Hello fellows, I´m new in LEAN and I have the next question:

How can I use the RelativeStrenghtIndex indicator in order to filter the universe selection, In the Bootcamp, there is a similarity

but whit EMA conditions, but I have no clue how to replicate it but just with RSI or another indicator such as MACD for example that have many variables to fill, no just the numbers of bar to take in consideration.

class EMAMomentumUniverse(QCAlgorithm): def Initialize(self): self.SetStartDate(2019, 1, 7) self.SetEndDate(2019, 4, 1) self.SetCash(100000) self.UniverseSettings.Resolution = Resolution.Daily self.AddUniverse(self.CoarseSelectionFunction) self.averages = { } def CoarseSelectionFunction(self, universe): selected = [] universe = sorted(universe, key=lambda c: c.DollarVolume, reverse=True) universe = [c for c in universe if c.Price > 10][:100] for coarse in universe: symbol = coarse.Symbol if symbol not in self.averages: # 1. Call history to get an array of 200 days of history data history = self.History(symbol, 200, Resolution.Daily) #2. Adjust SelectionData to pass in the history result self.averages[symbol] = SelectionData(history) self.averages[symbol].update(self.Time, coarse.AdjustedPrice) if self.averages[symbol].is_ready() and self.averages[symbol].fast > self.averages[symbol].slow: selected.append(symbol) return selected[:10] def OnSecuritiesChanged(self, changes): for security in changes.RemovedSecurities: self.Liquidate(security.Symbol) for security in changes.AddedSecurities: self.SetHoldings(security.Symbol, 0.10) class SelectionData(): #3. Update the constructor to accept a history array def __init__(self, history): self.slow = ExponentialMovingAverage(200) self.fast = ExponentialMovingAverage(50) #4. Loop over the history data and update the indicators for data in history.itertuples(): self.fast.Update(data.Index[1], data.close) self.slow.Update(data.Index[1], data.close) def is_ready(self): return self.slow.IsReady and self.fast.IsReady def update(self, time, price): self.fast.Update(time, price) self.slow.Update(time, price)

In the SelectionData class, the Bootcamp example places the ExponentialMovingAverage with just one parameter, the bar number to be considered for calculating it, but how can I set up this with other indicators such as RSI, or MACD that have many others variables to fill.


Thanks a lot!