Crypto Trading Strategy Daily -> 4h

Marcel Friz,

To fulfill your request we completely rebuild your code, made it long only, removed unnecessary.
If you are satisfied with my answer, please accept it. 
Enjoy

Here are some indicators

Well done Vladimir, and: interesting strategy Marcel Friz  

Vladimir Nice indicator plots! 

Could you please share the code?

.ekz.

Here it is

    def OnData(self, data):
        if self.IsWarmingUp: return

        for pair in self.pairs:  
            symbol = pair.symbol
            price = self.Securities[symbol].Price
            rsi = pair.rsi.Current.Value
            rsi_ema = pair.rsi_ema.Current.Value
            diff = rsi_ema - rsi
            
            self.Plot('RSI', symbol, rsi) 
            self.Plot('RSI EMA', symbol, rsi_ema)

            nma = pair.nma.Current.Value
            nma_ema = pair.nma_ema.Current.Value
            
            self.Plot(symbol, "price", price)
            self.Plot(symbol, "nma", nma) 
            self.Plot(symbol, "nma_ema", nma_ema)

But we need to run each set of indicators separately due to the limitations of the charting capabilities. 

QC,   

For some reason, the Expose plot shows the wrong portfolio exposer, not the same as we calculated it on OnEndOfDay (). 

def OnEndOfDay(self, symbol): 
        account_leverage = self.Portfolio.TotalHoldingsValue / self.Portfolio.TotalPortfolioValue       
        self.Plot('Holdings', 'leverage', round(account_leverage, 2))
        self.Plot('Holdings', 'Target Leverage', LEV)       
        for sec in CRYPTOS: 
            self.real_wt[sec] = round(self.ActiveSecurities[sec].Holdings.Quantity * self.Securities[sec].Price / self.Portfolio.TotalPortfolioValue,4)
            self.Plot('Holdings', self.Securities[sec].Symbol, round(self.real_wt[sec], 4))

Thanks Vladimir!

Hi Vladimir 

Thanks for your time and your effort. 
That's exactly what I was looking for!

Best regards

Marcel

Hello!

Vladimir has contacted support@quantconnect.com to get some clarification on the difference he found on the Expose calculated by QuantConnect/Lean and the values that he has found manually.

Fortunately, the answer is simple: different sampling times. OnEndOfDay is called 10 minutes after the market is closed and our samplings are done at Midnight. Instead of using OnEndOfDay, we should use a Scheduled event:

        self.Schedule.On(self.DateRules.EveryDay(),
            self.TimeRules.Midnight,
            self.MyOnEndOfDay)

with 

    def MyOnEndOfDay(self): 
        if not self.Portfolio.Invested: return
        
        account_leverage = self.Portfolio.TotalHoldingsValue / self.Portfolio.TotalPortfolioValue
        
        self.Plot('Holdings', 'leverage', round(account_leverage, 2))
        self.Plot('Holdings', 'Target Leverage', LEV)
        
        for sec in CRYPTOS: 
            self.real_wt[sec] = round(self.ActiveSecurities[sec].Holdings.Quantity * self.Securities[sec].Price / self.Portfolio.TotalPortfolioValue,4)
            self.Plot('Holdings', self.Securities[sec].Symbol, round(self.real_wt[sec], 4))

Let me note that crypto-currencies markets don't close, so Lean considers that it closes and reopens immediately at midnight.