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https://github.com/coding-kitties/investing-algorithm-framework

Framework for developing, backtesting, and deploying automated trading algorithms and trading bots.
https://github.com/coding-kitties/investing-algorithm-framework

algorithmic-trading backtesting backtesting-trading-strategies cryptocurrency python trade trading trading-bot trading-bots trading-strategies

Last synced: about 2 months ago
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Framework for developing, backtesting, and deploying automated trading algorithms and trading bots.

Host: GitHub
URL: https://github.com/coding-kitties/investing-algorithm-framework
Owner: coding-kitties
License: apache-2.0
Created: 2019-12-18T11:20:36.000Z (almost 5 years ago)
Default Branch: main
Last Pushed: 2024-07-26T08:15:20.000Z (2 months ago)
Last Synced: 2024-07-26T09:37:45.998Z (2 months ago)
Topics: algorithmic-trading, backtesting, backtesting-trading-strategies, cryptocurrency, python, trade, trading, trading-bot, trading-bots, trading-strategies
Language: Python
Homepage: https://investing-algorithm-framework.com
Size: 2.71 MB
Stars: 103
Watchers: 8
Forks: 19
Open Issues: 5
Metadata Files:
- Readme: README.md
- License: LICENSE
- Authors: AUTHORS.md

Awesome Lists containing this project

awesome-quant - Investing algorithm framework - Framework for developing, backtesting, and deploying automated trading algorithms. (Python / Trading & Backtesting)

README

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###### Sponsors

# [Investing Algorithm Framework](https://github.com/coding-kitties/investing-algorithm-framework)

The Investing Algorithm Framework is a Python tool that enables swift and
elegant development of trading bots. It comes with all the necessary
components for creating algorithms, including data provisioning,
portfolio management, and order execution.

Features:
* Order execution and tracking
* Broker and exchange connections through [ccxt](https://github.com/ccxt/ccxt)
* Backtesting and performance analysis reports [example](./examples/backtest_example)
* Backtesting multiple algorithms with different backtest date ranges [example](./examples/backtests_example)
* Portfolio management and tracking
* Tracing for analyzing and debugging your trading bot
* Web API for interacting with your deployed trading bot
* Data persistence through sqlite db or an in-memory db
* Stateless running for cloud function deployments
* Polars dataframes support out of the box for fast data processing [pola.rs](https://pola.rs/)

## Example implementation
The following algorithm connects to binance and buys BTC every 5 seconds.
It also exposes an REST API that allows you to interact with the algorithm.
```python
import pathlib
from investing_algorithm_framework import create_app, PortfolioConfiguration, \
RESOURCE_DIRECTORY, TimeUnit, CCXTOHLCVMarketDataSource, Algorithm, \
CCXTTickerMarketDataSource, MarketCredential, SYMBOLS

# Define the symbols you want to trade for optimization, otherwise the
# algorithm will check if you have orders and balances on all available
# symbols on the market
symbols = ["BTC/EUR"]

# Define resource directory and the symbols you want to trade
config = {
RESOURCE_DIRECTORY: pathlib.Path(__file__).parent.resolve(),
SYMBOLS: symbols
}

# Define market data sources
# OHLCV data for candles
bitvavo_btc_eur_ohlcv_2h = CCXTOHLCVMarketDataSource(
identifier="BTC-ohlcv",
market="BITVAVO",
symbol="BTC/EUR",
timeframe="2h",
window_size=200
)
# Ticker data for orders, trades and positions
bitvavo_btc_eur_ticker = CCXTTickerMarketDataSource(
identifier="BTC-ticker",
market="BITVAVO",
symbol="BTC/EUR",
)
app = create_app(config=config)
algorithm = Algorithm()
app.add_market_credential(MarketCredential(
market="bitvavo",
api_key="",
secret_key="",
))
app.add_portfolio_configuration(
PortfolioConfiguration(
market="bitvavo",
trading_symbol="EUR",
initial_balance=400
)
)
app.add_algorithm(algorithm)

@algorithm.strategy(
# Run every two hours
time_unit=TimeUnit.HOUR,
interval=2,
# Specify market data sources that need to be passed to the strategy
market_data_sources=[bitvavo_btc_eur_ticker, bitvavo_btc_eur_ohlcv_2h]
)
def perform_strategy(algorithm: Algorithm, market_data: dict):
# By default, ohlcv data is passed as polars df in the form of
# {"": } https://pola.rs/,
# call to_pandas() to convert to pandas
polars_df = market_data["BTC-ohlcv"]
print(f"I have access to {len(polars_df)} candles of ohlcv data")

# Ticker data is passed as {"": }
ticker_data = market_data["BTC-ticker"]
unallocated_balance = algorithm.get_unallocated()
positions = algorithm.get_positions()
trades = algorithm.get_trades()
open_trades = algorithm.get_open_trades()
closed_trades = algorithm.get_closed_trades()

# Create a buy oder
algorithm.create_limit_order(
target_symbol="BTC/EUR",
order_side="buy",
amount=0.01,
price=ticker_data["ask"],
)

# Close a trade
algorithm.close_trade(trades[0].id)

# Close a position
algorithm.close_position(positions[0].get_symbol())

if __name__ == "__main__":
app.run()
```

