# https://quantpedia.com/strategies/us-holiday-effect-in-eu-markets/
# 
# Buy DAX index (via ETF, CFD, fund or futures) at European close one day before each US holiday day. Sell on European close during US holiday day. Hold cash otherwise.

import numpy as np
import fk_tools

class US_Holiday_EU_Markets(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2012, 1, 1)
        self.SetEndDate(2019, 10, 1)
        self.SetCash(100000)           
        
        data = self.AddData(fk_tools.QuandlFutures, "CHRIS/EUREX_FESX1", Resolution.Daily)
        data.SetFeeModel(fk_tools.CustomFeeModel(self))
        self.symbol = data.Symbol
        
    def OnData(self, data):
        calendar1 = self.TradingCalendar.GetDaysByType(TradingDayType.PublicHoliday, self.Time, self.Time)
        calendar2 = self.TradingCalendar.GetDaysByType(TradingDayType.Weekend, self.Time, self.Time + timedelta(days=2))
        
        holidays = [i.Date for i in calendar1]
        weekends = [i.Date for i in calendar2]
        
        # subtract weekends in all holidays
        public_holidays = list(set(holidays) - set(weekends))

        if not self.Portfolio.Invested and len(public_holidays) > 0:
            self.SetHoldings(self.symbol, 1)
        if self.Portfolio.Invested and len(public_holidays) == 0:
            self.Liquidate()

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

import numpy as np

def Return(values):
    return (values[-1] - values[0]) / values[0]
    
def Volatility(values):
    values = np.array(values)
    returns = (values[1:] - values[:-1]) / values[:-1]
    return np.std(returns)  

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

# Quandl free data
class QuandlFutures(PythonQuandl):
    def __init__(self):
        self.ValueColumnName = "settle"
        
# Quantpedia data
# NOTE: IMPORTANT: Data order must be ascending (datewise)
class QuantpediaFutures(PythonData):
    def GetSource(self, config, date, isLiveMode):
        return SubscriptionDataSource("data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)

    def Reader(self, config, line, date, isLiveMode):
        data = QuantpediaFutures()
        data.Symbol = config.Symbol
        
        if not line[0].isdigit(): return None
        split = line.split(';')
        
        data.Time = datetime.strptime(split[0], "%d.%m.%Y") + timedelta(days=1)
        data['settle'] = float(split[1])
        data.Value = float(split[1])

        return data