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Gerald Lonlas
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# Freqtrade strategies
This Git repo contains free buy/sell strategies for [Freqtrade](https://github.com/gcarq/freqtrade) >= `0.16.0`.
This Git repo contains free buy/sell strategies for [Freqtrade](https://github.com/freqtrade/freqtrade) >= `0.16.0`.
## Disclaimer
@@ -13,7 +13,7 @@ Always start by testing strategies with a backtesting then run the
trading bot in Dry-run. Do not engage money before you understand how
it works and what profit/loss you should expect.
I strongly recommend you to have coding and Python knowledge. Do not
We strongly recommend you to have coding and Python knowledge. Do not
hesitate to read the source code and understand the mechanism of this
bot.
@@ -26,53 +26,37 @@ bot.
- [How were tested the strategies?](#how-were-tested-the-strategies)
- [How to install a strategy?](#how-to-install-a-strategy)
- [How to test a strategy?](#how-to-test-a-strategy)
- [Which coins were tested?](#which-coins-were-tested)
- [Can I have your configuration file?](#can-i-have-your-configuration-file)
- [Can I have your dataset?](#can-i-have-your-dataset)
- [How did you build dataset?](#how-did-you-build-dataset)
- [How to create/optimize a strategy?](https://github.com/gcarq/freqtrade/blob/develop/docs/bot-optimization.md)
- [Offer me a coffee](#offer-me-a-coffee)
- [How to create/optimize a strategy?](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md)
## Free trading strategies
Value below are result from backtesting from 2018-01-10 to 2018-01-30 and
`experimental.sell_profit_only` enabled. More detail on each strategy
page.
| Strategy | Buy count | AVG profit % | Total profit | AVG duration |
|-----------|-----------|--------------|--------------|--------------|
| [Strategy 001](https://github.com/glonlas/freqtrade-strategies/issues/1) | 55 | 0.05 | 0.00012102 | 476.1 |
| [Strategy 002](https://github.com/glonlas/freqtrade-strategies/issues/2) | 9 | 3.21 | 0.00114807 | 189.4 |
| [Strategy 003](https://github.com/glonlas/freqtrade-strategies/issues/3) | 14 | 1.47 | 0.00081740 | 227.5 |
| [Strategy 004](https://github.com/glonlas/freqtrade-strategies/issues/4) | 37 | 0.69 | 0.00102128 | 367.3 |
| [Strategy 005](https://github.com/glonlas/freqtrade-strategies/issues/11) | 180 | 1.16 | 0.00827589 | 156.2 |
| Strategy | Buy count | AVG profit % | Total profit | AVG duration | Ticker tested | Backtest period |
|-----------|-----------|--------------|--------------|--------------|--------------|-----------------|
| [Strategy 001](https://github.com/freqtrade/freqtrade-strategies/issues/1) | 55 | 0.05 | 0.00012102 | 476.1 | 5m | 2018-01-10 to 2018-01-30 |
| [Strategy 002](https://github.com/freqtrade/freqtrade-strategies/issues/2) | 9 | 3.21 | 0.00114807 | 189.4 | 5m | 2018-01-10 to 2018-01-30 |
| [Strategy 003](https://github.com/freqtrade/freqtrade-strategies/issues/3) | 14 | 1.47 | 0.00081740 | 227.5 | 5m | 2018-01-10 to 2018-01-30 |
| [Strategy 004](https://github.com/freqtrade/freqtrade-strategies/issues/4) | 37 | 0.69 | 0.00102128 | 367.3 | 5m | 2018-01-10 to 2018-01-30 |
| [Strategy 005](https://github.com/freqtrade/freqtrade-strategies/issues/11) | 180 | 1.16 | 0.00827589 | 156.2 | 5m | 2018-01-10 to 2018-01-30 |
Strategies from this repo are free to use and feel free to update them.
Strategies from this repo are free to use. Feel free to update them.
Most of them were designed from Hyperopt calculations.