> You can find more examples [here](./examples) folder.

## Backtesting and experiments
The framework also supports backtesting and performing backtest experiments. After
a backtest, you can print a report that shows the performance of your trading bot.

To run a single backtest you can use the example code that can be found [here](./examples/backtest).

### Backtesting report
You can use the ```pretty_print_backtest``` function to print a backtest report.
For example if you run the [moving average example trading bot](./examples/crossover_moving_average_trading_bot)
you will get the following backtesting report:

```bash

:%%%#+- .=*#%%% Backtest report
*%%%%%%%+------=*%%%%%%%- ---------------------------
*%%%%%%%%%%%%%%%%%%%%%%%- Start date: 2023-08-24 00:00:00
.%%%%%%%%%%%%%%%%%%%%%%# End date: 2023-12-02 00:00:00
#%%%####%%%%%%%%**#%%%+ Number of days: 100
.:-+*%%%%- -+..#%%%+.+- +%%%#*=-: Number of runs: 1201
.:-=*%%%%. += .%%# -+.-%%%%=-:.. Number of orders: 40
.:=+#%%%%%*###%%%%#*+#%%%%%%*+-: Initial balance: 400.0
+%%%%%%%%%%%%%%%%%%%= Final balance: 428.2434
:++ .=#%%%%%%%%%%%%%*- Total net gain: 28.2434 7.061%
:++: :+%%%%%%#-. Growth: 28.2434 7.061%
:++: .%%%%%#= Number of trades closed: 20
:++: .#%%%%%#*= Number of trades open(end of backtest): 0
:++- :%%%%%%%%%+= Percentage positive trades: 30.0%
.++- -%%%%%%%%%%%+= Percentage negative trades: 70.0%
.++- .%%%%%%%%%%%%%+= Average trade size: 100.9692 EUR
.++- *%%%%%%%%%%%%%*+: Average trade duration: 83.6 hours
.++- %%%%%%%%%%%%%%#+=
=++........:::%%%%%%%%%%%%%%*+-
.=++++++++++**#%%%%%%%%%%%%%++.

Price noise

Positions overview
╭────────────┬──────────┬──────────────────────┬───────────────────────┬──────────────┬───────────────┬───────────────────────────┬────────────────┬───────────────╮
│ Position │ Amount │ Pending buy amount │ Pending sell amount │ Cost (EUR) │ Value (EUR) │ Percentage of portfolio │ Growth (EUR) │ Growth_rate │
├────────────┼──────────┼──────────────────────┼───────────────────────┼──────────────┼───────────────┼───────────────────────────┼────────────────┼───────────────┤
│ EUR │ 428.243 │ 0 │ 0 │ 428.243 │ 428.243 │ 100.0000% │ 0 │ 0.0000% │
├────────────┼──────────┼──────────────────────┼───────────────────────┼──────────────┼───────────────┼───────────────────────────┼────────────────┼───────────────┤
│ DOT │ 0 │ 0 │ 0 │ 0 │ 0 │ 0.0000% │ 0 │ 0.0000% │
├────────────┼──────────┼──────────────────────┼───────────────────────┼──────────────┼───────────────┼───────────────────────────┼────────────────┼───────────────┤
│ BTC │ 0 │ 0 │ 0 │ 0 │ 0 │ 0.0000% │ 0 │ 0.0000% │
╰────────────┴──────────┴──────────────────────┴───────────────────────┴──────────────┴───────────────┴───────────────────────────┴────────────────┴───────────────╯
Trades overview
╭─────────┬─────────────────────┬─────────────────────┬────────────────────┬──────────────┬──────────────────┬───────────────────────┬────────────────────┬─────────────────────╮
