Zero days to expiration, aka 0DTE option strategies, provide traders with numerous daily opportunities to trade the market. This article explores an objective, data-driven approach to trading 0DTE using backtested results to provide insights based on research and practical examples.
What is the best strategy for trading 0DTE options?
The answer is… it depends. On multiple factors. As traders, we can use math and data to target opportunities with long-term positive expectancy based on historical backtesting and probabilities.
The best strategies for trading 0DTE options are those that effectively balance risk and reward while leveraging historical price action to inform decision-making.Â
Probability research shows that probabilities for short-term options trades, specifically 0DTE positions, tend to be less accurate than longer-dated strategies.
Instead, traders can focus on using historical price action to identify realized probabilities and combine them with favorable reward-to-risk ratios to enter trades with positive expected value.
0DTE Research
We analyzed historical intraday SPX price action. This Peg research analyzes SPX data to determine how often the market closes within a specific range of its marked price at different times of the day.
Each data point in the table below displays the percentage of time the SPX closed within the defined range (0.1%, 0.2%, 0.3%, 0.4%, or 0.5% OTM) from that time forward.
For example, the data shows that 65.6% of the time, the SPX closes within 0.2% of its 2:00pm price in the last 180 trading days. It also shows that 53.3% of the time, the SPX closes within 0.3% of its 10:30am price in the last 180 trading days.
Why is this important? When employing an option selling strategy like an iron condor, we realize a max profit if the short option expires out of the money. This data shows us the historical probability of max profit for each OTM% throughout the trading day.
We can also use this heat map to visualize the results of SPX 0DTE Peg data and how probabilities change based on OTM% and time of day:
We can clearly see that the market 'pegs' closer to the marked price later in the day. How can we ensure we're taking on appropriate risk for each given probability?
Evaluating Favorable Reward/Risk & Probabilities
Knowing the % of times a strike price X%Â OTMÂ will expire worthless is not enough. We must also consider if the trade has long-term viability. This is when we should also factor in a position's reward/risk ratio.
The table below shows the same stats as above, and includes the minimum favorable reward/risk for each OTM % historical results using the last 180 days.
For example, entering an iron condor 0.3% OTM at 1:00pm EST has realized a max profit 66.1% of the time in the last 180 days. We should target a minimum reward/risk of at least 51.3% for this strategy to have success over that timeframe.
Let's take a closer look...
Assume a 0.2% OTM, $5 wide iron condor entered at 2:44pm EST receives $196. The position's reward/risk is 64.4% ($196 / $304). Using the data, we know that trade would realize a max profit ~ 68% of the time. The minimum suggested R/R is 48%, so we'd expect this trade to yield positive returns:
(68% x $196) - (32% x $304) = +$36 EV/trade
The win rate and realized profit is actually probably higher, because some positions will profit if they’re in the money and have not exceeded to break even point. Plus, not all losses will be a max loss. But this is a simplified way of putting all the pieces together. Learn more about true Expected Value (EV).
Here's a simple 'cheat sheet' to quickly identify the minimum reward/risk for different probabilities of max profit (which is the same as the OTM% in the tables above).
While the data above can be extremely helpful in identifying quality positions using historical stats, we can use 0DTE backtesting to analyze and visualize the simulated results of a 0DTE trade.
Backtesting 0DTE Option Strategies
0DTE Oracle is very different than a traditional backtester and is a new approach to backtesting 0DTE positions. It's a positional backtester, meaning it's asking the question, "What if this exact position, using 0TM% and a specific reward/risk existed every single day at the same time over the last 1-3 years... What would have happened?"
It's not evaluating an arbitrary strategy available on historical dates at certain deltas or strike prices. The underlying price movement from the minute of entry into EOD expiration is used to evaluate this performance. It provides context for a trader on whether or not the specific trade setup and entry time has been successful.
This is a different way to think about trading. Backtesting 2.0 aims to highlight the importance of identifying the optimal R/R for setups based on their probability of max profit, and is a departure from traditional backtesting which simply uses a combo of variables without accounting for specific market conditions and pricing.
The 0dte Oracle backtester is not simply displaying the results of every position opened at 1:00pm with a $5 wide spread; it’s showing us the performance of every position with that exact reward-to-risk ratio, spread width, and entry time.
For example, we used the 0DTE Oracle to backtest an SPX iron condor 0.32% out-of-the-money that collects $285 on a $5 wide spread (132.56% reward/risk), opened at 11:09am each day. The strategy yielded these results over the last year:
When is the best time to trade 0DTE options?
Here's the Truth About 0DTE Options Time Decay: data suggests that the most significant decay occurs later in the day, and early entries don’t capture significantly more premium than entries in the later afternoon.
All of this data combines suggests that 0DTE option traders should target positions with proven results of expiring out-of-the-money and a favorable reward/risk ration, while also considering that entering trades later in the day will experience the impact of time decay quicker than trades opened in the morning.