## Contributes
Feel free to send your comments, optimizations and requests via an
[Issue ticket](https://github.com/glonlas/freqtrade-strategies/issues/new).
### Strategy requests
Are you looking to implement a new strategy, or one found on atrading
Forum/Chan?
You can request it via
[Issue ticket](https://github.com/glonlas/freqtrade-strategies/issues/new).
Please follow the template questions. Request that does not follow the
template will be removed. I cannot promise to implement all of them,
but will do my best to help.
## Share your own strategies and contribute to this repo
Feel free to send your strategies, comments, optimizations and pull requests via an
[Issue ticket](https://github.com/freqtrade/freqtrade-strategies/issues/new).
## FAQ
### What is Freqtrade?
[Freqtrade](https://github.com/gcarq/freqtrade) is a Simple High
[Freqtrade](https://github.com/freqtrade) is a Simple High
frequency trading bot for crypto currencies designed to support multi
exchanges and be controlled via Telegram built by [gcarq@](https://github.com/gcarq).
This bot is similar other trading bot like
[Gekko](https://github.com/askmike/gekko), and
[Zenbot](https://github.com/DeviaVir/zenbot)
exchanges and be controlled via Telegram built by [gcarq@](https://github.com/gcarq) and the
[core-dev team](https://github.com/orgs/freqtrade/teams/core-dev).
### What includes these strategies?
Each Strategies includes:
@@ -85,124 +69,38 @@ Each Strategies includes:
- [x] **Backtesting results**
### How were tested the strategies?
All strategies are tested with the dataset from this repo. The data set
is located into [user_data/data](https://github.com/glonlas/freqtrade-strategies/tree/master/user_data/data) folder.
For each strategies, I run backtests for 2 Period and 2 parameters:
`experimental.sell_profit_only` enabled and
`experimental.sell_profit_only` disabled
#### Period 1: From 2017-11-19 to 2017-12-20
1. `experimental.sell_profit_only` at `true` (Config file [user_data/config-profit-on.json](https://github.com/glonlas/freqtrade-strategies/blob/master/user_data/config-profit-on.json)).
2. `experimental.sell_profit_only` at `false` (Config file [user_data/config-profit-off.json](https://github.com/glonlas/freqtrade-strategies/blob/master/user_data/config-profit-off.json)).
#### Period 2: From 2017-12-19 to 2017-01-20
1. `experimental.sell_profit_only` at `true` (Config file [user_data/config-profit-on.json](https://github.com/glonlas/freqtrade-strategies/blob/master/user_data/config-profit-on.json)).
2. `experimental.sell_profit_only` at `false` (Config file [user_data/config-profit-off.json](https://github.com/glonlas/freqtrade-strategies/blob/master/user_data/config-profit-off.json)).
All strategies tests are explain on their own tickets.
For each strategies, we generally run backtests twice with `experimental.sell_profit_only`
enabled and disabled.
### How to install a strategy?
First you need a [working Freqtrade](https://github.com/gcarq/freqtrade/blob/feature/custom_strategy/docs/index.md)
First you need a [working Freqtrade](https://github.com/freqtrade/freqtrade/blob/feature/custom_strategy/docs/index.md)
in version >= 0.16.0.
**Note:** This version is not merged yet but you can find into the branch `feature/custom_strategy`.
```bash
git clone https://github.com/gcarq/freqtrade.git
git checkout feature/custom_strategy
```
Once you have the bot on the right version, follow this steps:
1. Select the strategy you want. All strategies of the repo are into
(user_data/strategies](https://github.com/glonlas/freqtrade-strategies/tree/feature/custom_strategy/user_data/strategies)
(user_data/strategies](https://github.com/freqtrade/freqtrade-strategies/tree/feature/custom_strategy/user_data/strategies)
2. Copy the strategy file
3. Paste it into your `user_data/strategies` folder
4. Run the bot with the parameter `-s <STRATEGY_FILE_NAME_WITHOUT_.py>` (ex: `python3 ./freqtrade/main.py -s strategy001`)
