Elena Framework for cryptocurrencies trading bots documentation

Repository	https://github.com/Pasta-fantasia/elena-docs
Copyright	Apache License - 2022 - Fran Simó

Install ↵

Pure Python

Note:

This is a work in progress. It's a software configuration guide. This Is Not Financial Advice.

Pre requisites

The pure-python install assumes that you are working on a linux machine running Debian 12 (bookworm) or similar Raspberry Pi OS using Python 3.11

System libraries

Most Debian had already installed Python3 and its basics components, but you may want to run this apt installs as root or sudo:

apt update
apt install -y python3 build-essential git libssl-dev gcc python3.11-venv wget cron

Dedicated user

It's recommended to create a dedicated user. This guide also assumes that.

useradd elena2 --user-group --create-home --shell /bin/bash

Modules installation

Logged as the dedicated user, install the modules on a new virtual environment.

The modules are:

elena: main trading lib.
elena-basics: basic strategies ready to use.
elena-notifications-telegram: plugin to send notifications to telegram.

python3 -m venv elena2_venv
source elena2_venv/bin/activate
pip install -U pip setuptools wheel
pip install git+https://github.com/Pasta-fantasia/elena.git@v2.4.1
pip install git+https://github.com/Pasta-fantasia/elena-basics.git@v0.1.7
pip install git+https://github.com/Pasta-fantasia/elena-notifications-telegram.git@v0.0.1

Note: if you have a previous version is recommended to uninstall elena and elena-basics before upgrading.

Create a data directory

mkdir $HOME/local_data

Create basic configuration files

cd $HOME/local_data
wget https://raw.githubusercontent.com/Pasta-fantasia/elena-docs/main/docs/assets/configs_2.3.2/config.yaml
wget https://raw.githubusercontent.com/Pasta-fantasia/elena-docs/main/docs/assets/configs_2.3.2/secrets.yaml
wget https://raw.githubusercontent.com/Pasta-fantasia/elena-docs/main/docs/assets/configs_2.3.2/strategies.yaml

Test

cd
elena

You should see something like:

Configure bash environment

echo "source $HOME/elena2_venv/bin/activate" >> $HOME/.bashrc
echo "export ELENA_HOME=$HOME/local_data" >> $HOME/.bashrc
source $HOME/.bashrc

Configure cron

Download the cron shell script:

wget https://raw.githubusercontent.com/Pasta-fantasia/elena-docs/main/docs/assets/configs_2.3.2/cron.sh

Check that cron.sh is pointing to your Python virtual environment and ELENA_HOME by running bash cron.sh, you should find last.log file on $HOME with the same contents of the image above.

Add this line using crontab -e:

* * * * * BASH_ENV=~/.bashrc bash -c -l "bash cron.sh"

Wait for a minute, and you should find last.log file on $HOME with the same contents of the image above.

Congratulations!

Now you have the basic Elena installed. The next step is to configure the exchanges, telegram (optional) and your strategies.

Docker

Note:

This is a work in progress. It's a software configuration guide. This Is Not Financial Advice.

https://docs.docker.com/engine/install/debian/

https://docs.docker.com/engine/install/linux-postinstall/

Ended: Install

Config ↵

Exchanges

Note:

This is a work in progress. It's a software configuration guide. This Is Not Financial Advice.

Secretes overview

Binance

Telegram configuration

Note:

This is a work in progress. It's a software configuration guide. This Is Not Financial Advice.

To use Telegram notifications check this README.md

Ended: Config

Strategies ↵

Strategies

Note:

This is a work in progress. It's a software configuration guide. This Is Not Financial Advice.

Use cases - which strategy is best for you?

