freqtrade_origin/docs/advanced-orderflow.md

Advanced Orderflow

This page explains some advanced tasks and configuration options that can be performed to use orderflow data by downloading public trade data.

Quickstart

enable using public trades in config.json

"exchange": {
   ...
   "use_public_trades": true,
}

set orderflow processing configuration in config.json:

"orderflow": {
    "scale": 0.5, 
    "stacked_imbalance_range": 3, # needs at least this amount of imblance next to each other
    "imbalance_volume": 1, # filters out below
    "imbalance_ratio": 300 # filters out ratio lower than
  },

Downloading data for backtesting

• use --dl-trades to fetch trades for timerange

For example

freqtrade download-data -p BTC/USDT:USDT --timerange 20230101-  --trading-mode futures  --timeframes 5m --dl-trades

Accessing orderflow data

Several new columns are available when activated.

    dataframe['trades']
    dataframe['orderflow']
    dataframe['bid']
    dataframe['ask']
    dataframe['delta']
    dataframe['min_delta']
    dataframe['max_delta']
    dataframe['total_trades']
    dataframe['stacked_imbalances_bid']
    dataframe['stacked_imbalances_ask']

These can be accessed like this:

def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
    # calculating cumulative delta
    dataframe['cum_delta'] = cumulative_delta(dataframe['delta'])

def cumulative_delta(delta: Series):
    cumdelta = delta.cumsum()
    return cumdelta