Merge branch 'develop' into feat/short

.github/FUNDING.yml

@@ -0,0 +1,3 @@
+# These are supported funding model platforms
+
+github: [xmatthias]

.gitignore

@@ -10,6 +10,9 @@ freqtrade-plot.html
 freqtrade-profit-plot.html
 freqtrade/rpc/api_server/ui/*
 
+# Macos related
+.DS_Store
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

README.md

@@ -5,10 +5,14 @@
 [![Documentation](https://readthedocs.org/projects/freqtrade/badge/)](https://www.freqtrade.io)
 [![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
 
-Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
+Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
 
 ![freqtrade](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/freqtrade-screenshot.png)
 
+## Sponsored promotion
+
+[![tokenbot-promo](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/TokenBot-Freqtrade-banner.png)](https://tokenbot.com/?utm_source=github&utm_medium=freqtrade&utm_campaign=algodevs)
+
 ## Disclaimer
 
 This software is for educational purposes only. Do not risk money which
@@ -31,7 +35,7 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
 - [X] [FTX](https://ftx.com)
 - [X] [Gate.io](https://www.gate.io/ref/6266643)
 - [X] [Kraken](https://kraken.com/)
-- [X] [OKEX](https://www.okex.com/)
+- [X] [OKX](https://www.okx.com/)
 - [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
 
 ### Community tested
@@ -57,9 +61,9 @@ Please find the complete documentation on the [freqtrade website](https://www.fr
 - [x] **Edge position sizing** Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market. [Learn more](https://www.freqtrade.io/en/stable/edge/).
 - [x] **Whitelist crypto-currencies**: Select which crypto-currency you want to trade or use dynamic whitelists.
 - [x] **Blacklist crypto-currencies**: Select which crypto-currency you want to avoid.
+- [x] **Builtin WebUI**: Builtin web UI to manage your bot.
 - [x] **Manageable via Telegram**: Manage the bot with Telegram.
-- [x] **Display profit/loss in fiat**: Display your profit/loss in 33 fiat.
-- [x] **Daily summary of profit/loss**: Provide a daily summary of your profit/loss.
+- [x] **Display profit/loss in fiat**: Display your profit/loss in fiat currency.
 - [x] **Performance status report**: Provide a performance status of your current trades.
 
 ## Quick start

config_examples/config_full.example.json

@@ -88,6 +88,7 @@
         "key": "your_exchange_key",
         "secret": "your_exchange_secret",
         "password": "",
+        "log_responses": false,
         "ccxt_config": {},
         "ccxt_async_config": {},
         "pair_whitelist": [

docs/backtesting.md

@@ -313,6 +313,7 @@ A backtesting result will look like that:
 | Avg. Duration Winners | 4:23:00             |
 | Avg. Duration Loser   | 6:55:00             |
 | Rejected Buy signals  | 3089                |
+| Entry/Exit Timeouts   | 0 / 0               |
 |                       |                     |
 | Min balance           | 0.00945123 BTC      |
 | Max balance           | 0.01846651 BTC      |
@@ -406,6 +407,7 @@ It contains some useful key metrics about performance of your strategy on backte
 | Avg. Duration Winners  | 4:23:00             |
 | Avg. Duration Loser    | 6:55:00             |
 | Rejected Buy signals   | 3089                |
+| Entry/Exit Timeouts    | 0 / 0               |
 |                        |                     |
 | Min balance            | 0.00945123 BTC      |
 | Max balance            | 0.01846651 BTC      |
@@ -435,6 +437,7 @@ It contains some useful key metrics about performance of your strategy on backte
 - `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade).
 - `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
 - `Rejected Buy signals`: Buy signals that could not be acted upon due to max_open_trades being reached.
+- `Entry/Exit Timeouts`: Entry/exit orders which did not fill (only applicable if custom pricing is used).
 - `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period.
 - `Drawdown (Account)`: Maximum Account Drawdown experienced. Calculated as $(Absolute Drawdown) / (DrawdownHigh + startingBalance)$.
 - `Drawdown`: Maximum, absolute drawdown experienced. Difference between Drawdown High and Subsequent Low point.

docs/bot-basics.md

@@ -63,6 +63,7 @@ This loop will be repeated again and again until the bot is stopped.
   * Check position adjustments for open trades if enabled and call `adjust_trade_position()` to determine if an additional order is requested.
   * Call `custom_stoploss()` and `custom_sell()` to find custom exit points.
   * For sells based on sell-signal and custom-sell: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle).
+  * Check for Order timeouts, either via the `unfilledtimeout` configuration, or via `check_buy_timeout()` / `check_sell_timeout()` strategy callbacks.
 * Generate backtest report output
 
 !!! Note

docs/data-analysis.md

@@ -1,6 +1,6 @@
-# Analyzing bot data with Jupyter notebooks  
+# Analyzing bot data with Jupyter notebooks
 
-You can analyze the results of backtests and trading history easily using Jupyter notebooks. Sample notebooks are located at `user_data/notebooks/` after initializing the user directory with `freqtrade create-userdir --userdir user_data`.  
+You can analyze the results of backtests and trading history easily using Jupyter notebooks. Sample notebooks are located at `user_data/notebooks/` after initializing the user directory with `freqtrade create-userdir --userdir user_data`.
 
