# https://quantpedia.com/strategies/trading-commodity-calendar-spreads/
#
# The investment universe consists of 20 commodity futures (first 12 months for each commodity are used for signal generation and trading).
# Each month, the investor determines the shape of the futures curve for each commodity by taking the difference of the first five contracts, 
# sums the differences and then takes an average of the sum (if the result is positive, then the curve is in backwardation, and if negative, 
# then the curve is in contango).
# In the case of backwardation, the investor takes a long position into the contract ‘most’ backwarded (he does it by taking the largest value 
# of differenced contracts, and once the contracts have been determined with the largest difference in price, in the case of backwardation a 
# long position is taken onto the further contract). The short position is determined by taking the smallest value of differenced contracts.
# When the curve is in contango, the process is the same but reversed. The investor takes a short position into the largest difference and 
# a long position into the smallest difference. The portfolio is equally weighted between 20 commodities and rebalanced once a month.

import numpy as np

class TradingCommodityCalendarSpreads(QCAlgorithm):
    
    def Initialize(self):
        self.SetStartDate(2010, 1, 1)
        self.SetCash(500000)
       
        # 1st contract and the number of contracts to approximately 12 months away.
        self.contracts = {
                        # "CHRIS/CME_S" :  8,  # Soybean Futures, Continuous Contract
                        # "CHRIS/CME_W"  : 6,  # Wheat Futures, Continuous Contract
                        # "CHRIS/CME_SM" : 9,  # Soybean Meal Futures, Continuous Contract
                        # "CHRIS/CME_BO" : 9,  # Soybean Oil Futures, Continuous Contract
                        # "CHRIS/CME_C" :  6,  # Corn Futures, Continuous Contract
                        # "CHRIS/CME_O" :  6,  # Oats Futures, Continuous Contract
                        "CHRIS/CME_LC" : 7,  # Live Cattle Futures, Continuous Contract
                        "CHRIS/CME_FC" : 7,  # Feeder Cattle Futures, Continuous Contract
                        "CHRIS/CME_LN" : 9,  # Lean Hog Futures, Continuous Contract
                        # "CHRIS/CME_GC" : 9,  # Gold Futures, Continuous Contract
                        # "CHRIS/CME_SI" : 9,  # Silver Futures, Continuous Contract
                        # "CHRIS/CME_PL" : 7,  # Platinum Futures, Continuous Contract
                        # "CHRIS/CME_CL" : 12, # Crude Oil Futures, Continuous Contract
                        # "CHRIS/CME_HG" : 13, # Copper Futures, Continuous Contract
                        # "CHRIS/CME_LB" : 7,  # Random Length Lumber Futures, Continuous Contract
                        # "CHRIS/CME_NG" : 12, # Natural Gas (Henry Hub) Physical Futures, Continuous Contract
                        # "CHRIS/CME_PA" : 7,  # Palladium Futures, Continuous Contract 
                        # "CHRIS/CME_RR" : 7,  # Rough Rice Futures, Continuous Contract
                        # "CHRIS/CME_CU" : 13, # Chicago Ethanol (Platts) Futures
                        # "CHRIS/CME_DA" : 13, # Class III Milk Futures
                        
                        # "CHRIS/ICE_CC" : 6,  # Cocoa Futures, Continuous Contract 
                        # "CHRIS/ICE_CT" : 6,  # Cotton No. 2 Futures, Continuous Contract
                        # "CHRIS/ICE_KC" : 6,  # Coffee C Futures, Continuous Contract
                        # "CHRIS/ICE_O" :  13, # Heating Oil Futures, Continuous Contract
                        # "CHRIS/ICE_OJ" : 7,  # Orange Juice Futures, Continuous Contract
                        # "CHRIS/ICE_SB" : 5   # Sugar No. 11 Futures, Continuous Contract
                        }
                        
        # CONTRACT_VALUE = {}
        # CONTRACT_VALUE['CHRIS/CME_PL1'] = ["PLATIUM", 50,0.10,1]
        # CONTRACT_VALUE['CHRIS/CME_PL2'] = ["PLATIUM", 50,0.10,1]
        # CONTRACT_VALUE['CHRIS/CME_PL3'] = ["PLATIUM", 50,0.10,1]
        # CONTRACT_VALUE['CHRIS/CME_PL4'] = ["PLATIUM", 50,0.10,1]
        # CONTRACT_VALUE['CHRIS/CME_PL5'] = ["PLATIUM", 50,0.10,1]
        # CONTRACT_VALUE['CHRIS/CME_PL6'] = ["PLATIUM", 50,0.10,1]
        # CONTRACT_VALUE['CHRIS/CME_PL7'] = ["PLATIUM", 50,0.10,1]

        self.rebalance_flag = True
        
        for future, future_count in self.contracts.items():
            for index in range(1, future_count + 1):
                contract = future + str(index)
            
                data = self.AddData(QuandlFutures, contract, Resolution.Daily)
                data.SetFeeModel(CustomFeeModel(self))
                data.SetLeverage(5)
        
        self.Schedule.On(self.DateRules.MonthStart('CHRIS/CME_LC1'), self.TimeRules.AfterMarketOpen('CHRIS/CME_LC1'), self.Rebalance)

    def Rebalance(self):
        self.rebalance_flag = True
        
    def OnData(self, data):
        if not self.rebalance_flag:
            return
        self.rebalance_flag = False
        
        long = []
        short = []

        for future, future_count in self.contracts.items():
            # curve_shape = sum( np.diff( [ self.Securities[future + str(index)].Price for index in range(1, 6) if self.Securities.ContainsKey(future + str(index)) ] ) )
            curve_shape = sum( np.diff( [ data[future + str(index)].Value for index in range(1, 6) if (future + str(index)) in data ] ) )
            curve_shape /= future_count
            if curve_shape != 0:
                # diff = np.diff( [ self.Securities[future + str(index)].Price for index in range(1, future_count + 1) if self.Securities.ContainsKey(future + str(index)) ] )
                diff = np.diff( [ data[future + str(index)].Value for index in range(1, future_count + 1) if (future + str(index)) in data ] )
                abs_diff = [abs(x) for x in diff]
                max_diff_index = abs_diff.index(max(abs_diff))
                min_diff_index = abs_diff.index(min(abs_diff))
                
                # Offset index by 2 to get right symbols to trade.
                max_diff_index += 2
                min_diff_index += 2
                
                if curve_shape > 0:
                    # Backwardation.
                    long.append(future + str(max_diff_index))
                    short.append(future + str(min_diff_index))
                else:
                    # Contango.
                    long.append(future + str(min_diff_index))
                    short.append(future + str(max_diff_index))
        
        # Trade execution.
        invested = [x.Key.Value for x in self.Portfolio if x.Value.Invested]
        for symbol in invested:
            if symbol not in long + short:
                self.Liquidate(symbol)
        
        weight = 1 / len(self.contracts)
        
        for symbol in long:
            if self.Securities[symbol].Price != 0:
                self.SetHoldings(symbol, weight)
        for symbol in short:
            if self.Securities[symbol].Price != 0:
                self.SetHoldings(symbol, -weight)

# Quandl free data
class QuandlFutures(PythonQuandl):
    def __init__(self):
        self.ValueColumnName = "settle"

# Custom fee model.
class CustomFeeModel(FeeModel):
    def GetOrderFee(self, parameters):
        fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
        return OrderFee(CashAmount(fee, "USD"))