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Run a Trader Bot

This README takes shows how to earn $ by running a trader bot on mainnet, and beyond.

  1. Install
  2. Simulate modeling & trading
  3. Run bot on testnet
  4. Run bot on mainnet

Then, you can go beyond: optimize trading strategy, and more.

Install pdr-backend Repo

Prerequisites:

  • Python 3.12. Earlier will fail, e.g. can't find UTC. Details
  • Ubuntu MacOS. Not Windows.

In a new console:

# clone the repo and enter into it
git clone https://github.com/oceanprotocol/pdr-backend
cd pdr-backend

# create & activate virtualenv
python -m venv venv
source venv/bin/activate

# install modules in the environment
pip install -r requirements.txt

# add pwd to bash path
export PATH=$PATH:.

You need a local copy of Ocean contract addresses address.json. In console:

# make directory if needed
mkdir -p ~/.ocean; mkdir -p ~/.ocean/ocean-contracts; mkdir -p ~/.ocean/ocean-contracts/artifacts/

# copy from github to local directory. Or, use wget if Linux. Or, download via browser.
curl https://github.com/oceanprotocol/contracts/blob/main/addresses/address.json -o ~/.ocean/ocean-contracts/artifacts/address.json

If you're running MacOS, then in console:

# so that sapphire.py works. Details in #66
codesign --force --deep --sign - venv/sapphirepy_bin/sapphirewrapper-arm64.dylib

# so that xgboost works. Details in #1339
brew install libomp

Simulate Modeling and Trading

Simulation allows us to quickly build intuition, and assess the performance of the data / predicting / trading strategy (backtest).

Copy ppss.yaml into your own file my_ppss.yaml and change parameters as you see fit.

cp ppss.yaml my_ppss.yaml

Let's run the simulation engine. In console:

pdr sim my_ppss.yaml

What the engine does does:

  1. Set simulation parameters.
  2. Grab historical price data from exchanges and stores in lake_data/ dir. It re-uses any previously saved data.
  3. Run through many 5 min epochs. At each epoch:
    • Build a model or get predictions from chain
    • Predict
    • Trade
    • Log to console and logs/out_<time>.txt
    • For plots, output state to sim_state/

Let's visualize results. Open a separate console, and:

cd ~/code/pdr-backend # or wherever your pdr-backend dir is
source venv/bin/activate
export PATH=$PATH:.

#start the plots server
pdr sim_plots

The plots server will give a url, such as http://127.0.0.1:8050. Open that url in your browser to see plots update in real time.

"Predict" actions are two-sided: it does one "up" prediction tx, and one "down" tx, with more stake to the higher-confidence direction. Two-sided is more profitable than one-sided prediction.

By default, simulation uses a linear model inputting prices of the previous 2-10 epochs as inputs (autoregressive_n), just BTC close price as input, a simulated 0% trading fee, and a trading strategy of "buy if predict up; sell 5min later". You can play with different values in my_ppss.yaml.

Profit isn't guaranteed: fees, slippage and more eats into them. Model accuracy makes a big difference too.

To see simulation CLI options: pdr sim -h.

Simulation uses Python logging framework. Configure it via logging.yaml. Here's a tutorial on yaml settings.

By default, Dash plots the latest sim (even if it is still running). To enable plotting for a specific run, e.g. if you used multisim or manually triggered different simulations, the sim engine assigns unique ids to each run. Select that unique id from the sim_state folder, and run pdr sim_plots --run_id <unique_id> e.g. pdr sim_plots --run_id 97f9633c-a78c-4865-9cc6-b5152c9500a3

You can run many instances of Dash at once, with different URLs. To run on different ports, use the --port argument.

Run Trader Bot on Sapphire Testnet

Predictoor contracts run on Oasis Sapphire testnet and mainnet. Sapphire is a privacy-preserving EVM-compatible L1 chain.

Let's get our bot running on testnet first.

First, tokens! You need (fake) ROSE to pay for gas, and (fake) OCEAN to stake and earn. Get them here.

Then, copy & paste your private key as an envvar. In console:

export PRIVATE_KEY=<YOUR_PRIVATE_KEY>

Then, run a simple trading bot. In console:

pdr trader 2 my_ppss.yaml sapphire-testnet

Your bot is running, congrats! Sit back and watch it in action.

It logs to console, and to logs/out_<time>.txt. Like simulation, it uses Python logging framework, configurable in logging.yaml.

To see trader CLI options: pdr trader -h

You can track behavior at finer resolution by writing more logs to the code, or querying Predictoor subgraph.

Run Trader Bot on Sapphire Mainnet

Time to make it real: let's get our bot running on Sapphire mainnet.

First, real tokens! Get ROSE via this guide and OCEAN via this guide.

Then, copy & paste your private key as an envvar. (You can skip this if it's same as testnet.) In console:

export PRIVATE_KEY=<YOUR_PRIVATE_KEY>

Update my_ppss.yaml as desired.

Then, run the bot. In console:

pdr trader 2 my_ppss.yaml sapphire-mainnet

This is where there's real $ at stake. Good luck!

Track performance, as in testnet.

Go Beyond

You've gone through all the essential steps to earn $ by running a trader bot on mainnet.

The next sections describe how to go beyond, by optimizing the trading strategy and more.

Optimize Trading Strategy

Once you're familiar with the above, you can set your own trading strategy and optimize it for $. Here's how:

  1. Fork pdr-backend repo.
  2. Change trader bot code as you wish, while iterating with simulation.
  3. Bring your trader bot to testnet then mainnet.

Source of predictions

Choose the source of the predictions used as signals for trading:

  • Use the builtin model. use_own_model=True
  • Get the predictions from live feeds. use_own_model=False

By default use_own_model is set to True, and can be changed inside my_ppss.yaml file.

Run Bots Remotely

To scale up compute or run without tying up your local machine, you can run bots remotely. Get started here.

Run Local Network

To get extra-fast block iterations, you can run a local test network (with local bots). It does take a bit more up-front setup. Get started here.

Warning

You will lose money trading if your $ out exceeds your $ in. Do account for trading fees, order book slippage, cost of prediction feeds, and more. Everything you do is your responsibility, at your discretion. None of this repo is financial advice.