Jay Beckner

High-Productivity Trading

Get in touch via email & Telegram

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

My code fetches data, builds dataframes, generates ideas, watches charts and monitors trades.

My tech stack includes Python 3, Google Colab, IEX data, Telegram, TOS and Robinhood.

I trade the deep, liquid options chains of 100+ U.S. stocks and ETFs.

I do so within a framework that reflects my experience and interests.

Stocks captured my interest in the late '90s.

I didn't know my identity in markets, until recently.


In August, 2018, I started trading more frequently, with appropriate sizing and sheets-based analytics.

Much progress has been made since.


I manage capital to a target level.

Distribute above as income. Add to increase target.


I make frequent trades, 1-5% of account value.

I diversify by bias, duration, underlying type, sector and strategy.


Entries, and which tickers to trade, are the most important decisions I make.

Average duration consumed is inversely correlated to portfolio health.


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


How the above translates into P/L.


Serverless | Connected | Efficient | Powerful

Collapsed view of my Google Colab notebook.


Record | Refer | Review | Improve

Partial view of my Google Sheets trading journal.


Consulting, I can deliver high-productivity tools to support your technical strategy and trading framework.

On your buy-side equity desk, I can add strategic diversity and collaborate with other traders on process automation.

At a later date, I may offer private alternative asset management services and/or a web-based, freemium version of my ideas and tech.