DCA_Strict:
- You're a believer in crypto and you're playing very long...
- Only buys.
- Why use Elena and not your exchange "auto invest"? At least in Binance, Elena is cheaper. You can also automate in one place several exchanges.
DCA_Conditional_Buy_LR:
- A believer that wants to avoid buying during a fall.
- Only buys.
DCA_Conditional_Buy_LR_with_TrailingStop:
- DCA + Trailing Stop Loss.
- Buys and passive sells with stop loss.
- Check TrailingStopLoss.
TrailingStopLoss: you want to protect your crypto holdings or incomes selling it in a fall ensuring a profit
- Passive sells with stop loss.
- You have crypto, you're holding, but you can trade a part to get a profit in the bull run.
- You have incomes in crypto, like a validator, miner, hotspot.
- You bought crypto on the previous bull run and you want to sell it with a profit, setting a minimal price. (pending to implement)
- You want to buy by your self, but after that you want to protect that asset from strong falls.

General parameters

Strategies:
  - id: DCA_Strict
    name: DCA_Strict
    enabled: true
    strategy_class: elena_basic.strategies.dca_strict.DCA_Strict

    bots:
      - id: DCA_BTC_USDT_1
        name: DCA Strict BTC/USDT
        enabled: false
        pair: BTC/USDT
        exchange: binance
        time_frame: 1h # Valid values: 1m, 1h, 1d, 1M, 1y
        cron_expression: "0,30 * * * *" # At 0 and 30 minutes of every hour
        budget_limit: 600.0 # Buy up to 600 UDST
        pct_reinvest_profit: 100.0 # reinvest all profits

Parameters:

strategy_class: this chooses what strategy to use.
bots.id: bot id, that's used as filename like DCA_BTC_USDT_1.json
pair: uppercase string literal of a pair of currencies (as CCXT express it)
exchange: exchange name as represented in Elena.
time_frame: default timeframe for the candles retrival from exchange as represented in Elena
cron_expression: cron expression that defines when the bot is going to be executed. The default installation in this guid makes Elena to execute every minute but a weekly DCA can uses something like "0 0 12 ? * SUN"
budget_limit: sets how much can spend. 0 means no limit. On any buy the strategies check if there is budget on the bot and balance on the exchange. You can assign 100 USDT on the bot while you keep 300 USDT on the exchange.
pct_reinvest_profit: sets, after a profitable trade, how much of that profit will become part of the budget.

DCA_Strict

On every cron execution it places a buy market order. The amount of the order is set by spend_on_order parameter and it's limited by budget.

Strategies:
  - id: DCA_Strict
    strategy_class: elena_basic.strategies.dca_strict.DCA_Strict
    bots:
      - id: DCA_BTC_USDT_1
        config:
          spend_on_order: 10.0

Parameters:

spend_on_order: how much can spend on every single order, budget and balance are checked.

DCA_Conditional_Buy_LR

As DCA_Strict but it evaluates a linear regression, if the angle is positive creates the buy order, to avoid buying during a fall. lr_buy_longitude determines how many time intervals are used to calculate the angle.

In 1d time frame, lr_buy_longitude is the number of days with price going up.

Strategies:
  - id: DCA_LR
    strategy_class: elena_basic.strategies.dca_conditional_lr.DCA_Conditional_Buy_LR
    bots:
      - id: DCA_LR_BTC_USDT_1
        config:
          spend_on_order: 100.0 
          lr_buy_longitude: 5

Parameters:

spend_on_order: how much can spend on every single order, budget and balance are checked.
lr_buy_longitude: number of timeframe point to calculate the linear regression. In a 1d time fame is the number of days.

TrailingStopLoss

A trailing stop moves up a stop order, an order that is executed when the prices fall from a "stop loss" point and has a minimal selling price at "stop price".

Stop loss limit is shown as lb_close the blue line on the graphs. Stop price as lb_low the orange line on the graphs.

It's a conservative strategy to protect the investment.

On every run the bots will:

Check if new coins has arrived they will start a new trade with an entry price as the current price.
Once a trade begins the bots will check if the entry price is higher than then current "stop price" +minimal_benefit_to_start_trailing, if so, a stop order will be sent with stop loss (lb_close) and stop price( lb_low).
For every trade already started they will check if the current calculated stop price is higher than the previous order, if so, they will cancel the old order and create a new one. The bots groups all trades in one stop order deu to some exchanges limitations.