4. Run the bot with the parameter `-s <STRATEGY CLASS NAME>` (ex: `python3 ./freqtrade/main.py -s Strategy001`)
### How to test a strategy?
Let assume you have selected the strategy `strategy-001.py`:
Let assume you have selected the strategy `strategy001.py`:
**Simple backtesting**
```bash
python3 ./freqtrade/main.py -s strategy-001 backtesting --realistic-simulation
python3 ./freqtrade/main.py -s Strategy001 backtesting --realistic-simulation
```
**Refresh your test data**
```bash
python3 ./freqtrade/main.py -s strategy-001 backtesting --realistic-simulation -r
python3 ./freqtrade/main.py -s Strategy001 backtesting --realistic-simulation -r
```
**Test with live data**
```bash
python3 ./freqtrade/main.py -s strategy-001 backtesting --realistic-simulation -l
python3 ./freqtrade/main.py -s Strategy001 backtesting --realistic-simulation -l
```
### Which coins were tested?
You will find the list of coin tested into the configuration files
(`user_data/config-profit-on.json` and
`user_data/config-profit-off.json`)
| Pair | Tested |
|-------|--------|
| BTC_ADA | Yes
| BTC_NEO | Yes |
| BTC_NXT | Yes |
| BTC_MCO | Yes |
| BTC_ETH | Yes |
| BTC_BCC | Yes |
| BTC_VOX | Yes |
| BTC_GUP | Yes |
| BTC_SC | Yes |
| BTC_VTC | Yes |
| BTC_STRAT | Yes |
| BTC_OMG | Yes |
| BTC_OK | Yes |
| BTC_EDG | Yes |
| BTC_STORJ | Yes |
| BTC_EMC2 | Yes |
| BTC_XLM | Yes |
| BTC_LSK | Yes |
| BTC_SYS | Yes |
| BTC_POWR | Yes |
| BTC_PAY | Yes |
| BTC_DGB | Yes |
| BTC_ETC | Yes |
| BTC_XRP | Yes |
| BTC_LTC | Yes |
| BTC_IOP | Yes |
| BTC_RCN | Yes |
| BTC_BTG | Yes |
| BTC_MONA | Yes |
| BTC_SALT | Yes |
| BTC_DASH | Yes |
| BTC_QTUM | Yes |
| BTC_CVC | Yes |
| BTC_KMD | Yes |
| BTC_XEM | Yes |
| BTC_XMR | Yes |
| BTC_ZEC | Yes |
| BTC_WAVES | Yes |
| BTC_PIVX | Yes |
| BTC_XZC | Yes |
| BTC_DOGE | No, this pair is blacklisted |
## Can I have your configuration file?
You will find them into [user_data/](https://github.com/glonlas/freqtrade-strategies/tree/master/user_data) folder.
## Can I have your datasets?
Yes of course! Datasets are into
[user_data/data](https://github.com/glonlas/freqtrade-strategies/tree/master/user_data/data)
folder. Download and use them.
## How did you build dataset?
I am using data collected from Bittrex and run the script
`scripts/extract_data.py`
```bash
python3 scripts/extract_data.py -f user_data/data/complete_data -d user_data/data/2017-11-19_2017-12-19 -s 2017-11-19 -e 2017-12-20
python3 scripts/extract_data.py -f user_data/data/complete_data -d user_data/data/2017-12-19_2018-01-19 -s 2017-12-19 -e 2018-01-20
```
# Offer me a coffee
This repo is made for you to improve your trading strategies. If you are
happy with the result of your strategy, feel free to offer me a coffee :)
- BTC: 1KouEQdEKGiFGvm9iCb5K9pkUqnsASqmGS
- ETH: 0x767D8AfB3B31131cBbf5b7318D2046996c9a40f2
- LTC: LXFPwMs38DMj6ecD4xWEPnWjNAjp78uNZM
You will find them into [user_data/](https://github.com/freqtrade/freqtrade-strategies/tree/master/user_data) folder.