MoniGoMani
Freqtrade Framework & Strategy
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It's not recommended to use this strategy live already, due to it still being under heavy development! If you'd like to see this project progress faster then please help out where you can here! |
Isn't that what we all want? Our money to go many? Well that's what this Freqtrade framework/strategy hopes to do for you by enabling you to HyperOpt a lot of signals to alter the weight from.
Big thank you to xmatthias and everyone who helped on MoniGoMani, Freqtrade Discord support was also really helpful, so thank you too!
If you like my work, feel free to donate or use one of my referral links, that would also greatly be appreciated:
- This strategy is under development. It is not recommended running it live at this moment.
- Always test this strategy before using it!
- I am in no way responsible for your live results! This strategy is still experimental and under heavy development!
- MoniGoMani should always be re-optimized after doing manual changes!
- You need to optimize your own copy of MoniGoMani while thinking logically, don't follow your computer blindly!
MoniGoMani is more than just a conventional strategy, it's a Framework that aims to help you "easily" find a profitable strategy configuration in any market through our partially automated optimization process!
Without the need to do any more real programming! 🚀
However, you will need to know about BackTesting-Traps and some Technical Analysis, to be able to tell if the MGM setup *HyperOpt found over the tested timerange is valid or not, this is not just an easy copy/paste!
MGM (MoniGoMani) derives itself from other strategies by its use of something I called weighted signals.
Each signal has its own weight allocated to it & a total buy/sell signal needed is defined too.
MGM will loop through all signals, if they trigger it will add up the weight and eventually it will check if it's bigger than what's needed in total over a candle lookback window (to take previous signals into consideration). If the grand total of the sum of weighted signals is bigger then what is required it will buy/sell.
An interface has been implemented so the indicators and weighted signals used by MGM can easily be tweaked in just a few lines of code! 🎉
The beauty lies in using MGM in combination with HyperOpting. Most of the parameters in MGM have been made HyperOptable thus it can be used to find an "ideal" weight division and setting configuration for you in any kind of market that that represents the data upon which you test.
It will also teach us what works where & what doesn't since MoniGoMani first detects Downwards/Sideways/Upwards trends and then does all the above individually for each kind of trend (Creating basically 3 individual strategies in 1, for each kind of trend one).
Further it has an embedded Open Trade Unclogger which will do various HyperOptable checks upon the open trades to see if there are "bad" ones to quickly unclog at small losses, so it can continue on the hunt for good trades more rapidly! 🚀
*HyperOpting: A form of machine learning where you BackTest a lot of times to find the most ideal values)
- Partially Automated Optimization Process
- All HyperOpt Results can easily be applied and removed with the use of some Go-To Commands
- Configurable Buy/Sell Signal Weight Influence Tables for Downwards/Sideways/Upwards trends, each table currently has 9 Buy & 9 Sell signals implemented (HyperOptable!):
- Weighted Signal Interface to easily change the weighted signals being used
- Configurable Total Buy/Sell Signal Percentages for Downwards/Sideways/Upwards trends (HyperOptable!)
- Configurable LookBack Windows for Total Buy/Sell Signal Percentages for Downwards/Sideways/Upwards trends (HyperOptable!)
- Configurable Trading During Trends (Downwards/Sideways/Upwards) for Buys/Sells
- Configurable Open Trade Unclogger, if enabled it attempts to unclog the bot when it's stuck with losing trades & unable to trade more new trades (HyperOptable!) 🚀
- TimeFrame-Zoom during BackTesting/HyperOpting to prevent profit exploitation! (Read: BackTesting-Traps)
- Configurable HyperOptable Stoploss to fine-tune where HyperOpt should look
- Custom Long Continuously decreasing ROI Table generation with configurable
roi_table_step_size - Precision Setting to alter the step-size used during HyperOpting
- 2 Custom HyperLoss Functions:
- WinRatioAndProfitRatioLoss: Attempts to optimise for the best profit and stability (Returns smaller number for better results)
- UncloggedWinRatioAndProfitRatioLoss: Same as WinRatioAndProfitRatioLoss but has a configurable Percentage of loss to ignore while HyperOpting (Small losses are a by-product of the Unclogger)
- Top Volume & All Tradable StaticPairList Downloading to easily fetch and apply a good StaticPairList
- Total Overall Signal Importance Calculator for Total Average Signal Importance Calculation upon the HyperOpt Results (With some really handy subcommands)
- Pre-Configured Main/Sub Plot Configurations for visualization of all indicators used in FreqUI
- Turn On/Off All Individual Weighted Signal DataFrame entries for easy debugging in an IDE or better speed while dry/live running or HyperOpting
Take a good read at the MGM_DOCUMENTATION.md, the current place where you can find all MoniGoMani Documentation!
