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[https://www.quantconnect.cloud/backtest/2c856210aebe94deb84792b87c7ab9a3/?theme=darkly](https://www.quantconnect.cloud/backtest/2c856210aebe94deb84792b87c7ab9a3/?theme=darkly)

This code implements a **5-Minute Intraday Momentum Strategy** using **0DTE (Zero Days to Expiration) In-The-Money (ITM) Options** on the SPY ETF.
It is designed to catch morning and early-afternoon intraday trends, leveraging the leverage of options while trying to minimize the rapid time-decay (theta) associated with 0DTEs by purchasing ITM contracts rather than At-The-Money (ATM) contracts.
Here is a comprehensive breakdown of the strategy's mechanics:
# 1. The Core Setup & Indicators
* **Asset:** SPY (S&P 500 ETF).
* **Timeframe:** 5-minute candles. The algorithm pulls raw 1-minute data but uses a `TradeBarConsolidator` to bundle it into 5-minute blocks.
* **Indicators:** A 9-period Exponential Moving Average (Fast EMA) and a 21-period Exponential Moving Average (Slow EMA). EMAs are used instead of Simple Moving Averages because they react faster to recent price action.
# 2. Entry Rules
The algorithm evaluates the market every 5 minutes and looks for a highly specific setup:
* **The Trigger:** A Bullish Crossover. The 9 EMA must cross *above* the 21 EMA, indicating a shift into short-term upward momentum.
* **Time Constraint:** The crossover must happen **before 1:00 PM ET**. This prevents the bot from entering late-day trends where there isn't enough time left in the trading session for the option to double in value.
* **Frequency Constraint:** The bot is limited to **1 trade per day** (`self.traded_today`). If it wins or gets stopped out, it turns off until tomorrow.
# 3. The Options Selection Engine
Once the entry signal fires, the algorithm doesn't just buy SPY shares; it dynamically finds a specific option contract:
* **0DTE Only:** It filters the options chain for contracts expiring on the exact same day (`Expiration(0, 0)`).
* **Call Options Only:** Because it only looks for bullish crossovers, it only buys Call options (`OptionRight.Call`).
* **The ITM Shift:** Instead of buying ATM options (which are highly susceptible to theta decay), it calculates a `target_strike` that is exactly **$2.50 below the current SPY price**. This forces the algorithm to buy an **In-The-Money (ITM)** contract (roughly a 0.65 to 0.70 Delta). These contracts are more expensive but behave more predictably.
# 4. Position Sizing & Risk Management
* **Flat Dollar Allocation:** The strategy uses a fixed budget of **$500 per trade** (`self.trade_budget = 500.00`).
* **Dynamic Quantity:** It calculates how many ITM contracts it can afford by taking the $500 budget and dividing it by the premium of the chosen option (multiplied by 100). If the premium is $4.00, it buys 1 contract. If the premium is $2.00, it buys 2.
# 5. Exit Rules
The bot actively manages the open position minute-by-minute and will exit based on three strict conditions:
1. **Take Profit (The Winner):** If the unrealized profit reaches **+100%** (the option premium doubles), it immediately liquidates.
2. **Stop Loss (The Loser):** If the unrealized profit drops to **-50%**, it immediately cuts the loss.
3. **Time Exit (The Safety Net):** Regardless of profit or loss, if the position is still open at **3:30 PM ET**, the bot forcefully liquidates everything. This ensures you never hold a 0DTE option into the volatile final 30 minutes of the market or let it expire worthless.
# 6. Thoughts
I was disappointed to see such a long run of losses between July 2023 to Jan 2025. Not sure why? But recently it's been performing decently. Any feedback or suggestions is greatly appriciated.
# 7. Code
from AlgorithmImports import *

class SPY5MinEMA_ITMOptions(QCAlgorithm):

def Initialize(self):
self.SetStartDate(2023, 1, 1)
self.SetEndDate(2026, 5, 1)
self.SetCash(10000)

self.spy = self.AddEquity("SPY", Resolution.MINUTE)
self.spy.SetDataNormalizationMode(DataNormalizationMode.RAW)

option = self.AddOption("SPY", Resolution.MINUTE)
# WIDENED FILTER: We need to ensure we load strikes deep enough below the price to be ITM
option.SetFilter(lambda universe: universe.IncludeWeeklys().Expiration(0, 0).Strikes(-10, 5))
self.option_symbol = option.Symbol

self.trade_budget = 500.00
self.traded_today = False
self.signal_triggered = False