│ Pair │ Open date │ Close date │ Duration (hours) │ Size (EUR) │ Net gain (EUR) │ Net gain percentage │ Open price (EUR) │ Close price (EUR) │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-11-24 12:00:00 │ 2023-11-27 14:00:00 │ 74 │ 107.55 │ -1.9587 │ -1.8212% │ 4.777 │ 4.69 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-11-20 00:00:00 │ 2023-11-21 08:00:00 │ 32 │ 109.39 │ -4.5949 │ -4.2005% │ 4.9875 │ 4.778 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ BTC-EUR │ 2023-11-19 22:00:00 │ 2023-11-22 00:00:00 │ 50 │ 109.309 │ -2.7624 │ -2.5272% │ 34159.1 │ 33295.9 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ BTC-EUR │ 2023-11-06 12:00:00 │ 2023-11-13 14:00:00 │ 170 │ 107.864 │ 6.1015 │ 5.6567% │ 32685.9 │ 34534.9 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-10-20 12:00:00 │ 2023-10-27 08:00:00 │ 164 │ 99.085 │ 10.9799 │ 11.0813% │ 3.5465 │ 3.9395 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ BTC-EUR │ 2023-10-14 04:00:00 │ 2023-10-27 22:00:00 │ 330 │ 97.4278 │ 24.137 │ 24.7742% │ 25638.9 │ 31990.7 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-10-14 04:00:00 │ 2023-10-17 14:00:00 │ 82 │ 99.5572 │ -1.8877 │ -1.8961% │ 3.56 │ 3.4925 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-10-07 08:00:00 │ 2023-10-08 08:00:00 │ 24 │ 99.9498 │ -1.5708 │ -1.5716% │ 3.8815 │ 3.8205 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ BTC-EUR │ 2023-09-27 10:00:00 │ 2023-10-05 20:00:00 │ 202 │ 98.2888 │ 3.433 │ 3.4927% │ 25202.2 │ 26082.5 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-09-27 10:00:00 │ 2023-10-03 20:00:00 │ 154 │ 98.7893 │ 1.2085 │ 1.2233% │ 3.842 │ 3.889 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-09-25 12:00:00 │ 2023-09-27 04:00:00 │ 40 │ 98.9193 │ -0.5194 │ -0.5251% │ 3.809 │ 3.789 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-09-14 16:00:00 │ 2023-09-18 02:00:00 │ 82 │ 98.9419 │ -0.0912 │ -0.0921% │ 3.799 │ 3.7955 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ BTC-EUR │ 2023-09-07 06:00:00 │ 2023-09-10 16:00:00 │ 82 │ 98.6093 │ 0.3412 │ 0.3460% │ 24051 │ 24134.3 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-09-07 00:00:00 │ 2023-09-09 02:00:00 │ 50 │ 98.9158 │ -0.2358 │ -0.2383% │ 3.986 │ 3.9765 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-09-05 14:00:00 │ 2023-09-06 12:00:00 │ 22 │ 99.2132 │ -1.1909 │ -1.2003% │ 3.999 │ 3.951 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-09-04 16:00:00 │ 2023-09-04 22:00:00 │ 6 │ 99.355 │ -0.5671 │ -0.5708% │ 3.942 │ 3.9195 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-09-04 10:00:00 │ 2023-09-04 14:00:00 │ 4 │ 99.4774 │ -0.4889 │ -0.4914% │ 3.968 │ 3.9485 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ BTC-EUR │ 2023-08-26 10:00:00 │ 2023-08-26 18:00:00 │ 8 │ 99.0829 │ -0.03 │ -0.0302% │ 24166.6 │ 24159.3 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-08-25 10:00:00 │ 2023-08-28 10:00:00 │ 72 │ 99.659 │ -0.6975 │ -0.6999% │ 4.1435 │ 4.1145 │
├─────────┼─────────────────────┼─────────────────────┼────────────────────┼──────────────┼──────────────────┼───────────────────────┼────────────────────┼─────────────────────┤
│ DOT-EUR │ 2023-08-24 00:00:00 │ 2023-08-25 00:00:00 │ 24 │ 99.9999 │ -1.3626 │ -1.3626% │ 4.1465 │ 4.09 │
╰─────────┴─────────────────────┴─────────────────────┴────────────────────┴──────────────┴──────────────────┴───────────────────────┴────────────────────┴─────────────────────╯
```

