ALGO TRADING IS COMING TO TOWN

The Future of Options Trading: How Algorithmic Trading Can Transform Your Trading Journey

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Read my book for deeper insights: Mean Reversion Trading Using Options

If you’ve been following me, you know that I’ve spent over 15 years trading options and two decades programming. These hard-earned skills didn’t come overnight—they demanded persistence, dedication, and continuous learning. As a mentor to thousands of traders, I’ve been teaching the importance of rules-based trading systems. Whether it’s trade entries, exits, risk management, or portfolio allocation, everything is predefined by rules in my approach.

So, what comes next when you’ve got a solid rules-based trading foundation?

Spoiler Alert: Automation.

 

Why Automate Your Trading?

Having coached over 6,000 traders in the past four years, I’ve learned a lot about the struggles people face in implementing trading strategies. Some find the strategy doesn’t fit their goals, others lack time, and a significant number simply struggle to stick to the rules.

Here’s the harsh truth: a trading system only works when followed with discipline. Skipping steps like managing losers or prematurely exiting winners often leads to underperformance. This is where algorithmic trading becomes a game-changer.

This video proves how a small variation in your ability to follow rules can kill your profits: 

The Downside of Discretionary Trading

Discretionary trading—the art of making decisions on the fly based on experience and judgment—can sometimes help but more often hinders. Imagine you’re bullish on Apple (AAPL) and hold onto a losing trade because you’re anticipating a game-changing product launch. This emotional bias clouds your judgment, and instead of cutting your losses as per your plan, you cling to hope, waiting for the trade to turn around.

While experience and intuition are valuable, relying too much on discretion leads to inconsistency and bad habits. Once emotions take the wheel, discipline goes out the window.

Moreover, the biggest limitation of discretionary trading is that it cannot be backtested or objectively proven. Since the rules are not fixed, you can’t apply them to historical data to validate performance. Backtesting requires a consistent set of rules that the system follows without deviation—something discretionary trading inherently lacks. Without proof of its effectiveness over time, discretionary trading remains subjective, leaving you with little more than gut feelings to guide your decisions.

For traders seeking reliability and accountability, the lack of testable results is a dealbreaker. It’s why rule-based systems—and their automated counterparts—have become the cornerstone of successful trading strategies.

The Beauty of Non-Discretionary Trading

In contrast, non-discretionary trading follows pre-defined rules with no room for emotion. When you teach a computer the rules of your trading system, it will execute them perfectly every time—no second-guessing, no hesitation. This consistency is the foundation of algorithmic trading.

But the benefits don’t stop there. By automating, you can:

• Backtest Strategies: Modern technology allows you to simulate trading systems over decades of historical data. For example, you can backtest how your algorithm would have performed during the 2008 financial crisis, recreating every tick of the market in real-time.
• Measure Performance Quantitatively: Instead of relying on gut feelings, automated systems provide precise metrics like ROI, win rate, drawdowns, and more.

My trading algorithm represents the intersection of two decades of programming expertise and 15+ years of options trading experience. It’s not just a set of coded instructions—it’s the culmination of everything I’ve learned, refined, and taught to thousands of traders worldwide. By automating the strategies I’ve meticulously developed, the algorithm eliminates the common pitfalls of manual trading—emotional bias, lack of discipline, and inconsistency.

But how do you prove that an algorithm works?

Imagine This:

Suppose you have a simple trading system based on a coin flip. Heads, you go bullish; tails, you go bearish. Your rules are straightforward—cut all your losers at a 50% loss and let all your winners double your money.

Now the question arises: How do you prove the effectiveness of this trading system?

Enter Backtesting.

The Power of Backtesting

The sophistication of modern technology enables traders to test their systems on years of historical market data. Backtesting recreates market conditions as they unfolded—tick by tick, day by day—allowing you to see how your trading strategy would have performed.

For example, if you were to test your system on the tumultuous markets of 2008 or the volatile pandemic years of 2020-2021, the algorithm would “live” in those moments, making trading decisions based solely on the pre-defined rules. At the end of the backtest, you’ll have quantifiable data: profit, loss, win rate, drawdown, and more.

Although backtesting doesn’t guarantee future results, it’s a critical tool for proving a system’s effectiveness before risking real money.

Months of Rigorous Backtesting

I’ve spent countless hours running backtest after backtest on my trading strategy, fine-tuning every rule and parameter to ensure the algorithm operates at its peak. The entire process—failures, successes, and refinements—is documented on my YouTube channel, so you can follow along and see the progression for yourself.

