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Merge branch 'develop' into feature/fetch-public-trades

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Matthias
2024-06-04 19:49:27 +02:00
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29
docs/configuration.md
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@@ -568,7 +568,14 @@ The possible values are: `GTC` (default), `FOK` or `IOC`.
This is ongoing work. For now, it is supported only for binance, gate and kucoin.
Please don't change the default value unless you know what you are doing and have researched the impact of using different values for your particular exchange.
### What values can be used for fiat_display_currency?
### Fiat conversion
Freqtrade uses the Coingecko API to convert the coin value to it's corresponding fiat value for the Telegram reports.
The FIAT currency can be set in the configuration file as `fiat_display_currency`.
Removing `fiat_display_currency` completely from the configuration will skip initializing coingecko, and will not show any FIAT currency conversion. This has no importance for the correct functioning of the bot.
#### What values can be used for fiat_display_currency?
The `fiat_display_currency` configuration parameter sets the base currency to use for the
conversion from coin to fiat in the bot Telegram reports.
@@ -587,7 +594,25 @@ The valid values are:
"BTC", "ETH", "XRP", "LTC", "BCH", "BNB"
```
Removing `fiat_display_currency` completely from the configuration will skip initializing coingecko, and will not show any FIAT currency conversion. This has no importance for the correct functioning of the bot.
#### Coingecko Rate limit problems
On some IP ranges, coingecko is heavily rate-limiting.
In such cases, you may want to add your coingecko API key to the configuration.
``` json
{
"fiat_display_currency": "USD",
"coingecko": {
"api_key": "your-api",
"is_demo": true
}
}
```
Freqtrade supports both Demo and Pro coingecko API keys.
The Coingecko API key is NOT required for the bot to function correctly.
It is only used for the conversion of coin to fiat in the Telegram reports, which usually also work without API key.
## Using Dry-run mode

34
docs/data-download.md
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@@ -24,10 +24,10 @@ usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[--days INT] [--new-pairs-days INT]
[--include-inactive-pairs]
[--timerange TIMERANGE] [--dl-trades]
[--exchange EXCHANGE]
[--convert] [--exchange EXCHANGE]
[-t TIMEFRAMES [TIMEFRAMES ...]] [--erase]
[--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
[--data-format-trades {json,jsongz,hdf5,feather}]
[--data-format-trades {json,jsongz,hdf5,feather,parquet}]
[--trading-mode {spot,margin,futures}]
[--prepend]
@@ -48,6 +48,11 @@ options:
--dl-trades Download trades instead of OHLCV data. The bot will
resample trades to the desired timeframe as specified
as --timeframes/-t.
--convert Convert downloaded trades to OHLCV data. Only
applicable in combination with `--dl-trades`. Will be
automatic for exchanges which don't have historic
OHLCV (e.g. Kraken). If not provided, use `trades-to-
ohlcv` to convert trades data to OHLCV data.
--exchange EXCHANGE Exchange name. Only valid if no config is provided.
-t TIMEFRAMES [TIMEFRAMES ...], --timeframes TIMEFRAMES [TIMEFRAMES ...]
Specify which tickers to download. Space-separated
@@ -57,7 +62,7 @@ options:
--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded candle (OHLCV) data.
(default: `feather`).
--data-format-trades {json,jsongz,hdf5,feather}
--data-format-trades {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded trades data. (default:
`feather`).
--trading-mode {spot,margin,futures}, --tradingmode {spot,margin,futures}
@@ -471,15 +476,20 @@ ETH/USDT 5m, 15m, 30m, 1h, 2h, 4h
## Trades (tick) data
By default, `download-data` sub-command downloads Candles (OHLCV) data. Some exchanges also provide historic trade-data via their API.
By default, `download-data` sub-command downloads Candles (OHLCV) data. Most exchanges also provide historic trade-data via their API.
This data can be useful if you need many different timeframes, since it is only downloaded once, and then resampled locally to the desired timeframes.
Since this data is large by default, the files use the feather fileformat by default. They are stored in your data-directory with the naming convention of `<pair>-trades.feather` (`ETH_BTC-trades.feather`). Incremental mode is also supported, as for historic OHLCV data, so downloading the data once per week with `--days 8` will create an incremental data-repository.
Since this data is large by default, the files use the feather file format by default. They are stored in your data-directory with the naming convention of `<pair>-trades.feather` (`ETH_BTC-trades.feather`). Incremental mode is also supported, as for historic OHLCV data, so downloading the data once per week with `--days 8` will create an incremental data-repository.
