piker/examples/max_pain.py

#!/usr/bin/env python
from decimal import (
    Decimal,
)
import numpy as np
import polars as pl
import trio
import tractor
from datetime import datetime
from pprint import pformat
from piker.brokers.deribit.api import (
    get_client,
    maybe_open_oi_feed,
)
from piker.storage import open_storage_client, StorageClient
import sys
import pyqtgraph as pg
from PyQt6 import QtCore
from pyqtgraph import ScatterPlotItem, InfiniteLine
from PyQt6.QtWidgets import QApplication

def check_if_complete(
        oi: dict[str, dict[str, Decimal | None]]
    ) -> bool:
    return all(
        oi[strike]['C'] is not None
        and
        oi[strike]['P'] is not None for strike in oi
    )


async def max_pain_daemon(
) -> None:
    oi_by_strikes: dict[str, dict[str, Decimal | None]]
    instruments: list[Symbol] = []
    expiry_dates: list[str]
    expiry_date: str
    currency: str = 'btc'
    kind: str = 'option'

    async with get_client(
    ) as client:
        expiry_dates: list[str] = await client.get_expiration_dates(
            currency=currency,
            kind=kind
        )

        print(f'Available expiration dates for {currency}-{kind}:')
        print(f'{expiry_dates}')
        expiry_date = input('Please enter a valid expiration date: ').upper()
        print('Starting little daemon...')

        oi_by_strikes: dict[str, dict[str, Decimal]]
        instruments = await client.get_instruments(
            expiry_date=expiry_date,
        )
        oi_by_strikes = client.get_strikes_dict(instruments)


    def get_total_intrinsic_values(
        oi_by_strikes: dict[str, dict[str, Decimal]]
    ) -> dict[str, dict[str, Decimal]]:
        call_cash: Decimal = Decimal(0)
        put_cash: Decimal = Decimal(0)
        intrinsic_values: dict[str, dict[str, Decimal]] = {}
        closes: list = sorted(Decimal(close) for close in oi_by_strikes)

        for strike, oi in oi_by_strikes.items():
            s = Decimal(strike)
            call_cash = sum(max(0, (s - c) * oi_by_strikes[str(c)]['C']) for c in closes)
            put_cash = sum(max(0, (c - s) * oi_by_strikes[str(c)]['P']) for c in closes)

            intrinsic_values[strike] = {
                'C': call_cash,
                'P': put_cash,
                'total': call_cash + put_cash,
            }

        return intrinsic_values

    def get_intrinsic_value_and_max_pain(
        intrinsic_values: dict[str, dict[str, Decimal]]
        ):
        # We meed to find the lowest value, so we start at
        # infinity to ensure that, and the max_pain must be
        # an amount greater than zero.
        total_intrinsic_value: Decimal = Decimal('Infinity')
        max_pain: Decimal = Decimal(0)

        for strike, oi in oi_by_strikes.items():
            s = Decimal(strike)
            if intrinsic_values[strike]['total'] < total_intrinsic_value:
                total_intrinsic_value = intrinsic_values[strike]['total']
                max_pain = s

        return total_intrinsic_value, max_pain

    def plot_graph(
        oi_by_strikes: dict[str, dict[str, Decimal]],
        plot,
    ):
        """Update the bar graph with new open interest data."""
        plot.clear()

        intrinsic_values = get_total_intrinsic_values(oi_by_strikes)

        for strike_str in sorted(oi_by_strikes, key=lambda x: int(x)):
            strike = int(strike_str)
            calls_val = float(oi_by_strikes[strike_str]['C'])
            puts_val  = float(oi_by_strikes[strike_str]['P'])

            bar_c = pg.BarGraphItem(
                x=[strike - 100],
                height=[calls_val],
                width=200,
                pen='w',
                brush=(0, 0, 255, 150)
            )
            plot.addItem(bar_c)

            bar_p = pg.BarGraphItem(
                x=[strike + 100],
                height=[puts_val],
                width=200,
                pen='w',
                brush=(255, 0, 0, 150)
            )
            plot.addItem(bar_p)

            total_val = float(intrinsic_values[strike_str]['total']) / 100000

            scatter_iv = ScatterPlotItem(
                x=[strike],
                y=[total_val],
                pen=pg.mkPen(color=(0, 255, 0), width=2),
                brush=pg.mkBrush(0, 255, 0, 150),
                size=3,
                symbol='o'
            )
            plot.addItem(scatter_iv)

