Absolutely. This session has a different feel from the normal GYP Office Hours because Tony Rihan was traveling and Tony Battista was joined by his son, Nick Battista. The father-son dynamic works particularly well because Tony brings the perspective of an old-school market maker and experienced discretionary trader, while Nick demonstrates how many of those same principles are being translated into 0DTE, systematic, data-driven and automated trading.
Below is a member-ready recap you can send with the replay.
Hi GYP Members,
While Tony Rihan was traveling, we had a very special edition of Grow Your Pile Office Hours.
Tony Battista was joined by his son, Nick Battista, for a fascinating father-and-son discussion that connected two generations of trading.
Tony brought decades of experience as a market maker and discretionary options trader. Nick showed us where he believes trading is heading: systematic strategies, massive numbers of occurrences, 0DTE options, data-driven decision making and automation.
What became especially interesting during the conversation was how similar the underlying philosophy actually is.
The technology has changed dramatically.
The core trading principles have not.
The Main Event:
How Nick Battista is Trading 0DTE
The heart of the session was Nick’s explanation of his current approach to systematic 0DTE trading.
And the scale was eye-opening.
Nick explained that his larger strategy allocates approximately $1 million per day to the SPX component, while smaller versions are also being run at different account sizes.
But the real lesson wasn’t the dollar amount.
It was the methodology.
Don’t Look for One Perfect Trade
Perhaps the single most important concept from Nick’s presentation was this:
There is no “best trade.”
Instead of trying to identify one incredible setup, Nick builds a portfolio containing many strategies and many occurrences.
Those strategies can include:
Multiple-entry iron condors
Ratio structures
Reverse-ratio structures
Moving-average/EMA-driven positions
Positions with slight directional biases
Different spread widths
Different entry times throughout the trading session
Some strategies may lose money on a particular day while others make money.
The objective is the combined portfolio, not whether every individual trade wins.
That is a major distinction.
Diversification by Time
Most traders think about diversification in terms of:
Stocks
Sectors
Strategies
Asset classes
Nick introduced another form:
Diversification by time.
Instead of placing one iron condor in the morning and living with that entry all day, the system introduces trades at multiple points throughout the session.
That means the trader isn’t completely dependent upon the market conditions present at one particular moment.
Different trades experience:
Different prices
Different volatility
Different deltas
Different remaining time to expiration
This creates another layer of diversification.
Why Automation Matters
The strategies Nick described aren’t manually entered one by one.
They are automated.
Nick and his team build the strategy rules, determine the parameters and backtest the ideas. The software then handles execution according to those rules.
But Nick made an important distinction:
Automated does NOT mean “set it and forget it.”
Humans are still responsible for:
Developing the strategies
Reviewing the data
Backtesting
Monitoring performance
Evaluating changing market conditions
Deciding which strategies belong in the portfolio
Adjusting allocations
Automation removes the repetitive execution.
It does not remove the need to think.
Backtesting: Useful, But Not a Crystal Ball
Nick spent considerable time explaining how he uses backtesting.
The purpose isn’t to say:
“This worked before, therefore it will work tomorrow.”
Instead, historical data is used to understand the characteristics of a strategy.
Among the things they examine:
One-year performance
Six-month performance
One-month performance
Recent performance
Average wins
Average losses
Maximum drawdowns
Distribution of returns
Performance under different volatility regimes
Performance on different days of the week
Performance around events such as FOMC
Whether recent performance is improving or deteriorating
The large number of 0DTE occurrences makes this particularly interesting.
A traditional 45-DTE strategy may generate a relatively limited number of independent observations.
A strategy traded multiple times every day can generate thousands of observations.
That produces an enormous amount of data to analyze.
The Numbers Behind the Strategy
Nick was extremely transparent about the numbers.
And this may have been the most educational part of the entire session.
The strategy is NOT built around winning 90% of the time.
Quite the opposite.
Nick discussed a historical daily win rate in roughly the low-50% range, including approximately 51% over the more recent period shown during the presentation.
That sounds unimpressive until you understand the philosophy.
The edge isn’t enormous.
The edge is repeated.
Nick described approximately a 6%–7% capture rate on the premium/extrinsic value being sold.
In one set of results shown during the session, approximately $2.5 million of premium had been sold, with roughly $185,000 captured, representing around a 7% capture rate before looking at the broader portfolio context.
The concept is:
Capture a very small edge an enormous number of times.
Tony Battista Immediately Recognized the Model
This led to one of my favorite parts of the session.
Tony realized that what Nick is doing with computers and 0DTE options is conceptually very similar to what Tony did as a floor market maker decades ago.
Tony described trading thousands of contracts in a day while attempting to capture only:
$6.25
$12.50
Or another very small amount per contract
Many trades would simply scratch.
The objective wasn’t to hit home runs.
It was:
Small edge × enormous number of occurrences.
Nick has essentially taken that traditional market-making philosophy and moved it into a modern systematic environment.
Tony summarized the evolution beautifully:
Instead of making markets, Nick is effectively making strategies.
Why a 51% Win Rate Can Still Work
This is an important lesson for every GYP member.
We naturally want high probabilities of success.
But probability alone doesn’t determine profitability.
If a process has:
A small positive expectancy
Appropriate risk management
Thousands of occurrences
Controlled transaction costs
Consistent execution
then even a modest statistical edge can become meaningful.
Nick compared it conceptually to flipping a coin where you possess a small edge.
You don’t care about the next flip.
You care about thousands of flips.
That is a completely different mindset from asking:
“Do I think the market is going up tomorrow?”
Losses Are Part of the System
Nick was equally transparent about drawdowns.
