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.

Performance

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

Much progress has been made since.

Capital

I manage capital to a target level.

Distribute above as income. Add to increase target.

Risk

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

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

Duration

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

Average duration consumed is inversely correlated to portfolio health.

Return

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

Profit

How the above translates into P/L.

Notebook

Serverless | Connected | Efficient | Powerful

Collapsed view of my Google Colab notebook.

Journal

Record | Refer | Review | Improve

Partial view of my Google Sheets trading journal.

Value

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.