accrual-anomaly.py

# https://quantpedia.com/strategies/accrual-anomaly/
#
# The investment universe consists of all stocks on NYSE, AMEX, and NASDAQ. Balance sheet based accruals (the non-cash component of
# earnings) are calculated as: BS_ACC = ( ∆CA – ∆Cash) – ( ∆CL – ∆STD – ∆ITP) – Dep
# Where:
# ∆CA = annual change in current assets
# ∆Cash = change in cash and cash equivalents
# ∆CL = change in current liabilities
# ∆STD = change in debt included in current liabilities
# ∆ITP = change in income taxes payable
# Dep = annual depreciation and amortization expense
# Stocks are then sorted into deciles and investor goes long stocks with the lowest accruals and short stocks with the highest accruals. 
# The portfolio is rebalanced yearly during May (after all companies publish their earnings).

from AlgorithmImports import *

class AccrualAnomaly(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2006, 1, 1)
        self.SetCash(100000)
        
        self.symbol = self.AddEquity("SPY", Resolution.Daily).Symbol

        self.coarse_count = 1000
        
        self.long = []
        self.short = []
        
        # Latest accruals data.
        self.accrual_data = {}
        
        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(5)

        for security in changes.RemovedSecurities:
            symbol = security.Symbol
            if symbol in self.accrual_data:
                del self.accrual_data[symbol]
                
    def CoarseSelectionFunction(self, coarse):
        if not self.selection_flag:
            return Universe.Unchanged
        
        # selected = [x.Symbol for x in coarse if x.HasFundamentalData and x.Market == 'usa']
        selected = [x.Symbol
            for x in sorted([x for x in coarse if x.HasFundamentalData and x.Market == 'usa'],
                key = lambda x: x.DollarVolume, reverse = True)[:self.coarse_count]]
        
        return selected
    
    def FineSelectionFunction(self, fine):
        fine = [x for x in fine if (float(x.FinancialStatements.BalanceSheet.CurrentAssets.TwelveMonths) != 0) 
                                and (float(x.FinancialStatements.BalanceSheet.CashAndCashEquivalents.TwelveMonths) != 0)
                                and (float(x.FinancialStatements.BalanceSheet.CurrentLiabilities.TwelveMonths) != 0)
                                and (float(x.FinancialStatements.BalanceSheet.CurrentDebt.TwelveMonths) != 0)
                                and (float(x.FinancialStatements.BalanceSheet.IncomeTaxPayable.TwelveMonths) != 0)
                                and (float(x.FinancialStatements.IncomeStatement.DepreciationAndAmortization.TwelveMonths) != 0)]

        if len(fine) > self.coarse_count:
            sorted_by_market_cap = sorted(fine, key = lambda x: x.MarketCap, reverse=True)
            top_by_market_cap = sorted_by_market_cap[:self.coarse_count]
        else:
            top_by_market_cap = fine
            
        accruals = {}
        for stock in top_by_market_cap:
            symbol = stock.Symbol
            
            if symbol not in self.accrual_data:
                self.accrual_data[symbol] = None
                
            # Accrual calc.
            current_accruals_data = AccrualsData(stock.FinancialStatements.BalanceSheet.CurrentAssets.TwelveMonths, stock.FinancialStatements.BalanceSheet.CashAndCashEquivalents.TwelveMonths,
                                                stock.FinancialStatements.BalanceSheet.CurrentLiabilities.TwelveMonths, stock.FinancialStatements.BalanceSheet.CurrentDebt.TwelveMonths, stock.FinancialStatements.BalanceSheet.IncomeTaxPayable.TwelveMonths,
                                                stock.FinancialStatements.IncomeStatement.DepreciationAndAmortization.TwelveMonths, stock.FinancialStatements.BalanceSheet.TotalAssets.TwelveMonths)
            
            # There is not previous accrual data.
            if not self.accrual_data[symbol]:
                self.accrual_data[symbol] = current_accruals_data
                continue
            
            # Accruals and market cap calc.
            acc = self.CalculateAccruals(current_accruals_data, self.accrual_data[symbol])
            accruals[symbol] = acc
            
            # Update accruals data.
            self.accrual_data[symbol] = current_accruals_data
        
        # Accruals sorting.
        sorted_by_accruals = sorted(accruals.items(), key = lambda x: x[1], reverse = True)
        decile = int(len(sorted_by_accruals) / 10)
        self.long = [x[0] for x in sorted_by_accruals[-decile:]]
        self.short = [x[0] for x in sorted_by_accruals[:decile]]
        
        return self.long + self.short
        
    def OnData(self, data):
        if not self.selection_flag:
            return
        self.selection_flag = False
        
        # Trade execution.
        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:
            self.SetHoldings(symbol, 1 / len(self.long))
        for symbol in self.short:
            self.SetHoldings(symbol, -1 / len(self.short))

        self.long.clear()
        self.short.clear()
            
    def Selection(self):
        if self.Time.month == 4:
            self.selection_flag = True
            
    def CalculateAccruals(self, current_accrual_data, prev_accrual_data):
        delta_assets = current_accrual_data.CurrentAssets - prev_accrual_data.CurrentAssets
        delta_cash = current_accrual_data.CashAndCashEquivalents - prev_accrual_data.CashAndCashEquivalents
        delta_liabilities = current_accrual_data.CurrentLiabilities - prev_accrual_data.CurrentLiabilities
        delta_debt = current_accrual_data.CurrentDebt - prev_accrual_data.CurrentDebt
        delta_tax = current_accrual_data.IncomeTaxPayable - prev_accrual_data.IncomeTaxPayable
        dep = current_accrual_data.DepreciationAndAmortization
        avg_total = (current_accrual_data.TotalAssets + prev_accrual_data.TotalAssets) / 2
        
        bs_acc = ((delta_assets - delta_cash) - (delta_liabilities - delta_debt - delta_tax) - dep) / avg_total
        return bs_acc

class AccrualsData():
    def __init__(self, current_assets, cash_and_cash_equivalents, current_liabilities, current_debt, income_tax_payable, depreciation_and_amortization, total_assets):
        self.CurrentAssets = current_assets
        self.CashAndCashEquivalents = cash_and_cash_equivalents
        self.CurrentLiabilities = current_liabilities
        self.CurrentDebt = current_debt
        self.IncomeTaxPayable = income_tax_payable
        self.DepreciationAndAmortization = depreciation_and_amortization
        self.TotalAssets = total_assets
        
# Custom fee model.
class CustomFeeModel(FeeModel):
    def GetOrderFee(self, parameters):
        fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
        return OrderFee(CashAmount(fee, "USD"))