Overall Statistics |
Total Orders
396
Average Win
1.04%
Average Loss
-0.76%
Compounding Annual Return
1.879%
Drawdown
8.700%
Expectancy
0.321
Start Equity
100000
End Equity
159090.44
Net Profit
59.090%
Sharpe Ratio
-0.294
Sortino Ratio
-0.098
Probabilistic Sharpe Ratio
0.024%
Loss Rate
44%
Win Rate
56%
Profit-Loss Ratio
1.38
Alpha
-0.01
Beta
0.036
Annual Standard Deviation
0.03
Annual Variance
0.001
Information Ratio
-0.339
Tracking Error
0.156
Treynor Ratio
-0.246
Total Fees
$2017.94
Estimated Strategy Capacity
$380000000.00
Lowest Capacity Asset
SPY R735QTJ8XC9X
Portfolio Turnover
4.34%
|
# 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 changes: # - 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 # custom data is still coming if self.securities[self.fed_days_symbol].get_last_data() and self.time.date() > FedDays.get_last_update_date()[self.fed_days_symbol]: self.liquidate() 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): _last_update_date:Dict[str, datetime.date] = {} @staticmethod def get_last_update_date() -> Dict[str, datetime.date]: return FedDays._last_update_date 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) # store last update dates if config.Symbol not in FedDays._last_update_date: FedDays._last_update_date[config.Symbol] = datetime(1,1,1).date() if custom_data.Time.date() > FedDays._last_update_date[config.Symbol]: FedDays._last_update_date[config.Symbol] = custom_data.Time.date() 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 # store last update dates if config.Symbol not in FedDays._last_update_date: FedDays._last_update_date[config.Symbol] = datetime(1,1,1).date() if custom.Time.date() > FedDays._last_update_date[config.Symbol]: FedDays._last_update_date[config.Symbol] = custom.Time.date() return custom