# EMAs (Standard 9/21 setup)
self.fast_ema = ExponentialMovingAverage(9)
self.slow_ema = ExponentialMovingAverage(21)

# 5-Minute Consolidator
five_min_consolidator = TradeBarConsolidator(timedelta(minutes=5))
five_min_consolidator.DataConsolidated += self.OnFiveMinuteBar
self.SubscriptionManager.AddConsolidator(self.spy.Symbol, five_min_consolidator)

self.RegisterIndicator(self.spy.Symbol, self.fast_ema, five_min_consolidator)
self.RegisterIndicator(self.spy.Symbol, self.slow_ema, five_min_consolidator)

self.SetWarmUp(timedelta(days=2))
self.previous_fast = 0
self.previous_slow = 0

self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.At(0, 0), self.ResetDay)
self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.At(15, 30), self.ClosePositions)

def ResetDay(self):
self.traded_today = False
self.signal_triggered = False

def OnFiveMinuteBar(self, sender, bar):
if self.IsWarmingUp: return
if not self.fast_ema.IsReady or not self.slow_ema.IsReady: return

current_fast = self.fast_ema.Current.Value
current_slow = self.slow_ema.Current.Value

if self.previous_fast > 0 and self.previous_slow > 0:
# Check for Bullish Crossover
if self.previous_fast <= self.previous_slow and current_fast > current_slow:
# Must be BEFORE 1:00 PM (13:00)
if self.Time.hour < 13 and not self.traded_today and not self.Portfolio.Invested:
self.signal_triggered = True
self.Debug(f"[{self.Time}] EMA Bullish Crossover. Looking for ITM Call.")

self.previous_fast = current_fast
self.previous_slow = current_slow

def OnData(self, slice: Slice):
if self.IsWarmingUp: return

# --- MANAGING OPEN POSITION ---
if self.Portfolio.Invested:
for symbol, holding in self.Portfolio.items():
if holding.Invested and holding.Type == SecurityType.Option:
current_pnl = holding.UnrealizedProfitPercent

if current_pnl >= 1.0:
self.Liquidate(symbol, "Hard Target +100% Hit")
elif current_pnl <= -0.50:
self.Liquidate(symbol, "Hard Stop -50% Hit")
return

# --- ENTRY EXECUTION (ITM SHIFT) ---
if self.signal_triggered and not self.traded_today:
if not slice.ContainsKey(self.spy.Symbol) or slice[self.spy.Symbol] is None: return
current_price = slice[self.spy.Symbol].Close

chain = slice.OptionChains.get(self.option_symbol)
if not chain: return

# Filter for 0DTE Calls
contracts = [x for x in chain if x.Expiry.date() == self.Time.date() and x.Right == OptionRight.Call]
if not contracts: return

# THE DYNAMIC SHIFT: Target 0.5% below the current price
# If SPY is at $400, offset is $2.00. If SPY is at $550, offset is $2.75.
dynamic_offset = current_price * 0.005
target_strike = current_price - dynamic_offset

itm_contract = sorted(contracts, key=lambda x: abs(x.Strike - target_strike))[0]

premium = itm_contract.AskPrice
if premium == 0: return

# Position Sizing: ITM contracts cost more, so you will buy fewer contracts per trade
qty = int(self.trade_budget // (premium * 100))

if qty > 0:
self.Buy(itm_contract.Symbol, qty)
self.traded_today = True
self.signal_triggered = False
self.Debug(f"[{self.Time}] Entered ITM Call. SPY: ${round(current_price,2)} | Strike: ${itm_contract.Strike} | Premium: ${premium}")

def ClosePositions(self):
if self.Portfolio.Invested:
self.Liquidate()
self.Debug(f"[{self.Time}] 3:30 PM Time Exit triggered. Closing positions.")from AlgorithmImports import *

class SPY5MinEMA_ITMOptions(QCAlgorithm):

def Initialize(self):
self.SetStartDate(2023, 1, 1)
self.SetEndDate(2026, 5, 1)
self.SetCash(10000)

self.spy = self.AddEquity("SPY", Resolution.MINUTE)
self.spy.SetDataNormalizationMode(DataNormalizationMode.RAW)

option = self.AddOption("SPY", Resolution.MINUTE)
# WIDENED FILTER: We need to ensure we load strikes deep enough below the price to be ITM
option.SetFilter(lambda universe: universe.IncludeWeeklys().Expiration(0, 0).Strikes(-10, 5))
self.option_symbol = option.Symbol

self.trade_budget = 500.00
self.traded_today = False
self.signal_triggered = False

