Alpha

The NullAlphaModel doesn't emit any insights. It's the default Alpha model.

AddAlpha(new NullAlphaModel());

self.add_alpha(NullAlphaModel())

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.

The ConstantAlphaModel always returns the same insight for each security.

AddAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(30)));

self.add_alpha(ConstantAlphaModel(InsightType.PRICE, InsightDirection.UP, timedelta(30)))

The following table describes the arguments the model accepts:

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.

The HistoricalReturnsAlphaModel buys securities that have a positive trailing return and sells securities that have a negative trailing return. It sets the magnitude of the Insight objects to the trailing rate of change.

AddAlpha(new HistoricalReturnsAlphaModel());

self.add_alpha(HistoricalReturnsAlphaModel())

The following table describes the arguments the model accepts:

This model cancels all the active insights it has emit for a security when the security has a 0% historical return.

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.

The EmaCrossAlphaModel uses an exponential moving average (EMA) cross to create insights. When the fast EMA crosses above the slow EMA, it emits up insights. When the fast EMA crosses below the slow EMA, it emits down insights. It sets the duration of Insight objects to be the product of the resolution and fastPeriod arguments.

AddAlpha(new EmaCrossAlphaModel());

self.add_alpha(EmaCrossAlphaModel())

The following table describes the arguments the model accepts:

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.

The MacdAlphaModel emits insights based on moving average convergence divergence (MACD) crossovers. If the MACD signal line is 1% above the security price, the model emits an up insight. If the MACD signal line is 1% below the security price, the model emits a down insight. If the MACD signal line is within 1% of the security price, the model cancels all the active insights it has emitted for the security.

AddAlpha(new MacdAlphaModel());

self.add_alpha(MacdAlphaModel())

The following table describes the arguments the model accepts:

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.

The RsiAlphaModel generates insights based on the relative strength index (RSI) indicator values. When the RSI value passes above 70, the model emits a down insight. When the RSI value passes below 30, the model emits an up insight. The model uses the Wilder moving average type and sets the duration of Insight objects to be the product of the resolution and period arguments.

AddAlpha(new RsiAlphaModel());

self.add_alpha(RsiAlphaModel())

The following table describes the arguments the model accepts:

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.

The BasePairsTradingAlphaModel analyzes every possible pair combination from securities that the Universe Selection model selects. This model calculates a ratio between the two securities by dividing their historical prices over a lookback window. It then calculates the mean of this ratio by taking the 500-period EMA of the quotient. When the ratio diverges far enough from the mean ratio, this model emits generates alternating long ratio/short ratio insights emitted as a group to capture the reversion of the ratio.

AddAlpha(new BasePairsTradingAlphaModel());

self.add_alpha(BasePairsTradingAlphaModel())

The following table describes the arguments the model accepts:

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.

The PearsonCorrelationPairsTradingAlphaModel ranks every pair combination by its Pearson correlation coefficient and trades the pair with the highest correlation. This model follows the same insight logic as the BasePairsTradingModel.

AddAlpha(new PearsonCorrelationPairsTradingAlphaModel());

self.add_alpha(PearsonCorrelationPairsTradingAlphaModel())

The following table describes the arguments the model accepts:

To view the implementation of this model, see the LEAN GitHub repositoryLEAN GitHub repository.