Hyper Opting MoniGoManiHyperStrategy.py:
freqtrade hyperopt -s MoniGoManiHyperStrategy -c ./user_data/mgm-config.json -c ./user_data/mgm-config-private.json --hyperopt-loss WinRatioAndProfitRatioLoss --spaces all -e 800 --timerange 20210101-20210316 --enable-protectionsApply HyperOpt Results after Run 1 from a <epoch of choice>:
freqtrade hyperopt-show -n <epoch of choice> -c ./user_data/mgm-config.json -c ./user_data/mgm-config-private.json --no-header --print-json | tail -n 1 | jq '.' > ./user_data/mgm-config-hyperopt.json && jq '.' ./user_data/mgm-config-hyperopt.jsonApply HyperOpt Results after Run 2 from a <epoch of choice>:
freqtrade hyperopt-show -n <epoch of choice> -c ./user_data/mgm-config.json -c ./user_data/mgm-config-private.json --no-header --print-json | tail -n 1 | jq '.' > ./tmp.json && jq -s '.[0] * .[1]' ./user_data/mgm-config-hyperopt.json ./tmp.json > ./tmp2.json && rm ./tmp.json ./user_data/mgm-config-hyperopt.json && mv ./tmp2.json ./user_data/mgm-config-hyperopt.json && jq '.' ./user_data/mgm-config-hyperopt.jsonReset HyperOpt Results:
rm ./user_data/mgm-config-hyperopt.jsonBack Testing MoniGoManiHyperStrategy.py:
freqtrade backtesting -s MoniGoManiHyperStrategy -c ./user_data/mgm-config.json -c ./user_data/mgm-config-private.json --timerange 20210101-20210316 --enable-protectionsTotal Average Signal Importance Calculation (with the Total-Overall-Signal-Importance-Calculator.py):
python ./user_data/mgm_tools/Total-Overall-Signal-Importance-Calculator.pyRetrieve and apply a current Binance-Top-Volume-StaticPairList.json file (using Binance-Retrieve-Top-Volume-StaticPairList.json):
freqtrade test-pairlist -c ./user_data/mgm_tools/Binance-Retrieve-Top-Volume-StaticPairList.json --quote USDT --print-json | tail -n 1 | jq '.|{exchange: { pair_whitelist: .}}' > ./user_data/mgm_pair_lists/Binance-USDT-Top-Volume-StaticPairList.json && jq 'del(.exchange.pair_whitelist )' ./user_data/mgm-config.json > ./tmp.json && jq -s '.[0] * .[1]' ./tmp.json ./user_data/mgm_pair_lists/Binance-USDT-Top-Volume-StaticPairList.json > ./user_data/mgm-config.json && rm ./tmp.json && jq '.' ./user_data/mgm-config.jsonDownload Candle Data:
freqtrade download-data --timerange 20201201-20210316 -t 5m 1h -c ./user_data/mgm-config.json -c ./user_data/mgm-config-private.json- Feel free to join our community CryptoStonksShallRise on Discord, there you can follow/participate in the Official MoniGoMani Channels:
#moni-go-mani-announcements#moni-go-mani-updates#moni-go-mani-github#moni-go-mani-development(Only available to MoniGoMani Developers!)#moni-go-mani-testing#moni-go-mani-help(Be sure to take your time to read the Documentation thoroughly before asking questions though!)#moni-go-mani-cluster-releases(Only available to the MoniGoMani Cluster Maintainer & MoniGoMani Developers, for now!)#moni-go-mani-setup-releases
More general chats for Technical Analysis, Freqtrade, Iconomi and Random discussion are also available there 🙂
MoniGoMani's planned section lives under the Issues section! (Don't be scared GitHub likes to pick bad names for things, but also don't abuse this for common questions though!) This is where we'll keep track of all New Feature, Feature Enhancements and BugFixes and it should be the ideal place to follow the status of the project more in depth or to contribute more directly towards it! 🤝
To keep track of what's exactly planned for the next release you can also check the Milestones section!
MoniGoMani's ChangeLog can be read under the Releases section!
(You can also check the Older Legacy ChangeLog to see the very beginning of MGM)
Freqtrade is the well known open source crypto day-trading bot that makes this strategy possible!
It's completely free to use and alter and has many amazing features.
Big thank you to xmatthias and everyone who helped on it!
- Official Freqtrade Website
- Official Freqtrade GitHub Repository
- Official Freqtrade Discord Server- Sigmoid Buy/Sell Signals
Can't wait until MoniGoMani is fully on point? Or is this all too technical for you? Check out ICONOMI!
Instead of buying loose individual crypto manually like you usually do on exchanges, this platform has mostly been created to buy & hodl Investment Strategies.
ICONOMI strategies are owned by Strategy Managers, these are often day-trades / technical analysts by profession so in general they have quite a good idea what they are doing.
Each investment strategy contains up to ±20 different coins with a percentage allocated to each one. The managers will often re-balance these percentages towards coins they'll think will be profitable.
There are fees tied to each strategy, and it's up to the manager of each strategy to pick the percentages of fees for his/her strategy. Usually strategies that are re-balanced often (aka market being watched more actively) or larger strategies with a good reputation ask higher fees. However, fees are only charged if new profits have been made, so they are quite in the benefit of the user. More info on fees in general can be found here, and more info on Performance fees can be found here.
In general this is a good platform to invest into when you still need to start learning Technical Analysis, when you don't have time to monitor the status of the market or when you don't feel confident trading your own funds. Since here you have strategy owners "doing the day-trading for you" by re-balancing the strategies & the percentages of coins in them.
If you join please use my referral link! => (https://www.iconomi.com/register?ref=JdFzz) 🙏 (Then a percentage of your fees that you have to pay anyways to the strategy owners and ICONOMI will go to me instead, which is a neat win-win way for us both to support me for my work on MGM!)
- Crypto Knowledge Pool (CKP): A community influenced strategy
- CKP's Telegram Chat: If you want to vote if the coins will go up or down and hear about interesting news or ask questions. When I wrote this they we're right about 65% of the time. The manager will take the results into consideration when altering the strategy.
- Knepala: The personal strategy of the owner of CKP, most of the time it does even better than CKP itself.
- Look on ICONOMI for more strategies you deem interesting 🙂
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