Uses Double Exponential Moving Average (DEMA) on the Closes to calculate the stop loss. Stop price is the stop loss minus a percentage.

Why DEMA? Because it performed better on the simulations.

  - id: TrailingStopLoss
    name: TrailingStopLoss
    enabled: true
    strategy_class: elena_basic.strategies.trailing_stop.TrailingStopLoss

    bots:
      - id: BTC_USDT_1
        name: TrailingStopLoss BTC/USDT
        config:
          band_length: 7
          band_mult: 1
          band_low_pct: 3.8906
          min_price_to_start_trailing: 0.0
          minimal_benefit_to_start_trailing: 0.3 
          asset_to_manage: 100%

Parameters:

band_length: DEMA length. Number of data point in the time_frame defined at bot level.
band_mult: standard deviation multiplier over band.
band_low_pct: percentage bellow stop loss to set the stop price.
min_price_to_start_trailing: price of the asset to start trailing
minimal_benefit_to_start_trailing: % minimal benefit, expressed as 5%, but minimal could be 0.3%
asset_to_manage: expressed a % or absolute is how much asset to manage.

stop_loss = dema(ohlc.close,band_length) - ( std(ohlc.close,band_length) * band_mult )

stop_price = stop_loss - band_low_pct%

band_low_pct in the examples coms from the down variance (open - low) of the price for the optimization period.

DCA_Conditional_Buy_LR_with_TrailingStop

Buys as DCA_Conditional_Buy_LR but adds a trailing stop. The trailing is the same as TrailingStopLoss but it works only with the trades that the DCA started (only DCA buys are managed)

Experiments.

Strategies:
  - id: DCA_LR_SL...
    strategy_class: elena_basic.strategies.dca_conditional_lr_trailing_stop.DCA_Conditional_Buy_LR_with_TrailingStop

    bots:
      - id: DCA_LR_SL_BTC_USDT_1
        config:
          spend_on_order: 200.0
          daily_budget: 200.0
          # weekly_budget: 0.0
          spent_times_shift: "-5 hours"
          lr_buy_longitude: 7
          band_length: 34
          band_mult: 2
          band_low_pct: 3.8906
          min_price_to_start_trailing: 0.0
          minimal_benefit_to_start_trailing: 0.3

Parameters:

spend_on_order: how much can spend on every single order, budget and balance are checked.
daily_budget: how much to spend by day. spend_on_order = to 10, with a cron by hour will by 24 times and spend 240... unless daily_budget is set to, for example, 100 then it will buy only 100 per day. Spend by day is calculated based on the buy orders.
weekly_budget: same as daily_budget but for week.
spent_times_shift: -timedelta to shit the week or daily spend. Useful to start the day at 5am with "-5 hours".
lr_buy_longitude: number of timeframe point to calculate the linear regression. In a 1d time fame is the number of days.
band_length: DEMA length. Number of data point in the time_frame defined at bot level.
band_mult: standard deviation multiplier over band.
band_low_pct: percentage bellow stop loss to set the stop price.
min_price_to_start_trailing: price of the asset to start trailing
minimal_benefit_to_start_trailing: % minimal benefit, expressed as 5%, but minimal could be 0.3%
asset_to_manage: expressed a % or absolute is how much asset to manage.

Configuration by example

Note:

This is a work in progress. It's a software configuration guide. This Is Not Financial Advice.

This page guides you to an example of parametrization using DCA_Conditional_Buy_LR_with_TrailingStop and TrailingStopLoss.

Lets supuse you have 1000 USDT and some old BTC and some HNT from your hotspot.

You believe in two possible scenarios for the next year: Up and Down or Range.

TrailingStopLoss to protect or trade some already hodl crypto, BTC and HNT.
DCA_Conditional_Buy_LR_with_TrailingStop to invest the 1000 USDT.