 ## Quick start with docker
 
@@ -41,32 +41,35 @@ ipython kernel install --user --name=freqtrade
 !!! Warning
     Some tasks don't work especially well in notebooks. For example, anything using asynchronous execution is a problem for Jupyter. Also, freqtrade's primary entry point is the shell cli, so using pure python in a notebook bypasses arguments that provide required objects and parameters to helper functions. You may need to set those values or create expected objects manually.
 
-## Recommended workflow  
+## Recommended workflow
 
-| Task | Tool |  
-  --- | ---  
-Bot operations | CLI  
+| Task | Tool |
+  --- | ---
+Bot operations | CLI
 Repetitive tasks | Shell scripts
-Data analysis & visualization | Notebook  
+Data analysis & visualization | Notebook
 
 1. Use the CLI to
+
     * download historical data
     * run a backtest
     * run with real-time data
-    * export results  
+    * export results
 
 1. Collect these actions in shell scripts
+
     * save complicated commands with arguments
-    * execute multi-step operations  
+    * execute multi-step operations
     * automate testing strategies and preparing data for analysis
 
 1. Use a notebook to
+
     * visualize data
-    * munge and plot to generate insights
+    * mangle and plot to generate insights
 
-## Example utility snippets  
+## Example utility snippets
 
-### Change directory to root  
+### Change directory to root
 
 Jupyter notebooks execute from the notebook directory. The following snippet searches for the project root, so relative paths remain consistent.
 

docs/exchanges.md

@@ -182,13 +182,13 @@ Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force)
 For Kucoin, please add `"KCS/<STAKE>"` to your blacklist to avoid issues.
 Accounts having KCS accounts use this to pay for fees - if your first trade happens to be on `KCS`, further trades will consume this position and make the initial KCS trade unsellable as the expected amount is not there anymore.
 
-## OKEX
+## OKX
 
-OKEX requires a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
+OKX requires a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
 
 ```json
 "exchange": {
-    "name": "okex",
+    "name": "okx",
     "key": "your_exchange_key",
     "secret": "your_exchange_secret",
     "password": "your_exchange_api_key_password",
@@ -197,7 +197,7 @@ OKEX requires a passphrase for each api key, you will therefore need to add this
 ```
 
 !!! Warning
-    OKEX only provides 100 candles per api call. Therefore, the strategy will only have a pretty low amount of data available in backtesting mode.
+    OKX only provides 100 candles per api call. Therefore, the strategy will only have a pretty low amount of data available in backtesting mode.
 
 ## Gate.io
 

docs/hyperopt.md

@@ -116,7 +116,7 @@ optional arguments:
                         ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss,
                         SharpeHyperOptLoss, SharpeHyperOptLossDaily,
                         SortinoHyperOptLoss, SortinoHyperOptLossDaily,
-                        CalmarHyperOptLoss, MaxDrawDownHyperOptLoss
+                        CalmarHyperOptLoss, MaxDrawDownHyperOptLoss, ProfitDrawDownHyperOptLoss
   --disable-param-export
                         Disable automatic hyperopt parameter export.
   --ignore-missing-spaces, --ignore-unparameterized-spaces
@@ -525,6 +525,7 @@ Currently, the following loss functions are builtin:
 * `SortinoHyperOptLossDaily` - optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation.
 * `MaxDrawDownHyperOptLoss` - Optimizes Maximum drawdown.
 * `CalmarHyperOptLoss` - Optimizes Calmar Ratio calculated on trade returns relative to max drawdown.
+* `ProfitDrawDownHyperOptLoss` - Optimizes by max Profit & min Drawdown objective. `DRAWDOWN_MULT` variable within the hyperoptloss file can be adjusted to be stricter or more flexible on drawdown purposes.
 
 Creation of a custom loss function is covered in the [Advanced Hyperopt](advanced-hyperopt.md) part of the documentation.
 

docs/index.md

@@ -11,7 +11,7 @@
 
 ## Introduction
 
-Freqtrade is a crypto-currency algorithmic trading software developed in python (3.8+) and supported on Windows, macOS and Linux.
+Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
 
 !!! Danger "DISCLAIMER"
     This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.
@@ -20,6 +20,12 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python
 
     We strongly recommend you to have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms and techniques implemented in it.
 
