core/strategy.py

from typing import List

import sympy.abc
from bfxapi import Position
from sympy import Point, solve

from bfxbot.models import Strategy, PositionState, SymbolStatus, Event, EventKind, EventMetadata
from bfxbot.utils import TAKER_FEE, net_pl_percentage


class SquaredTrailingStop:
    def __init__(self, p_min: Point, p_max: Point):
        a = sympy.abc.a
        b = sympy.abc.b
        c = sympy.abc.c

        self.p_min = p_min
        self.p_max = p_max

        e1 = 2 * a * (p_max.x + b)
        e2 = a * (p_min.x + b) ** 2 + c - p_min.y
        e3 = a * (p_max.x + b) ** 2 + c - p_max.y

        s = solve([e1, e2, e3])[0]

        self.a, self.b, self.c = s[a], s[b], s[c]

    def y(self, x):
        def inter_y(x):
            return self.a * (x + self.b) ** 2 + self.c

        if x < self.p_min.x:
            return self.p_min.y
        elif x > self.p_max.x:
            return self.p_max.y
        else:
            return inter_y(x)

    def profit(self, x):
        if x < self.p_min.x:
            return 0
        return x - self.y(x)


class TrailingStopMetadata(EventMetadata):
    def __init__(self, net_pl_percentage: float, **kwargs):
        super(TrailingStopMetadata, self).__init__(**kwargs)
        self.net_pl_percentage: float = net_pl_percentage


class TrailingStopStrategy(Strategy):
    BREAK_EVEN_PERC = TAKER_FEE
    MIN_PROFIT_PERC = BREAK_EVEN_PERC + 0.3
    GOOD_PROFIT_PERC = MIN_PROFIT_PERC * 2.5
    MAX_LOSS_PERC = -3.75
    OFFER_PERC = 0.005

    TRAILING_STOP = SquaredTrailingStop(Point(MIN_PROFIT_PERC, MIN_PROFIT_PERC / 3 * 2), Point(GOOD_PROFIT_PERC, 0.1))

    def position_on_new_tick(self, position: Position, ss: SymbolStatus) -> (PositionState, List[Event]):
        events = []

        pl_perc = net_pl_percentage(position.profit_loss_percentage, TAKER_FEE)
        prev = ss.previous_pw(position.id)
        event_metadata = TrailingStopMetadata(position_id=position.id, net_pl_percentage=pl_perc)

        if pl_perc > self.GOOD_PROFIT_PERC:
            state = PositionState.PROFIT
        elif self.MIN_PROFIT_PERC <= pl_perc < self.GOOD_PROFIT_PERC:
            state = PositionState.MINIMUM_PROFIT
        elif 0.0 <= pl_perc < self.MIN_PROFIT_PERC:
            state = PositionState.BREAK_EVEN
        elif self.MAX_LOSS_PERC < pl_perc < 0.0:
            state = PositionState.LOSS
        else:
            state = PositionState.CRITICAL

        if not prev or prev.state == state:
            return state, events

        if state == PositionState.PROFIT:
            events.append(Event(EventKind.REACHED_GOOD_PROFIT, ss.current_tick, event_metadata))
        elif state == PositionState.MINIMUM_PROFIT:
            events.append(Event(EventKind.REACHED_MIN_PROFIT, ss.current_tick, event_metadata))
        elif state == PositionState.BREAK_EVEN:
            events.append(Event(EventKind.REACHED_BREAK_EVEN, ss.current_tick, event_metadata))
        elif state == PositionState.LOSS:
            events.append(Event(EventKind.REACHED_LOSS, ss.current_tick, event_metadata))
        else:
            events.append(Event(EventKind.REACHED_MAX_LOSS, ss.current_tick, event_metadata))
            events.append(Event(EventKind.CLOSE_POSITION, ss.current_tick, event_metadata))

        return state, events