# EMAs (Standard 9/21 setup)
self.fast_ema = ExponentialMovingAverage(9)
self.slow_ema = ExponentialMovingAverage(21)

# 5-Minute Consolidator
five_min_consolidator = TradeBarConsolidator(timedelta(minutes=5))
five_min_consolidator.DataConsolidated += self.OnFiveMinuteBar
self.SubscriptionManager.AddConsolidator(self.spy.Symbol, five_min_consolidator)

self.RegisterIndicator(self.spy.Symbol, self.fast_ema, five_min_consolidator)
self.RegisterIndicator(self.spy.Symbol, self.slow_ema, five_min_consolidator)

self.SetWarmUp(timedelta(days=2))
self.previous_fast = 0
self.previous_slow = 0

self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.At(0, 0), self.ResetDay)
self.Schedule.On(self.DateRules.EveryDay("SPY"), self.TimeRules.At(15, 30), self.ClosePositions)

def ResetDay(self):
self.traded_today = False
self.signal_triggered = False

def OnFiveMinuteBar(self, sender, bar):
if self.IsWarmingUp: return
if not self.fast_ema.IsReady or not self.slow_ema.IsReady: return

current_fast = self.fast_ema.Current.Value
current_slow = self.slow_ema.Current.Value

if self.previous_fast > 0 and self.previous_slow > 0:
# Check for Bullish Crossover
if self.previous_fast <= self.previous_slow and current_fast > current_slow:
# Must be BEFORE 1:00 PM (13:00)
if self.Time.hour < 13 and not self.traded_today and not self.Portfolio.Invested:
self.signal_triggered = True
self.Debug(f"[{self.Time}] EMA Bullish Crossover. Looking for ITM Call.")

self.previous_fast = current_fast
self.previous_slow = current_slow

def OnData(self, slice: Slice):
if self.IsWarmingUp: return

# --- MANAGING OPEN POSITION ---
if self.Portfolio.Invested:
for symbol, holding in self.Portfolio.items():
if holding.Invested and holding.Type == SecurityType.Option:
current_pnl = holding.UnrealizedProfitPercent

if current_pnl >= 1.0:
self.Liquidate(symbol, "Hard Target +100% Hit")
elif current_pnl <= -0.50:
self.Liquidate(symbol, "Hard Stop -50% Hit")
return

# --- ENTRY EXECUTION (ITM SHIFT) ---
if self.signal_triggered and not self.traded_today:
if not slice.ContainsKey(self.spy.Symbol) or slice[self.spy.Symbol] is None: return
current_price = slice[self.spy.Symbol].Close

chain = slice.OptionChains.get(self.option_symbol)
if not chain: return

# Filter for 0DTE Calls
contracts = [x for x in chain if x.Expiry.date() == self.Time.date() and x.Right == OptionRight.Call]
if not contracts: return

# THE DYNAMIC SHIFT: Target 0.5% below the current price
# If SPY is at $400, offset is $2.00. If SPY is at $550, offset is $2.75.
dynamic_offset = current_price * 0.005
target_strike = current_price - dynamic_offset

itm_contract = sorted(contracts, key=lambda x: abs(x.Strike - target_strike))[0]

premium = itm_contract.AskPrice
if premium == 0: return

# Position Sizing: ITM contracts cost more, so you will buy fewer contracts per trade
qty = int(self.trade_budget // (premium * 100))

if qty > 0:
self.Buy(itm_contract.Symbol, qty)
self.traded_today = True
self.signal_triggered = False
self.Debug(f"[{self.Time}] Entered ITM Call. SPY: ${round(current_price,2)} | Strike: ${itm_contract.Strike} | Premium: ${premium}")

def ClosePositions(self):
if self.Portfolio.Invested:
self.Liquidate()
self.Debug(f"[{self.Time}] 3:30 PM Time Exit triggered. Closing positions.")

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