From Scalper to Seller: Why I Built "QMA" to Fix My Trading Psychology

I spent years chasing the 5-minute chart. I loved the adrenaline of scalping futures, the dopamine hit of a quick $800 win, and the crushing stress of the inevitable $1,000 loss that followed. I was a gambler acting like a trader.

Then I realized something fundamental: The Casino doesn’t scalp. The Casino sells probability.

I decided to shift my entire approach to a Laddered Premium Selling Strategy—selling Options on Futures with high statistical win rates (70%+) and letting time decay (Theta) do the heavy lifting. But a new strategy required a new discipline. I didn’t need another complex broker platform; I needed a simple, transparent way to hold myself accountable.

Spreadsheets were too clunky. Paper journals were too easily ignored. So, I built QMA (Quantitative Market Analysis).

What is QMA?

QMA is an open-source, lightweight tool designed to log, track, and analyze options trade ideas. It isn’t an algorithm that trades for you; it is a system that forces you to think before you trade.

Built on a Jekyll front-end with a simple JSON data structure, it allows me to treat my trading plan like code: version-controlled, structured, and transparent.

The Problem: Strategy Drift

When trading options on futures (like /MES or /MNQ), the biggest enemy isn’t the market—it’s Strategy Drift.

• Plan: “I will only sell 16 Delta strangles.”
• Reality: “The market looks weak, I’ll just sell a naked call… and double the size.”

This “drift” kills portfolios. I needed a way to formalize the “Ladder” approach I use:

1. Week 1: Sell /MES Strangle (Income)
2. Week 2: Sell GLD Iron Condor (Diversification)
3. Week 3: Ladder /MES
4. Week 4: Manage & Roll

How QMA Enforces Discipline

QMA strips away the noise of blinking lights and 1-second ticks. It focuses on the metrics that actually matter for a premium seller:

• The “Why”: Every entry requires a summaryJustification. If I can’t write a 2-sentence thesis on why I’m entering, QMA (and my own discipline) won’t let me place the trade.
• The Mechanics: It tracks specific mechanics like ivRank and expectedReturnDisplay. If IV Rank is < 30, the log stares back at me, asking why I’m selling cheap premium.
• The Timeline: By logging dte (Days to Expiration) and expiration dates, I can visualize my “Ladder” perfectly. I can see if I’m over-concentrated in January or if I have successfully rolled my risk out to February.

Under the Hood: The Tech Stack

I wanted something I could self-host and modify easily without a heavy backend database.

• Engine: Jekyll (Static Site Generator)
• Database: A single data.json file. This makes the data portable and easy to parse for future backtesting.
• Frontend: Bootstrap 5 for clean, card-based visualization.
• Notifications: Integrated with a Telegram bot to push my trade ideas to a live feed instantly.

Why Open Source?

I believe profitable trading shouldn’t be a black box. By making QMA open source, I’m inviting other traders to fork it, improve it, and perhaps find the same discipline it has given me.

If you are tired of the emotional rollercoaster of directional trading and want to start building a systematic, data-driven portfolio, check out the project. It might just be the accountability partner you didn’t know you needed.