# https://quantpedia.com/strategies/net-payout-yield-effect/
#
# The investment universe consists of all stocks on NYSE, AMEX, and NASDAQ. At the end of June of each year t, ten portfolios are formed based on ranked 
# values net payout yield. The net payout yield is the ratio of dividends plus repurchases minus common share issuances in year t to year-end market
# capitalization. There are two measures of payout yield, one based on the statement of cash flows, the other based on the change in Treasury stocks. 
# For the net payout yield, we use the cash flow-based measure of repurchases. The portfolio with the highest net payout yield is bought and held for
# one year, after which it is rebalanced.
#
# QC implementation changes:
#   - Instead of all listed stock, we select 500 most liquid stocks traded on NYSE, AMEX, or NASDAQ.

from AlgorithmImports import *

class NetPayoutYieldEffect(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2000, 1, 1)  
        self.SetCash(100000) 

        self.symbol = self.AddEquity('SPY', Resolution.Daily).Symbol
        
        self.coarse_count = 500
        self.quantile = 10
        self.leverage = 5

        self.long = []
        
        self.selection_flag = False
        self.UniverseSettings.Resolution = Resolution.Daily
        self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
        self.Schedule.On(self.DateRules.MonthEnd(self.symbol), self.TimeRules.AfterMarketOpen(self.symbol), self.Selection)

    def OnSecuritiesChanged(self, changes):
        for security in changes.AddedSecurities:
            security.SetFeeModel(CustomFeeModel())
            security.SetLeverage(self.leverage)

    def CoarseSelectionFunction(self, coarse):
        if not self.selection_flag:
            return Universe.Unchanged
        
        selected = sorted([x for x in coarse if x.HasFundamentalData and x.Market == 'usa'],
            key=lambda x: x.DollarVolume, reverse=True)
        
        return [x.Symbol for x in selected[:self.coarse_count]]
    
    def FineSelectionFunction(self, fine):
        fine = [x for x in fine if x.MarketCap !=0 and x.ValuationRatios.TotalYield != 0 and x.FinancialStatements.CashFlowStatement.CommonStockIssuance.TwelveMonths != 0 and 
            ((x.SecurityReference.ExchangeId == "NYS") or (x.SecurityReference.ExchangeId == "NAS") or (x.SecurityReference.ExchangeId == "ASE"))]
        
        # Sorting by net payout.
        sorted_by_payout = sorted(fine, key = lambda x: ( (x.ValuationRatios.TotalYield * (x.MarketCap)) - \
                                                            (x.FinancialStatements.CashFlowStatement.CommonStockIssuance.TwelveMonths / (x.MarketCap))), reverse=True)
        
        if len(sorted_by_payout) >= self.quantile:
            decile = int(len(sorted_by_payout) / self.quantile)
            self.long = [x.Symbol for x in sorted_by_payout[:decile]]

        return self.long
    
    def OnData(self, data):
        if not self.selection_flag:
            return
        self.selection_flag = False

        stocks_invested = [x.Key for x in self.Portfolio if x.Value.Invested]
        for symbol in stocks_invested:
            if symbol not in self.long:
                self.Liquidate(symbol)

        for symbol in self.long:
            if symbol in data and data[symbol]:
                self.SetHoldings(symbol, 1 / len(self.long))

        self.long.clear()
    
    def Selection(self):
        if self.Time.month == 6:
            self.selection_flag = True

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