Window ask and window bid

To find the windowed ask and bid prices for every order tick, where the window is defined as window_before seconds before an order and window_after seconds after an order, you can use the join_with_query method in onetick.py. This method allows you to join two data sources based on a time window.

Here’s a full code example that implements the function get_window_ask_bid to achieve this:

import onetick.py as otp

# Define your symbols, orders, and quotes database
symbol = 'TSLA'
orders_db = 'ORDERS_DB'
quotes_db = 'NYSE_TAQ'
date = otp.dt(2022, 3, 2)

# Define the time window parameters
window_before = 5.0  # seconds before the order
window_after = 7.0   # seconds after the order

# Load orders and quotes data
orders = otp.DataSource(orders_db, tick_type='ORDER', symbol=symbol)
quotes = otp.DataSource(quotes_db, tick_type='QTE', symbol=symbol)

def get_window_ask_bid(orders: otp.Source, quotes: otp.Source, window_before: float, window_after: float) -> otp.Source:
    # Aggregate ask and bid prices over the window
    quotes = quotes.agg({'WINDOW_ASK': otp.agg.max('ASK_PRICE'),
                         'WINDOW_BID': otp.agg.min('BID_PRICE')})

    # Define the start and end of the window
    window_start = orders['Time'] - otp.Nano(int(window_before * 1e9))
    window_end = orders['Time'] + otp.Nano(int(window_after * 1e9))

    # Join orders with the aggregated quotes based on the time window
    return orders.join_with_query(quotes,
                                  start=window_start,
                                  end=window_end)

# Apply the function to get windowed ask and bid prices
windowed_ask_bid = get_window_ask_bid(orders, quotes, window_before, window_after)

# Run the query for the specified date
df = otp.run(windowed_ask_bid, date=date)