# Rikj000/MoniGoMani

Isn't that what we all want? Our money to go many? Well that's what this framework/strategy hopes to do for you! By giving you & HyperOpt a lot of signals to alter the weights from.

Repository: https://github.com/Rikj000/MoniGoMani
Canonical: https://ross.abutalabs.com/products/monigomani
Homepage: https://monigomani.io
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: freqtrade, freqtrade-strategies, freqtrade-ui, python, cryptocurrencies, trading-bot, trading-strategies, weighted-signals, hyperopt, machine-learning, mgm, framework, moni-go-mani, freqtrade-framework, bitcoin, trading, crypto
Archived: true
Last push: 2023-03-11T14:05:58+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1985, "days_push": 1271, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1026, forks 153 (observed 2026-08-28T04:03:16.853535+00:00)

## What it is
MoniGoMani is a Freqtrade framework and trading strategy for cryptocurrency trading that uses weighted signals optimized via HyperOpt. It is explicitly marked as pre-release/experimental and not recommended for live trading.

## Use cases
- optimize a freqtrade crypto trading strategy with hyperopt
- build a weighted-signal trading strategy for bitcoin
- backtest and tune crypto trading bot signals
- find a freqtrade strategy framework to customize
- experiment with machine-learning-tuned crypto strategies

## When to choose
- you already use Freqtrade and want a signal-weighting strategy skeleton
- you want to experiment with HyperOpt-driven strategy tuning
- you want a community-supported freqtrade strategy starting point

## When to avoid
- you need a stable, production-ready strategy for live trading
- you want a plug-and-play profitable bot without tuning
- you don't use Freqtrade or Python

## Facets
- artifact type: framework
- maturity: experimental
- function: trading, machine-learning, developer-tools
- domain: fintech, machine-learning
- platform: python, cli
- tags: freqtrade, hyperopt, trading-strategy, crypto-trading-bot, weighted-signals, cryptocurrency

## Member repositories
- Rikj000/MoniGoMani (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:16.853535+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:07:56.963579+00:00, confidence not recorded.
  - readme: https://github.com/Rikj000/MoniGoMani (fetched 2026-08-28T04:03:16.853535+00:00, sha f1a992752367)
- Data as of 2026-08-30T08:39:29.467469+00:00.