Budgeting & Forecasting

One Python interface in front of many financial data sources.

A crypto trading bot that runs on its owner's machine, with testing on past prices and pretend-money trading built in.

A Python research workbench for machine-learning experiments on market data.

It makes every amount of money get a job before it is spent.

A personal finance manager you run yourself, with budgets, categories and reports.

A free framework for writing and running automated trading programs on cryptocurrency exchanges.

More than 150 standard chart indicators for Python, computed by the long-established TA-Lib engine.

One page showing every holding across every account, on a private server.

It runs thousands of variations of a trading rule over past prices at once.

Tests a trading rule against years of past prices and reports what it would have returned.

A self-hosted tracker for recurring subscriptions, with renewal dates, currencies and totals.

The long-established free library for pricing and risk-managing financial instruments.

Portfolio tearsheets from a returns series — the monthly-returns heatmap that tests the 2%-a-month claim, under a licence he can ship.

Double-entry bookkeeping written as a plain text file, with a command-line program that checks it and reports on it.

Works out how to split a sum of money across a set of holdings, then converts the percentages into whole share counts.

Double-entry accounting from a plain text file, run from the command line, with no database of any kind.

A trading test that models the place in the order queue and the delay before an order arrives.

It keeps double-entry accounts in a plain text file and prints reports from it.

It works out how to split money between several strategies, using many different measures of risk.

Desktop double-entry accounting for a person or a small business.

A Python library for backtesting trading strategies and studying market behaviour.

It tests a trading idea on history and says how much of the result could be luck.

A complete systematic futures trading system in Python, for testing against past prices and for live trading.

Charts and reports over a plain-text money ledger you already keep.

A Python library that prices financial derivatives and measures their risk.

Backtesting built from reusable blocks, with strategies that can contain other strategies.

Reads United States company filings and their financial tables in Python.

GroupStats: hand it a DataFrame of many equity curves and get one table of performance statistics for all of them.

A website for a plain text accounting file, with balances, charts and filters.

A Python library for portfolio allocation, built to the same shape as scikit-learn, with time-aware testing built in.

A Java toolbox of chart indicators and a tester for trading rules.

A desktop program for household accounts, budgets and spending, saved in one local file.

The standard Python library for measuring market volatility and for testing whether the best of many strategies is real.

A shared-expense list that works out the shortest set of payments to make everyone even.

It computes portfolio weights by solving an optimisation problem, and replays the resulting policy over historical prices.

A check on whether a trading signal actually predicts returns, before anything is built on it.

Python financial indicators that update as each new price arrives, instead of recalculating the whole series.