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