### Backtest experiments
The framework also supports backtest experiments. Backtest experiments allows you to
compare multiple algorithms and evaluate their performance. Ideally,
you would do this by parameterizing your strategy and creating a factory function that
creates the algorithm with the different parameters. You can find an example of this
in the [backtest experiments example](./examples/backtest_experiment).

## Broker/Exchange configuration
The framework has by default support for [ccxt](https://github.com/ccxt/ccxt).
This should allow you to connect to a lot of brokers/exchanges.

```python
from investing_algorithm_framework import PortfolioConfiguration, \
MarketCredential, create_app
app = create_app()
app.add_market_credential(
MarketCredential(
market="",
api_key="",
secret_key="",
)
)
app.add_portfolio_configuration(
PortfolioConfiguration(
market="",
initial_balance=400,
track_from="01/01/2022",
trading_symbol="EUR"
)
)
```

## Performance
We are continuously working on improving the performance of the framework. If
you have any suggestions, please let us know.

## Download
You can download the framework with pypi.

```bash
pip install investing-algorithm-framework
```

## Disclaimer
If you use this framework for your investments, do not risk money
which you are afraid to lose, until you have clear understanding how
the framework works. We can't stress this enough:

BEFORE YOU START USING MONEY WITH THE FRAMEWORK, MAKE SURE THAT YOU TESTED
YOUR COMPONENTS THOROUGHLY. USE THE SOFTWARE AT YOUR OWN RISK.
THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR INVESTMENT RESULTS.

Also, make sure that you read the source code of any plugin you use or
implementation of an algorithm made with this framework.

## Documentation

All the documentation can be found online
at the [documentation webstie](https://investing-algorithm-framework.com)

In most cases, you'll probably never have to change code on this repo directly
if you are building your algorithm/bot. But if you do, check out the
contributing page at the website.

If you'd like to chat with investing-algorithm-framework users
and developers, [join us on Slack](https://inv-algo-framework.slack.com) or [join us on reddit](https://www.reddit.com/r/InvestingBots/)

## Acknowledgements
We want to thank all contributors to this project. A full list of all
the people that contributed to the project can be
found [here](https://github.com/investing-algorithms/investing-algorithm-framework/blob/master/AUTHORS.md)

### [Bugs / Issues](https://github.com/investing-algorithms/investing-algorithm-framework/issues?q=is%3Aissue)

If you discover a bug in the framework, please [search our issue tracker](https://github.com/investing-algorithms/investing-algorithm-framework/issues?q=is%3Aissue)
first. If it hasn't been reported, please [create a new issue](https://github.com/investing-algorithms/investing-algorithm-framework/issues/new).

### Contributing
The investing algorithm framework is a community driven project.
We welcome you to participate, contribute and together help build
the future trading bots developed in python.

Feel like the framework is missing a feature? We welcome your pull requests!
If you want to contribute to the project roadmap, please take a look at the [project board](https://github.com/coding-kitties/investing-algorithm-framework/projects?query=is%3Aopen).
You can pick up a task by assigning yourself to it.

**Note** before starting any major new feature work, *please open an issue describing what you are planning to do*.
This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.

**Important:** Always create your feature or hotfix against the `develop` branch, not `master`.