For transparency, I’ve also shared the results of these backtests, including detailed breakdowns of profit and loss for each year. You can view the full results here:
Backtesting Results Spreadsheet 

Key Insights From the Backtests

The years 2020-2024 are particularly illuminating because they’re fresh in our memories. If you’ve been trading during this time, you’ll remember major market events and can directly tally those against the algorithm’s trading decisions. Here’s how you can explore the results:

• Summary Tab: A snapshot of profit and loss for each year, giving you a high-level overview of the algorithm’s performance.
• Individual Year Tabs: Dive deeper into specific years to understand why the algorithm made particular trading decisions during key moments in the market.

This transparency ensures that you’re not just taking my word for it—you can see the numbers, scrutinize the trades, and decide for yourself.

From Rules to Results

This algorithm isn’t just about proving a concept—it’s about consistency and discipline. While backtesting has validated the system’s potential, the real magic is in its ability to execute trades day after day, without hesitation or emotional interference.

Want proof of how it performs?

1. Watch the Journey: Follow along on YouTube.
2. Explore the Data: See the backtest results.

Trust isn’t built overnight, but when you see the level of thought, testing, and transparency behind this algorithm, I’m confident you’ll understand why I believe it’s a game-changer for options traders. Let the data speak for itself!

When Will the Algorithm Go Live?

The algorithm, affectionately named Maya, has been live since October 20, 2024, and has taken its first round of trades on November 26th after a 1 month ‘trading fast’. This was expected behavior and Maya skipped trading for the whole month due to the rules below that are coded into the algorithm. 

• Pre-Election Volatility: Leading up to the elections, heightened market uncertainty caused a spike in the VIX, a key indicator used by Maya to manage risk. With VIX levels too high, the algorithm refrained from trading, adhering strictly to its risk-avoidance protocols.
• Post-Election Market Surge: Right after the elections, the market made an aggressive move from the bottom of the Bollinger Bands to the top in just one day. This rapid shift pushed markets into overbought conditions, preventing Maya from executing trades. 

Pilot Program Underway

Currently, Maya is in a pilot/beta program with a select group of traders from our community. This exclusive phase allows us to monitor the algorithm’s performance in real-time and make any necessary adjustments. The pilot program is expected to last about a month after Maya places its first trade.

What problems are being addressed in the pilot ?

• PAPER FILLS: The algo is live with a paper trading account and an account with my own real money. Although, Interactive Brokers is a very good platform, there could be discrepancies between when a trade gets filled on a paper account vs a live account. Since the trade alerts are coming from a paper account for now, you may see more trade alerts than you can get filled on in real life. My live account has $5000 in it and the paper account has $25,000. My goal is for my real account to grow to $25,000. At that point, I will connect the trade alerts to my real account. If I do it before that, the algo will get limited by lack of funds and the group will hardly see any trade alerts. 
• PERFECT FILLS: Backtesting comes with some assumptions. One such assumption is ‘perfect fills’. When the algo determines it is time to take a trade, backtesting assumes that the trade gets opened immediately. In real life, you submitting an order doesn’t mean that the exchange will fill the order.
• CLOSING ORDERS: The algo will send closing trade alerts when a trade reaches its profit target, or needs loss management. However, it is very difficult to calculate the current price of an options spread. No brokerage can give you the exact value of a spread and that is why stop loss orders don’t work for spreads either. Once Maya opens trades, we will have to monitor if those closing alerts are sent at the right time. This is a process which will need to happen after a full trading cycle which lasts 30 days on average.    

After the pilot, Maya will be opened to the entire group for 1-2 months to showcase its effectiveness before being fully released to everyone. This phased rollout ensures that the algorithm performs consistently and reliably under various market conditions. 

Will the algo be free for all members?

I believe in full transparency and letting results speak louder than words. Before introducing any additional costs, Maya needs to demonstrate its effectiveness. That’s why the algorithm is currently in a pilot phase with a select group of traders. This allows us to monitor real-world performance and ensure Maya meets the high standards I’ve set for it.

Once Maya has consistently proven its value over a few months, I plan to open it up to the broader group. At that point, there will be an additional fee for access, as running the algorithm incurs significant operational costs—several thousand dollars annually. This fee will reflect the value Maya provides while covering the infrastructure and development required to keep it running smoothly.

For now, the focus is entirely on performance. Discussions around fees will only happen after Maya proves itself as a reliable, effective trading solution. My commitment is to deliver results first, and everything else will follow natural