This tool allows Excel to be the main interface for trading through the Alpaca broker Below are two demo videos of the tool This tool allows the following to be done via Excel Some aspects of the tool that can be customized are Known Limitations Please note: this has only been tested on windows based machines Link to tool for purchase
I recently finished the first version of a philosophy-oriented NLP research pipeline focused on shareholder letters. The idea behind philo_nlp is simple: long-form corporate communication often reflects an underlying philosophy. In this first implementation, the reference philosophy is Berkshire Hathaway and Warren Buffett shareholder communication. The project is split into three repositories. Berkshire_Letters builds the Buffett reference corpus by downloading and normalizing Berkshire shareholder letters into a reusable...
I built a local research dashboard to make Commitments of Traders data easier to review across a focused futures market universe. The goal is simple: take raw CFTC COT data, clean it, match it to a configured set of markets, and surface where current positioning sits relative to recent history. This is not a trading signal tool. It does not predict prices, recommend trades, or replace market judgment....
Most macroeconomic analysis lives at one of two extremes: This project sits somewhere in the middle. I wanted a clear, repeatable, and modular way to explore macroeconomic regimes using publicly available FRED data — something that supports learning, experimentation, and practical monitoring without pretending to predict the economy. That’s what this repository is. Here’s a link to GitHub. What This Project Is This repo is a macro research...
As part of a larger NLP project focused on analyzing shareholder communications, I needed a clean, consistent corpus of historical letters to shareholders. One obvious and valuable dataset is the collection of Chairman’s Letters from Berkshire Hathaway, which spans nearly five decades. While the letters are publicly available on Berkshire’s website, assembling them into a single, NLP-ready dataset isn’t quite as simple as it sounds. Here’s a link...
One of the most effective uses of large language models (LLMs) is helping people get up to speed on unfamiliar code. Excel models don’t get that benefit. As spreadsheets grow, logic becomes harder to reason about: If you didn’t build the model — or if enough time has passed — understanding how it works can be surprisingly slow. A simple shift in approach Instead of asking an LLM...
Working with SEC fundamentals data is powerful—but rarely simple. Raw filings are large, fragmented across periods, and difficult to transform into something usable for research, screening, or visualization. To solve this, I built SEC FSN, a lightweight Python-based data engineering and analytics pipeline for working with SEC EDGAR Financial Statements & Notes (FSN) data. The goal was simple: create a transparent, reproducible fundamentals foundation that works equally well...
Introduction This Small Business Finance Template Suite was built for owners who want visibility into their business without adopting complex software or changing how they already work. The goal is simple: clear structure, realistic data flow, and decision support. Not automation for its own sake. Each template works on its own, but together they form a lightweight system for managing clients, revenue, commissions, and cash flow using Google...
Lines of credit and bridge loans rarely follow clean schedules. They often involve: Because of this, traditional amortization calculators often fall short. They require assumptions that don’t reflect what actually happens over time. This Line Of Credit template is designed for tracking, not forecasting. What This Template Does The template functions as a transaction level ledger for a revolving line of credit. You enter: From there, the template...
Most Microsoft Access databases hide years of business logic inside saved queries and VBA modules. When you’re ready to modernize—whether that’s moving processes into Power BI Dataflows, SQL Server, Fabric, or a Python-based pipeline—the first problem is usually: “How do I extract all of this logic from Access without opening every query manually?” To make that easier, I worked with ChatGPT to build a lightweight VBA utility that:...
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