Long Term Debt Factor within Stocks
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Strategy in a nutshell
: Annual U.S. Equity Long-Term Debt Change Strategy
This annual strategy targets non-financial U.S. stocks (AMEX, NYSE, NASDAQ). Stocks are ranked by annual changes in long-term financial liabilities, including long-term debt, debt in current liabilities, and preferred stock. A zero-investment portfolio is formed by going long on stocks with the largest increases in liabilities and shorting those with the smallest changes. Positions are equally weighted and rebalanced yearly.
Economic rationale
Financial liabilities reflect future cash obligations discounted at issuance rates, with minimal subjectivity due to restrictions on anticipated non-payments. This objective measurement ensures reliable accruals, making long-term debt changes a credible indicator for assessing financial health and forecasting potential stock price movements.
Backtest performance
Annualised return10.5%
Volatility6.5%
Beta0.073
Sharpe ratio1.62
Sortino ratio0.012
Win rate55%
Full Python code
from AlgorithmImports import *
from typing import Dict, List
import numpy as np
class LongTermDebtFactorWithinStocks(QCAlgorithm):
def Initialize(self) -> None:
self.SetStartDate(2008, 1, 1)
self.SetCash(100_000)
self.UniverseSettings.Leverage = 10
self.UniverseSettings.Resolution = Resolution.Daily
self.AddUniverse(self.FundamentalSelectionFunction)
self.Settings.MinimumOrderMarginPortfolioPercentage = 0.0
self.exchange_codes: List[str] = ['NYS', 'NAS', 'ASE']
self.fundamental_count: int = 3_000
self.fundamental_sorting_key = lambda x: x.MarketCap
self.fin_sector_code: int = 103
self.rebalancing_month: int = 1
self.quantile: int = 10
self.selection_flag: bool = True
self.last_year_liabilities: Dict[Symbol, float] = {}
self.long_symbols: List[Symbol] = []
self.short_symbols: List[Symbol] = []
market: Symbol = self.AddEquity('SPY', Resolution.Daily).Symbol
self.Schedule.On(self.DateRules.MonthStart(market), self.TimeRules.AfterMarketOpen(market), self.Selection)
self.settings.daily_precise_end_time = False
def OnSecuritiesChanged(self, changes: SecurityChanges) -> None:
for security in changes.AddedSecurities:
security.SetFeeModel(CustomFeeModel())
for security in changes.RemovedSecurities:
if security.Symbol in self.last_year_liabilities:
del self.last_year_liabilities[security.Symbol]
def FundamentalSelectionFunction(self, fundamental: List[Fundamental]) -> List[Symbol]:
if not self.selection_flag:
return Universe.Unchanged
filtered: List[Fundamental] = [
f for f in fundamental if f.HasFundamentalData
and f.SecurityReference.ExchangeId in self.exchange_codes
and not np.isnan(f.MarketCap)
and f.MarketCap != 0
and not np.isnan(f.FinancialStatements.BalanceSheet.TradingandFinancialLiabilities.TwelveMonths)
and f.FinancialStatements.BalanceSheet.TradingandFinancialLiabilities.TwelveMonths > 0
and f.asset_classification.morningstar_industry_code != self.fin_sector_code
]
sorted_filter: List[Fundamental] = sorted(filtered,
key=self.fundamental_sorting_key,
reverse=True)[:self.fundamental_count]
change_in_liabilities: Dict[Symbol, float] = {}
for f in sorted_filter:
liabilities: float = f.FinancialStatements.BalanceSheet.TradingandFinancialLiabilities.TwelveMonths
if f.Symbol not in self.last_year_liabilities:
self.last_year_liabilities[f.Symbol] = liabilities
continue
change_in_liabilities[f.Symbol] = liabilities / self.last_year_liabilities[f.Symbol] - 1
if len(change_in_liabilities) >= self.quantile:
# Sorting by change in Longterm financial liabilities
sorted_by_liabilities: List = sorted(change_in_liabilities.items(), key=lambda x: x[1], reverse=True)
decile: int = int(len(sorted_by_liabilities) / self.quantile)
self.long_symbols = [x[0] for x in sorted_by_liabilities[:decile]]
self.short_symbols = [x[0] for x in sorted_by_liabilities[-decile:]]
return self.long_symbols + self.short_symbols
def OnData(self, slice: Slice) -> None:
if not self.selection_flag:
return
self.selection_flag = False
# Trade execution
targets: List[PortfolioTarget] = []
for i, portfolio in enumerate([self.long_symbols, self.short_symbols]):
for symbol in portfolio:
if slice.ContainsKey(symbol) and slice[symbol] is not None:
targets.append(PortfolioTarget(symbol, ((-1) ** i) / len(portfolio)))
self.SetHoldings(targets, True)
self.long_symbols.clear()
self.short_symbols.clear()
def Selection(self) -> None:
if self.Time.month == self.rebalancing_month:
self.selection_flag = True
class CustomFeeModel(FeeModel):
def GetOrderFee(self, parameters):
fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
return OrderFee(CashAmount(fee, "USD"))