All config bellow are in strategies_example.yaml

TrailingStopLoss for BTC and HNT

For long term BTC configuration for the trailing is 1d timeframe and:

band_length=34
band_mult=2

For HNT the same configuration can be used. You can see in the graph that the sell is not triggered.

The bots will run every hour to check the status.

In both cases all the balance in the exchange will be managed by the strategy. Every time new coins arrive the bots will take them as "under protection".

If you want to combine this strategy with another trading one in the same exchange you must use absolute number on asset_to_manage. The example will use Kucoin for TrailingStopLoss and Binance for DCA_Conditional_Buy_LR_with_TrailingStop.

The configuration file for this looks like:

Strategies:
  - id: TrailingStopLoss
    name: TrailingStopLoss
    enabled: true
    strategy_class: elena_basic.strategies.trailing_stop.TrailingStopLoss

    bots:
       - id: BTC_USDT_1
        name: TrailingStopLoss BTC/USDT
        enabled: true
        pair: BTC/USDT
        exchange: kucoin
        time_frame: 1d # Valid values: 1m, 1h, 1d, 1M, 1y
        cron_expression: "0 * * * *" # At every minute
        budget_limit: 0.0 # don't control budget
        pct_reinvest_profit: 100.0 # reinvest all profits
        tags:
          - TrailingStopLoss
          - bear
        config: # https://elena.fransimo.info/03_strategies/DCA_Conditional_Buy_LR_with_TrailingStop/LongTerm/Binance_BTC-USDT_1d_2017-01-01_2017-01-01_2024-01-20_1526/
          band_length: 34
          band_mult: 2
          minimal_benefit_to_start_trailing: 0.3 # % minimal benefit, expressed as 5%, but minimal could be 0.3%
          asset_to_manage: 100%

      - id: HNT_USDT_1
        name: TrailingStopLoss HNT/USDT
        enabled: true
        pair: HNT/USDT
        exchange: kucoin
        time_frame: 1d # Valid values: 1m, 1h, 1d, 1M, 1y
        cron_expression: "0 * * * *" # At every minute
        budget_limit: 0.0 # don't control budget
        pct_reinvest_profit: 100.0 # reinvest all profits
        tags:
          - TrailingStopLoss
          - bear
        config: # https://elena.fransimo.info/03_strategies/DCA_Conditional_Buy_LR_with_TrailingStop/HNT/KuCoin_HNT-USDT_1d_2023-06-16_2023-06-16_2024-01-21_1731/
          band_length: 34
          band_mult: 2
          minimal_benefit_to_start_trailing: 0.3 # % minimal benefit, expressed as 5%, but minimal could be 0.3%
          asset_to_manage: 100%

DCA_Conditional_Buy_LR_with_TrailingStop to invest the 1000 USDT

With the 1000 USDT on Binance, 500 will trade with BTC and 500 on ETH.

All configration will spend 100 USDT each time.

For BTC:

lr_buy_longitude: 7
band_length: 34
band_mult: 2

From the experiment.

You split the 500 on ETH in two parametrization:

Range (from the experiment)
- lr_buy_longitude: 6
- band_length: 11
- band_mult: 1
Up_and_down (from the experiment)
- lr_buy_longitude: 2
- band_length: 55
- band_mult: 2

Optimization are only a guide and are based on history. The ETH Range optimization is band_length: 11, band_mult: 1, but it also says dca_budget=1600, buy_all_days=0. That means use all your budget once a week. The example bellow uses only 100 USDT per day.

Before using any bot with any configuration is better your check at least the simulation by your self, and then, if the parameters are compatible run it in the exchange test environment.

