# https://quantpedia.com/strategies/federal-open-market-committee-meeting-effect-in-stocks/
#
# The investor is invested in stocks during FOMC meetings (going long S&P 500 ETF, fund, future, or CFD on a close one day before the meeting and closing position on close after the meeting).
# Otherwise, he is invested in cash during the remaining days. The strategy has very low exposure to the stock market (8 days during the average year); therefore, it can be very easily leveraged
# to gain very significant returns.
#
# QC implementation:
#   - FED dates are imported from text file.

from AlgorithmImports import *
from pandas.tseries.offsets import BDay
from datetime import datetime

class FederalOpenMarketCommitteeMeetingEffectinStocks(QCAlgorithm):
    
    def Initialize(self) -> None:
        self.SetStartDate(2000, 1, 1)
        self.SetCash(100000)
        
        self.market:Symbol = self.AddEquity("SPY", Resolution.Minute).Symbol

        self.fed_days_symbol:Symbol = self.AddData(FedDays, 'fed_days', Resolution.Daily, TimeZones.NewYork).Symbol
        self.SetWarmUp(1, Resolution.Daily)
        FedDays.set_algo(self)
        
        self.recent_day:int = -1

    def OnData(self, data:Slice) -> None:
        if self.IsWarmingUp: return

        if self.fed_days_symbol in data and data[self.fed_days_symbol]:
            self.Log(f"New FOMC meeting data arrived: {self.Time}; submitting an MOC order...")

            # new fed day data arrived
            quantity:float = self.CalculateOrderQuantity(self.market, 1.)
            self.MarketOnCloseOrder(self.market, quantity)

            self.recent_day = self.Time.day
        else:
            # other new minute resolution data arrived
            if self.Portfolio[self.market].Invested:
                if self.Time.day != self.recent_day:
                    self.recent_day = self.Time.day

                    self.Log(f"FOMC meeting day; submitting an MOC order to close opened position...")
                
                    self.MarketOnCloseOrder(self.market, -self.Portfolio[self.market].Quantity)
        
class FedDays(PythonData):
    algo = None
    
    @staticmethod
    def set_algo(algo):
        FedDays.algo = algo

    def GetSource(self, config:SubscriptionDataConfig, date:datetime, isLiveMode:bool) -> SubscriptionDataSource:
        if isLiveMode:
            # FedDays.algo.Log(f"Edited GetSource date {FedDays.algo.Time}")
            return SubscriptionDataSource("https://data.quantpedia.com/backtesting_data/economic/fed_days.json", SubscriptionTransportMedium.RemoteFile, FileFormat.UnfoldingCollection)

        return SubscriptionDataSource("https://data.quantpedia.com/backtesting_data/economic/fed_days.csv", SubscriptionTransportMedium.RemoteFile)
        
    def Reader(self, config:SubscriptionDataConfig, line:str, date:datetime, isLiveMode:bool) -> BaseData:
        if isLiveMode:
            try:
                # FedDays.algo.Log(f"Reader")

                objects = []
                data = json.loads(line)
                end_time = None

                for index, sample in enumerate(data):
                    custom_data = FedDays()
                    custom_data.Symbol = config.Symbol

                    custom_data.Time = (datetime.strptime(str(sample["fed_date"]), "%Y-%m-%d") - BDay(1)).replace(hour=9, minute=31)
                    # FedDays.algo.Log(f"{custom_data.Time}")

                    end_time = custom_data.Time  
                    objects.append(custom_data)

                return BaseDataCollection(end_time, config.Symbol, objects) 

            except ValueError:
                # FedDays.algo.Log(f"Reader Error")
                return None
        else:
            if not (line.strip() and line[0].isdigit()):
                return None
            
            custom = FedDays()
            custom.Symbol = config.Symbol

            custom.Time = (datetime.strptime(line, "%Y-%m-%d") - BDay(1)).replace(hour=9, minute=31)
            custom.Value = 0.
            custom["fed_date_str"] = line

            return custom