Methods

description	Short explanation of what the strategy does.
evaluate	Evaluate the strategy and return orders.
required_indicators	Indicators that must be computed up-front for this strategy.

method description()

Short explanation of what the strategy does.

Returns

str

The description.

method evaluate(data, portfolio, state, indicators=None)

Evaluate the strategy and return orders.

Parameters

data : dict[str, np.array | pd.DataFrame | pl.DataFrame]

Keys are the experiment's symbols and values are the historical OHLCV data available up to the current bar.

portfolio : Portfolio

Current portfolio holdings (cash, positions and open orders).

state : State

Current simulation state.

indicators : dict[str, dict[str, np.array | pd.DataFrame | pl.DataFrame]] | None

The first keys are the indicator names. The second keys are the experiment's symbols. The values are the pre-computed indicator values. None if no indicators were selected.

Returns

list[Order]

Orders to place this tick.

method required_indicators()

Indicators that must be computed up-front for this strategy.

Returns a list of indicator instances, already parameterized with this strategy's current settings, that the engine will auto-include before the backtest starts.

Returns

list[BaseIndicator]

The required indicator instances.