To use this mode, simply add `--dl-trades` to your call. This will swap the download method to download trades, and resamples the data locally.
To use this mode, simply add `--dl-trades` to your call. This will swap the download method to download trades.
If `--convert` is also provided, the resample step will happen automatically and overwrite eventually existing OHLCV data for the given pair/timeframe combinations.
!!! Warning "do not use"
You should not use this unless you're a kraken user. Most other exchanges provide OHLCV data with sufficient history.
!!! Warning "Do not use"
You should not use this unless you're a kraken user (Kraken does not provide historic OHLCV data).
Most other exchanges provide OHLCV data with sufficient history, so downloading multiple timeframes through that method will still proof to be a lot faster than downloading trades data.
!!! Note "Kraken user"
Kraken users should read [this](exchanges.md#historic-kraken-data) before starting to download data.
Example call:
@@ -490,12 +500,6 @@ freqtrade download-data --exchange kraken --pairs XRP/EUR ETH/EUR --days 20 --dl
!!! Note
While this method uses async calls, it will be slow, since it requires the result of the previous call to generate the next request to the exchange.
!!! Warning
The historic trades are not available during Freqtrade dry-run and live trade modes because all exchanges tested provide this data with a delay of few 100 candles, so it's not suitable for real-time trading.
!!! Note "Kraken user"
Kraken users should read [this](exchanges.md#historic-kraken-data) before starting to download data.
## Next step
Great, you now have backtest data downloaded, so you can now start [backtesting](backtesting.md) your strategy.
Great, you now have some data downloaded, so you can now start [backtesting](backtesting.md) your strategy.

7
docs/exchanges.md
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@@ -127,6 +127,13 @@ These settings will be checked on startup, and freqtrade will show an error if t
Freqtrade will not attempt to change these settings.
## Bingx
BingX supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "IOC" (immediate-or-cancel) and "PO" (Post only) settings.
!!! Tip "Stoploss on Exchange"
Bingx supports `stoploss_on_exchange` and can use both stop-limit and stop-market orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
## Kraken
Kraken supports [time_in_force](configuration.md#understand-order_time_in_force) with settings "GTC" (good till cancelled), "IOC" (immediate-or-cancel) and "PO" (Post only) settings.

2
docs/freqai-feature-engineering.md
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@@ -224,7 +224,7 @@ where $W_i$ is the weight of data point $i$ in a total set of $n$ data points. B
## Building the data pipeline
By default, FreqAI builds a dynamic pipeline based on user congfiguration settings. The default settings are robust and designed to work with a variety of methods. These two steps are a `MinMaxScaler(-1,1)` and a `VarianceThreshold` which removes any column that has 0 variance. Users can activate other steps with more configuration parameters. For example if users add `use_SVM_to_remove_outliers: true` to the `freqai` config, then FreqAI will automatically add the [`SVMOutlierExtractor`](#identifying-outliers-using-a-support-vector-machine-svm) to the pipeline. Likewise, users can add `principal_component_analysis: true` to the `freqai` config to activate PCA. The [DissimilarityIndex](#identifying-outliers-with-the-dissimilarity-index-di) is activated with `DI_threshold: 1`. Finally, noise can also be added to the data with `noise_standard_deviation: 0.1`. Finally, users can add [DBSCAN](#identifying-outliers-with-dbscan) outlier removal with `use_DBSCAN_to_remove_outliers: true`.
By default, FreqAI builds a dynamic pipeline based on user configuration settings. The default settings are robust and designed to work with a variety of methods. These two steps are a `MinMaxScaler(-1,1)` and a `VarianceThreshold` which removes any column that has 0 variance. Users can activate other steps with more configuration parameters. For example if users add `use_SVM_to_remove_outliers: true` to the `freqai` config, then FreqAI will automatically add the [`SVMOutlierExtractor`](#identifying-outliers-using-a-support-vector-machine-svm) to the pipeline. Likewise, users can add `principal_component_analysis: true` to the `freqai` config to activate PCA. The [DissimilarityIndex](#identifying-outliers-with-the-dissimilarity-index-di) is activated with `DI_threshold: 1`. Finally, noise can also be added to the data with `noise_standard_deviation: 0.1`. Finally, users can add [DBSCAN](#identifying-outliers-with-dbscan) outlier removal with `use_DBSCAN_to_remove_outliers: true`.
