Jay Beckner

High-Productivity Trader

With a balanced framework, I trade options on 120+ U.S. stocks and ETFs.

I automate things like technical, statistical and relative analysis to scale my trading process.

My code maintains data, evaluates markets, tracks setups, alerts entries and monitors positions.

Tech stack: GCE with Python 3 and Storage, Shell, Colab, IEX Cloud and Telegram

Background

My career began as a broker, cold-calling during the 2002 bear market. I left the business in 2004 and earned an MBA in 2008. Afterwards, I accumulated experiences in technology, product and systems development and data analytics, unrelated to trading (but the fire burned).

I started this project in 2018 and quickly shed sheets-based tools for Python code and cloud computing. While creating supportive technology, I traded options, journaled transactions and improved my framework and process.

Hundreds of strategies in, I'm ever closer to producing consistent, absolute returns with relative outperformance.

The charts below reflect my activity during the building and testing phase. Soon, I'll deploy my latest tech, hit the reset button and see how we do.

Performance

My goal is to make money and beat the market's total return.

Capital

Periodically, I withdraw capital in excess of deposits.

Risk

Each position risks 1 to 10 percent of capital.

Duration

Open to expiry, my framework consumes half of that time on average.

Returns

Average return on risk is more important than individual strategy results.

For a defined risk strategy, return equals net closing value divided by maximum potential loss.

Notebooks

For testing code and decision support.

Collapsed view of a Python 3 notebook.

Journal

For strategy analytics, framework improvement and relaying positions to live code for monitoring.

Partial view of my Google Sheets trading journal, which generates the charts charts above.