Strategies:
  - id: DCA_LR_SL
    name: DCA_LR_SL
    enabled: true
    strategy_class: elena_basic.strategies.dca_conditional_lr_trailing_stop.DCA_Conditional_Buy_LR_with_TrailingStop

    bots:
      - id: DCA_LR_SL_BTC_USDT_1
        name: DCA Conditional LR with Trailing Stop Loss BTC/USDT
        enabled: false
        pair: BTC/USDT
        exchange: binance
        time_frame: 1d # Valid values: 1m, 1h, 1d, 1M, 1y
        cron_expression: "0 5 * * *" # At 5am each day
        budget_limit: 500.0 # Buy up to 500 UDST
        pct_reinvest_profit: 100.0 # reinvest all profits
        tags:
          - DCA
          - bull
        config: # https://elena.fransimo.info/03_strategies/DCA_Conditional_Buy_LR_with_TrailingStop/Up_and_down/Binance_BTC-USDT_1d_2019-11-01_2019-11-01_2024-01-20_1523/
          spend_on_order: 100.0 # spend 100 USDT on every cycle
          lr_buy_longitude: 7 # data points for linear regression
          band_length: 34
          band_mult: 2
          minimal_benefit_to_start_trailing: 0.3 # % minimal benefit, expressed as 5%, but minimal could be 0.3%

      - id: DCA_LR_SL_ETH_USDT_1
        name: DCA Conditional LR with Trailing Stop Loss BTC/USDT
        enabled: false
        pair: ETH/USDT
        exchange: binance
        time_frame: 1d # Valid values: 1m, 1h, 1d, 1M, 1y
        cron_expression: "0 5 * * *" # At 5am each day
        budget_limit: 250.0 # Buy up to 250 UDST
        pct_reinvest_profit: 100.0 # reinvest all profits
        tags:
          - DCA
          - ranging
        config: # https://elena.fransimo.info/03_strategies/DCA_Conditional_Buy_LR_with_TrailingStop/Range/Binance_ETH-USDT_1d_2022-06-16_2022-06-16_2024-01-20_1612/
          spend_on_order: 100.0 # spend 100 USDT on every cycle
          lr_buy_longitude: 6 # data points for linear regression
          band_length: 11
          band_mult: 1
          minimal_benefit_to_start_trailing: 0.3 # % minimal benefit, expressed as 5%, but minimal could be 0.3%

      - id: DCA_LR_SL_ETH_USDT_2
        name: DCA Conditional LR with Trailing Stop Loss BTC/USDT 2
        enabled: false
        pair: ETH/USDT
        exchange: binance
        time_frame: 1d # Valid values: 1m, 1h, 1d, 1M, 1y
        cron_expression: "0 5 * * *" # At 5am each day
        budget_limit: 250.0 # Buy up to 250 UDST
        pct_reinvest_profit: 100.0 # reinvest all profits
        tags:
          - DCA
          - bull
        config: # https://elena.fransimo.info/03_strategies/DCA_Conditional_Buy_LR_with_TrailingStop/Up_and_down/Binance_ETH-USDT_1d_2019-11-01_2019-11-01_2024-01-20_1609/
          spend_on_order: 100.0 # spend 100 USDT on every cycle
          lr_buy_longitude: 2 # data points for linear regression
          band_length: 55
          band_mult: 2
          minimal_benefit_to_start_trailing: 0.3 # % minimal benefit, expressed as 5%, but minimal could be 0.3%

General conservative configuration

The only real way to configure your strategies is to try the parameters your self using the experiments' repo notebooks.

The results here always come with a heat map, an ordered by return set of results that show all posible combination of parameters.

As mentioned above, optimization are only a guide based on history.

All that said, over a lot of simulations one repeats very ofter:

        time_frame: 1d # Valid values: 1m, 1h, 1d, 1M, 1y
        cron_expression: "0 5 * * *" # At 5am each day
        config: 
          spend_on_order: 100.0 # spend 50 on bear, 100 on range, more only if you're absolute sure.
          lr_buy_longitude: 7 # or 6
          band_length: 34 # for long term and trusted assets
          band_mult: 2
          # band_length: 13 # for short term or risk reduction
          # band_mult: 1

Experiments ↵

DCA_Conditional_Buy_LR_with_TrailingStop

Note:

This is a work in progress. It's a software configuration guide. This Is Not Financial Advice.

Experiment's source code can be found here.