!!! note "More information available"
Please review the [parameter table](freqai-parameter-table.md) for more information on these parameters.

1
docs/index.md
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@@ -41,6 +41,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
- [X] [Binance](https://www.binance.com/)
- [X] [Bitmart](https://bitmart.com/)
- [X] [BingX](https://bingx.com/invite/0EM9RX)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [HTX](https://www.htx.com/) (Former Huobi)
- [X] [Kraken](https://kraken.com/)

2
docs/installation.md
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@@ -286,7 +286,7 @@ cd freqtrade
#### Freqtrade install: Conda Environment
```bash
conda create --name freqtrade python=3.11
conda create --name freqtrade python=3.12
```
!!! Note "Creating Conda Environment"

2
docs/requirements-docs.txt
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@@ -1,6 +1,6 @@
markdown==3.6
mkdocs==1.6.0
mkdocs-material==9.5.22
mkdocs-material==9.5.25
mdx_truly_sane_lists==1.3
pymdown-extensions==10.8.1
jinja2==3.1.4

2
docs/rest-api.md
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@@ -161,7 +161,7 @@ freqtrade-client --config rest_config.json <command> [optional parameters]
| `delete_lock <lock_id>` | Deletes (disables) the lock by id.
| `locks add <pair>, <until>, [side], [reason]` | Locks a pair until "until". (Until will be rounded up to the nearest timeframe).
| `profit` | Display a summary of your profit/loss from close trades and some stats about your performance.
| `forceexit <trade_id>` | Instantly exits the given trade (Ignoring `minimum_roi`).
| `forceexit <trade_id> [order_type] [amount]` | Instantly exits the given trade (ignoring `minimum_roi`), using the given order type ("market" or "limit", uses your config setting if not specified), and the chosen amount (full sell if not specified).
| `forceexit all` | Instantly exits all open trades (Ignoring `minimum_roi`).
| `forceenter <pair> [rate]` | Instantly enters the given pair. Rate is optional. (`force_entry_enable` must be set to True)
| `forceenter <pair> <side> [rate]` | Instantly longs or shorts the given pair. Rate is optional. (`force_entry_enable` must be set to True)

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docs/stoploss.md
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@@ -30,6 +30,7 @@ The Order-type will be ignored if only one mode is available.
|----------|-------------|
| Binance | limit |
| Binance Futures | market, limit |
| Bingx | market, limit |
| HTX (former Huobi) | limit |
| kraken | market, limit |
| Gate | limit |

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docs/windows_installation.md
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@@ -5,6 +5,30 @@ We **strongly** recommend that Windows users use [Docker](docker_quickstart.md)
If that is not possible, try using the Windows Linux subsystem (WSL) - for which the Ubuntu instructions should work.
Otherwise, please follow the instructions below.
All instructions assume that python 3.9+ is installed and available.
## Clone the git repository
First of all clone the repository by running:
``` powershell
git clone https://github.com/freqtrade/freqtrade.git
```
Now, choose your installation method, either automatically via script (recommended) or manually following the corresponding instructions.
## Install freqtrade automatically
### Run the installation script
The script will ask you a few questions to determine which parts should be installed.
```powershell
Set-ExecutionPolicy -ExecutionPolicy Bypass
cd freqtrade
. .\setup.ps1
```
## Install freqtrade manually
!!! Note "64bit Python version"
@@ -14,17 +38,11 @@ Otherwise, please follow the instructions below.
!!! Hint
Using the [Anaconda Distribution](https://www.anaconda.com/distribution/) under Windows can greatly help with installation problems. Check out the [Anaconda installation section](installation.md#installation-with-conda) in the documentation for more information.
### 1. Clone the git repository
```bash
git clone https://github.com/freqtrade/freqtrade.git
```
### 2. Install ta-lib
### Install ta-lib
Install ta-lib according to the [ta-lib documentation](https://github.com/TA-Lib/ta-lib-python#windows).
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), Freqtrade provides these dependencies (in the binary wheel format) for the latest 3 Python versions (3.9, 3.10 and 3.11) and for 64bit Windows.
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), Freqtrade provides these dependencies (in the binary wheel format) for the latest 3 Python versions (3.9, 3.10, 3.11 and 3.12) and for 64bit Windows.
These Wheels are also used by CI running on windows, and are therefore tested together with freqtrade.
Other versions must be downloaded from the above link.