+![freqtrade screenshot](assets/freqtrade-screenshot.png)
+
+## Sponsored promotion
+
+[![tokenbot-promo](assets/TokenBot-Freqtrade-banner.png)](https://tokenbot.com/?utm_source=github&utm_medium=freqtrade&utm_campaign=algodevs)
+
 ## Features
 
 - Develop your Strategy: Write your strategy in python, using [pandas](https://pandas.pydata.org/). Example strategies to inspire you are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
@@ -29,7 +35,7 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python
 - Select markets: Create your static list or use an automatic one based on top traded volumes and/or prices (not available during backtesting). You can also explicitly blacklist markets you don't want to trade.
 - Run: Test your strategy with simulated money (Dry-Run mode) or deploy it with real money (Live-Trade mode).
 - Run using Edge (optional module): The concept is to find the best historical [trade expectancy](edge.md#expectancy) by markets based on variation of the stop-loss and then allow/reject markets to trade. The sizing of the trade is based on a risk of a percentage of your capital.
-- Control/Monitor: Use Telegram or a REST API (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
+- Control/Monitor: Use Telegram or a WebUI (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
 - Analyse: Further analysis can be performed on either Backtesting data or Freqtrade trading history (SQL database), including automated standard plots, and methods to load the data into [interactive environments](data-analysis.md).
 
 ## Supported exchange marketplaces
@@ -41,7 +47,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
 - [X] [FTX](https://ftx.com)
 - [X] [Gate.io](https://www.gate.io/ref/6266643)
 - [X] [Kraken](https://kraken.com/)
-- [X] [OKEX](https://www.okex.com/)
+- [X] [OKX](https://www.okx.com/)
 - [ ] [potentially many others through <img alt="ccxt" width="30px" src="assets/ccxt-logo.svg" />](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
 
 ### Community tested

docs/installation.md

@@ -24,7 +24,7 @@ The easiest way to install and run Freqtrade is to clone the bot Github reposito
     The `stable` branch contains the code of the last release (done usually once per month on an approximately one week old snapshot of the `develop` branch to prevent packaging bugs, so potentially it's more stable).
 
 !!! Note
-    Python3.7 or higher and the corresponding `pip` are assumed to be available. The install-script will warn you and stop if that's not the case. `git` is also needed to clone the Freqtrade repository.  
+    Python3.8 or higher and the corresponding `pip` are assumed to be available. The install-script will warn you and stop if that's not the case. `git` is also needed to clone the Freqtrade repository.  
     Also, python headers (`python<yourversion>-dev` / `python<yourversion>-devel`) must be available for the installation to complete successfully.
 
 !!! Warning "Up-to-date clock"
@@ -54,7 +54,7 @@ We've included/collected install instructions for Ubuntu, MacOS, and Windows. Th
 OS Specific steps are listed first, the [Common](#common) section below is necessary for all systems.
 
 !!! Note
-    Python3.7 or higher and the corresponding pip are assumed to be available.
+    Python3.8 or higher and the corresponding pip are assumed to be available.
 
 === "Debian/Ubuntu"
     #### Install necessary dependencies
@@ -69,7 +69,7 @@ OS Specific steps are listed first, the [Common](#common) section below is neces
 
 === "RaspberryPi/Raspbian"
     The following assumes the latest [Raspbian Buster lite image](https://www.raspberrypi.org/downloads/raspbian/).
-    This image comes with python3.7 preinstalled, making it easy to get freqtrade up and running.
+    This image comes with python3.9 preinstalled, making it easy to get freqtrade up and running.
 
     Tested using a Raspberry Pi 3 with the Raspbian Buster lite image, all updates applied.
 
@@ -169,7 +169,7 @@ You can as well update, configure and reset the codebase of your bot with `./scr
 ** --install **
 
 With this option, the script will install the bot and most dependencies:
-You will need to have git and python3.7+ installed beforehand for this to work.
+You will need to have git and python3.8+ installed beforehand for this to work.
 
 * Mandatory software as: `ta-lib`
 * Setup your virtualenv under `.env/`

docs/plotting.md

@@ -322,8 +322,8 @@ optional arguments:
                         Specify what timerange of data to use.
   --export EXPORT       Export backtest results, argument are: trades.
                         Example: `--export=trades`
-  --export-filename PATH
-                        Save backtest results to the file with this filename.
+  --export-filename PATH, --backtest-filename PATH
+                        Use backtest results from this filename.
                         Requires `--export` to be set as well. Example:
                         `--export-filename=user_data/backtest_results/backtest
                         _today.json`

docs/requirements-docs.txt

@@ -1,4 +1,4 @@
 mkdocs==1.2.3
-mkdocs-material==8.1.8
+mkdocs-material==8.1.10
 mdx_truly_sane_lists==1.2
 pymdown-extensions==9.1