Issue with Short Put Spread with SMA filter

sorry by the way I have just realized that I was comparing the option chain price with the SMA price

Here are the functional bugs found in 'AlMoJo's' code that could cause the SMA 200 filter or spread logic not to work as intended (excluding naming, allocation, and import issues):

main.py

1. Incorrect Warm-up Method (Typo/Redundancy): Both self.SetWarmUp(200, Resolution.Daily) and self.SetWarmup(200, Resolution.Daily) are called. Only the properly cased SetWarmUp will work; having both is redundant, and the lowercase variant will cause an exception if reached.
2. Expiration Filter Limitation: The option filter uses .Expiration(0, 1) (contracts expiring in one day or less), but later the code tries to select contracts expiring close to 30 days, so the chain will likely be empty and never result in trades.
3. Redundant/Unreachable SMA Check: There is a duplicate if not self.sma200.IsReady: after it's already checked at the beginning of OnData. This is unnecessary but not harmful.
4. Syntax Error After Buy Call: The f-string f"Price={price:.2f}, SMA200={self.sma200.Current.Value:.2f}") is not assigned or logged—this orphaned line (with an extra closing parenthesis and indentation) will cause a syntax error and prevent the script from running.
5. Potential Spread Leg Miss/Index Issue: The spread selects long/short legs with a fixed 5-strike gap by index; if there are fewer than five strikes below the short put, no trade occurs, which could block trades even when 1-4 strikes are available.
6. No Clearing of Open Spread: The openSpread is set after trades but is only checked for any(self.Portfolio[x].Invested for x in self.openSpread). If one leg is assigned or expires, the other may remain in openSpread and block new trades, potentially causing logic to stall on assignment/expiry.

execution.py

No code issues identified in the given execution model. All main functionality issues relevant to your SMA filtering and spread trading live in main.py.

Summary:
Address the expiration filter, typo redundancy, f-string syntax error, and index/logic checks around the spread construction. These are necessary to restore reliability of the 200-SMA momentum filter and ensure spread logic functions as expected.

If you compare an option contract's price to the SMA of the underlying asset, the units are not compatible: option prices are often much smaller and behave differently (they are premiums, not share prices). The SMA is calculated from the price history of the underlying security, so you must compare the current price of the underlying asset itself to its SMA.

Correct Approach:

• Get the price of the underlying (e.g., chain.Underlying.Price or self.Securities[underlying].Price), which is in the same units as the SMA.
• Get the value of the SMA indicator (e.g., self.sma.Current.Value).
• Compare these two values directly.

Why This Works:
Both values are in "USD per share" (or whatever the currency/quote asset is), so it is a clean momentum comparison.

Sample Logic Patch

# Inside your OnData(self, slice)
chain = slice.option_chains.get(self.symbol)
if not chain or chain.underlying is None or not self.sma_200.is_ready:
    return

underlying_price = chain.underlying.price      # USD/share (e.g., 426.00)
sma_value = self.sma_200.current.value          # USD/share (e.g., 420.00)

if underlying_price > sma_value:
    # Underlying is showing upward momentum above its 200-SMA (bullish condition)
    # Proceed to consider selling a put spread, etc.
    self.debug(f"Bullish: Price {underlying_price} > SMA200 {sma_value}")
else:
    # Do not sell the spread
    self.debug(f"Bearish: Price {underlying_price} <= SMA200 {sma_value}")

What Was Wrong Before:
If you did if some_option.Price > self.sma200.Current.Value: you were comparing an option contract's price (in dollars per option, often $2–$10) to a stock price (often $200+)—which is a meaningless comparison.

Summary:

• Always compare the underlying's price to the SMA for direction/momentum signals.
• Use the option chain only to select the contracts you’ll trade once your signal is confirmed.

This structure will result in consistent, meaningful bullish/bearish signals for your spread logic.

Sources: Equity Options - QuantConnect.com, Combining Indicators - QuantConnect.com, US Futures Security Master - QuantConnect.com, Indicators - QuantConnect.com, Indicators - QuantConnect.com

I was able to fix it by changing from OnData to a daily scheduler :)