The results were not a straight line higher.
He showed individual days where the larger portfolio experienced substantial losses, including a roughly $90,000 losing day, while other periods produced significant winning days.
The lesson wasn’t the dollar amount because those numbers correspond to a much larger capital base.
The important point was:
A profitable system still loses.
Sometimes it loses several days in a row.
The question is whether:
The loss falls within the expected distribution
Position sizing remains appropriate
The statistical edge remains intact
The trader can continue executing the strategy
That last point is critical.
A strategy that you abandon during its normal drawdown isn’t really a strategy you can trade.
Why Account Size Changes the Experience
Nick also demonstrated results for a roughly $50,000 account.
The smaller portfolio could still implement the basic approach, but there is an important difference:
Fewer occurrences create wider outcomes.
A large account might distribute capital across dozens or hundreds of trades.
A smaller account may only have enough buying power for five or six positions.
Therefore, individual trades have a much larger effect on the overall account.
This means smaller accounts can experience more pronounced percentage swings even when using essentially the same methodology.
That was an important reminder that you cannot simply shrink every institutional strategy proportionally and expect identical behavior.
Why 0DTE Is Different
Nick believes short-duration trading will continue to become a much larger part of the options market.
His thesis is based partly on volatility.
Short-duration options typically contain higher annualized implied volatility because uncertainty over very short periods can be substantial.
And if the basic premium-selling thesis remains true—that implied volatility tends, over large samples, to exceed subsequent realized volatility—then 0DTE creates many more opportunities to express that edge.
Instead of waiting 30 or 45 days for another occurrence, a 0DTE trader gets another opportunity tomorrow.
And then again the following day.
That acceleration in the number of occurrences is one of the fundamental attractions of the strategy.
An Underappreciated Advantage: Overnight Risk Goes Away
One of Nick’s favorite characteristics of 0DTE trading has nothing to do with return.
At the end of the trading day:
The SPX positions are gone and settle to cash.
That means the capital used for those strategies isn’t carrying the same equity exposure overnight.
If something significant happens Saturday or Sunday, the 0DTE book isn’t sitting there carrying Friday’s expiring SPX risk into Monday.
Nick described this as an important and difficult-to-quantify benefit.
Tony’s Short-Put Management
The session wasn’t entirely about automation.
Tony also answered an excellent member question about how he manages short-dated naked puts.
His general framework:
He may initially sell approximately 20–30 delta puts with roughly five or six days remaining.
If the underlying falls and the put reaches approximately:
At-the-money
Or one to two strikes in-the-money
Tony begins considering management.
His preferred approach is generally to roll, rather than automatically accept assignment and wheel the position.
He may:
Roll approximately another week
Maintain the strike
Or move down one or two strikes when the pricing allows
The objective is to collect additional premium while maintaining manageable delta exposure.
Tony also emphasized sizing.
When he believed the market looked potentially toppy, he didn’t simply refuse to trade.
Instead, he began with roughly 25% of his normal position size.
As the market declined, he added exposure.
That’s an important GYP principle:
You don’t always have to choose between “all in” and “all out.”
Position size itself is a risk-management tool.
The Bigger Lesson:
Trading Is Becoming More Systematic
Perhaps the biggest forward-looking takeaway from the conversation was Nick’s belief that automation will become increasingly important.
And that doesn’t necessarily mean everyone needs to become a 0DTE algorithmic trader.
Automation could eventually be used for very familiar GYP concepts.
For example:
“Sell a 30-DTE put after the market falls 1%.”
Rather than watching a screen all day and waiting for the condition, software can monitor it and execute according to predetermined rules.
That has several potential benefits:
Removes emotion
Creates consistency
Reduces screen time
Enforces predetermined rules
Makes systematic portfolio management easier
Technology isn’t necessarily replacing the trader.
It’s increasingly capable of replacing the trader’s repetitive tasks.
Key Takeaways for GYP Members
This session connected old-school market making with the future of systematic trading.
The biggest lessons were:
1. Stop searching for the perfect trade.
A portfolio of small statistical edges can be more powerful than one brilliant idea.
2. Number of occurrences matters.
A modest edge repeated thousands of times can become meaningful.
3. Diversification isn’t only about underlyings.
You can diversify across strategies, deltas, volatility regimes and even entry times.
4. Automation doesn’t eliminate judgment.
It automates execution; humans still design and monitor the process.
5. Backtests are information—not guarantees.
Use them to understand distributions, drawdowns and behavior rather than predict tomorrow.
6. A profitable strategy can still have a lot of losing trades.
A roughly 51% win rate can work if the overall expectancy is positive.
7. Position sizing matters enormously.
The same strategy can behave very differently in a $50,000 account than in a $1 million account.
8. Expect drawdowns.
If normal losses cause you to abandon the strategy, your position size or strategy may not fit you.
9. 0DTE offers an enormous number of occurrences—but also enormous speed.
That creates opportunity and risk.
10. Think like a market maker.
You don’t need to make a fortune on every trade. Sometimes the goal is to capture a tiny edge repeatedly.
Final Thought
What made this Office Hours especially interesting was seeing the evolution of the same trading philosophy across two generations.
Tony Battista learned to capture small edges by standing in an options pit, making markets and trading thousands of contracts.
Nick Battista is applying many of those same principles using data, automation, backtesting and 0DTE options.
Different technology.
Different market.
Same fundamental idea:
Find an edge. Keep risk under control. Repeat it enough times to let the probabilities work.
Thank you to Nick for joining us and filling in while Tony Rihan was traveling—and thank you to all our GYP members who joined live and brought such great questions.
We hope you enjoy the replay.
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