        _, max_pain = get_intrinsic_value_and_max_pain(intrinsic_values)

        vertical_line = InfiniteLine(
            pos=max_pain,
            angle=90,
            pen=pg.mkPen(color='yellow', width=1, style=QtCore.Qt.PenStyle.DotLine),
            label=f'Max pain: {max_pain:,.0f}',
            labelOpts={
                'position': 0.85,
                'color': 'yellow',
                'movable': True
            }
        )
        plot.addItem(vertical_line)

    def update_oi_by_strikes(msg: tuple):
        nonlocal oi_by_strikes
        if 'oi' == msg[0]:
            strike_price = msg[1]['strike_price']
            option_type = msg[1]['option_type']
            open_interest = msg[1]['open_interest']
            oi_by_strikes.setdefault(
                strike_price, {}
            ).update(
                {option_type: open_interest}
            )

    # Define the structured dtype
    dtype = np.dtype([
        ('time', int),
        ('oi', float),
        ('oi_calc', float),
    ])
    async def write_open_interest_on_file(msg: tuple, client: StorageClient):
        if 'oi' == msg[0]:
            nonlocal expiry_date
            timestamp = msg[1]['timestamp']
            strike_price = msg[1]["strike_price"]
            option_type = msg[1]['option_type'].lower()
            col_sym_key = f'btc-{expiry_date.lower()}-{strike_price}-{option_type}'

            # Create the numpy array with sample data
            data = np.array([
                (
                    int(timestamp),
                    float(msg[1]['open_interest']),
                    np.nan,
                ),
            ], dtype=dtype)

            path = await client.write_oi(
                col_sym_key,
                data,
            )

    def get_max_pain(
        oi_by_strikes: dict[str, dict[str, Decimal]]
    ) -> dict[str, str | Decimal]:
        '''
        This method requires only the strike_prices and oi for call
        and puts, the closes list are the same as the strike_prices
        the idea is to sum all the calls and puts cash for each strike
        and the ITM strikes from that strike, the lowest value is what we
        are looking for the intrinsic value.

        '''

        nonlocal timestamp

        intrinsic_values = get_total_intrinsic_values(oi_by_strikes)

        total_intrinsic_value, max_pain = get_intrinsic_value_and_max_pain(intrinsic_values)

        return {
            'timestamp': timestamp,
            'expiry_date': expiry_date,
            'total_intrinsic_value': total_intrinsic_value,
            'max_pain': max_pain,
        }

    async with (
        open_storage_client() as (_, storage),

        maybe_open_oi_feed(
            instruments,
        ) as oi_feed,
    ):
        # Initialize QApplication
        app = QApplication(sys.argv)

        win = pg.GraphicsLayoutWidget(show=True)
        win.setWindowTitle('Calls (blue) vs Puts (red)')

        plot = win.addPlot(title='OI by Strikes')
        plot.showGrid(x=True, y=True)
        print('Plot initialized...')

        async for msg in oi_feed:

            # In memory oi_by_strikes dict, all message are filtered here
            # and the dict is updated with the open interest data
            update_oi_by_strikes(msg)

            # Write on file using storage client
            await write_open_interest_on_file(msg, storage)

            # Max pain calcs, before start we must gather all the open interest for
            # all the strike prices and option types available for a expiration date
            if check_if_complete(oi_by_strikes):
                if 'oi' == msg[0]:
                    # Here we must read for the filesystem all the latest open interest value for
                    # each instrument for that specific expiration date, that means look up for the
                    # last update got the instrument btc-{expity_date}-*oi1s.parquet (1s because is
                    # hardcoded to something, sorry.)
                    timestamp = msg[1]['timestamp']
                    max_pain = get_max_pain(oi_by_strikes)
                    intrinsic_values = get_total_intrinsic_values(oi_by_strikes)

                    # graph here
                    plot_graph(oi_by_strikes, plot)

                    print('-----------------------------------------------')
                    print(f'timestamp:             {datetime.fromtimestamp(max_pain['timestamp'])}')
                    print(f'expiry_date:           {max_pain['expiry_date']}')
                    print(f'max_pain:              {max_pain['max_pain']:,.0f}')
                    print(f'total intrinsic value: {max_pain['total_intrinsic_value']:,.0f}')
                    print('-----------------------------------------------')

            # Process GUI events to keep the window responsive
            app.processEvents()


async def main():

    async with tractor.open_nursery() as n:

        p: tractor.Portal = await n.start_actor(
            'max_pain_daemon',
            enable_modules=[__name__],
            infect_asyncio=True,
        )
        await p.run(max_pain_daemon)

if __name__ == '__main__':
    trio.run(main)