Scenarios and best results for BTC

DCA_Conditional_Buy_LR_with_TrailingStop works better on 1 day timeframe in any scenario. It took thousands of test sampling ranging dates to discard minute and hourly trading for this strategy.

Sampling moving and overlapping dates helped to reduce the parameters space.

Range

From: 2022-06-16 to 2023-03-10.

Optimized parameters

band_length=3
band_mult=1
band_low_pct=2.065553230602729
minimal_benefit_to_start_trailing=1.003
reinvest=2
dca_budget=1000
buy_all_days=0
lr_buy_longitude=6

Results

Return: 36.37531513528706% over -1.2284505259711431% on buy and hold.
Initial investment: 1000.0
Final result: 1363.7531513528706

Up and Down

From 2019-11-01 to 2022-01-23.

Optimized parameters

band_length=34
band_mult=2
band_low_pct=3.0025190627892058
minimal_benefit_to_start_trailing=1.003
reinvest=2
dca_budget=100
buy_all_days=1
lr_buy_longitude=10

Results

Return: 965.4840942441458% over 292.6135311175407% on buy and hold.
Initial investment: 1000.0
Final result: 10654.840942441459

Bear

From 2021-11-12 to 2022-11-12.

Optimized parameters

band_length=3
band_mult=1
band_low_pct=2.8111930348691905
minimal_benefit_to_start_trailing=1.003
reinvest=2
dca_budget=50
buy_all_days=0
lr_buy_longitude=11

Results

Return: -9.49249976588443% over -73.78119881357838% on buy and hold.
Initial investment: 1000.0
Final result: 905.0750023411557

Long Term

From 2017-01-01 to 2024-01-20.

Optimized parameters

band_length=34
band_mult=2
band_low_pct=2.815263919591264
minimal_benefit_to_start_trailing=1.003
reinvest=2
dca_budget=100
buy_all_days=1
lr_buy_longitude=7

Results

Return: 1487.0788390592738% over 904.5432166669% on buy and hold.
Initial investment: 1000.0
Final result: 15870.788390592737

BTC

ETH

Bear

Binance_ETH-USDT_1d_2021-11-12_2021-11-12_2024-01-20_1611

Range

Binance_ETH-USDT_1d_2022-06-16_2022-06-16_2024-01-20_1612

Up_and_down

Binance_ETH-USDT_1d_2019-11-01_2019-11-01_2024-01-20_1609

Long Term

Binance_ETH-USDT_1d_2017-01-01_2017-01-01_2024-01-20_1610

Ended: Experiments

Ended: Strategies

Roadmap

High level roadmap

Task Details

Task details can be found in the Github project

Resources

Backtesting.py

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About ↵

Team

Note:

This is a work in progress

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Elena Framework for cryptocurrencies trading bots documentation

Install ↵

Pure Python

Pre requisites

System libraries

Dedicated user

Modules installation

Create a data directory

Create basic configuration files

Test

Configure bash environment

Configure cron

Congratulations!

Docker

Ended: Install

Config ↵

Exchanges

Secretes overview

Binance

Telegram configuration

Ended: Config

Strategies ↵

Strategies

Use cases - which strategy is best for you?

General parameters

DCA_Strict

DCA_Conditional_Buy_LR

TrailingStopLoss

DCA_Conditional_Buy_LR_with_TrailingStop

Configuration by example

TrailingStopLoss for BTC and HNT

DCA_Conditional_Buy_LR_with_TrailingStop to invest the 1000 USDT

General conservative configuration

Experiments ↵

DCA_Conditional_Buy_LR_with_TrailingStop

Scenarios and best results for BTC

Range

Optimized parameters

Results

Up and Down

Optimized parameters

Results

Bear

Optimized parameters

Results

Long Term

Optimized parameters

Results

BTC

Bear

Range

Up and down

Long Term

ETH

Bear

Range

Up_and_down

Long Term

Ended: Experiments

Ended: Strategies

Roadmap

High level roadmap

Task Details

Resources

Donate

About ↵

Team

Ended: About