Our Portfolio Engineering & Backtesting Guides

Welcome to Weekly Roundup #6 at ForecastOS! We're glad to have you here, following our journey :)

This newsletter is split into three sections: 1) thoughts, musings, and updates relevant to ForecastOS, 2) what we worked on last week, and 3) what's coming next.

1. Thoughts, Musings, and Updates

Our Portfolio Engineering & Backtesting Guides

Earlier this week InvestOS - our open-source module for backtesting and portfolio optimization - released its first two guides!

They can be found here:

• Getting Started
• Portfolio Backtesting

The design of the guide engine is fantastic - see below for a screenshot. We are excited to release more guides next week!

2. Work: What Got Done

ForecastOS is a new startup. As such, we try to spend 100% of our time either building or selling. We log that effort here.

This past week, as it pertains to selling, we:

• Continued the outreach process for our unified AI management (AIM) platform; if you know anyone we should talk to, please let us know! We have capacity to onboard 1 additional client in Q4 2023

This past week, as it pertains to building, we:

• Helped a new InvestOS open-source user build and backtest a quant portfolio
• Added UI improvements for the user settings page
• Created a test suite for our web app (for regression testing)
• Built a guide engine for InvestOS for rendering versioned guides from source control
• Wrote 2 guides for InvestOS

Other notable activities from this past week:

• Onboarded Tom, our first engineer. He had his full development environment set up and working for all of our repositories and applications by the end of the first day! He even uploaded a backtest to ForecastOS for a quantitative crypto strategy on day 1!

3. Work: What's Coming Next

It's important to keep velocity high. We keep ourselves accountable by sharing what we hope to finish over the next week.

This week we will:

• Continue outreach for our unified AI management (AIM) platform
• Build, and prepare to deploy, our open-source (PyPI) package and associated API for consuming features and datasets through ForecastOS in less than 10 lines of code
• Start planning our first (financial) forecasting competition
• Write more guides on customizable portfolio engineering and backtesting
• Help an InvestOS open-source user create and implement custom portfolio engineering logic

Until next week!