-

strategy/turtle_system_1.py

@@ -0,0 +1,234 @@
+import math
+from enum import Enum, auto
+from typing import List, override
+
+import numpy as np
+
+from internal_types.types import OHLC, BidAsk, Instrument, Position, Quote
+from strategy.strategy import Strategy
+from utils.utils import SEC_1_DAY, BlendedOHLC, Portfolio, crossover, crossunder, max_abs
+
+
+class State(Enum):
+  WARMUP = auto()
+  INIT = auto()
+  LONG = auto()
+  SHORT = auto()
+  SHADOW_LONG = auto()
+  SHADOW_SHORT = auto()
+
+
+class TurtleSystem1(Strategy):
+
+  def __init__(self, init_balance: float, instr: Instrument):
+    self.state = State.WARMUP
+    self.init_balance = init_balance
+    self.N: float = 0
+    self.tradable_acct_balance = init_balance
+    self.unit_size: int = 0
+    self.instr = instr
+    self.unit_limit = 4
+    self.trade_next_20_day_breakout = True
+    self.daily_ohlc = BlendedOHLC(instr, SEC_1_DAY)
+    self.shadow_portfolio = Portfolio()
+    self.portfolio = Portfolio()
+    self.desired_portfolio = Portfolio()
+
+  def warmup(self, warmup_historical_data: List[OHLC]):
+    for ohlc in warmup_historical_data:
+      self.daily_ohlc.append(ohlc)
+
+    if len(self.daily_ohlc) < 20:
+      raise ValueError('need as least 20 days of OHLC to warmup')
+
+    self.__init_day_20_N()
+    self.__adjust_unit_size()
+    self.state = State.INIT
+
+  def __true_range(self, day_i) -> float:
+    # todo: check index out of bound
+    curr_q = self.daily_ohlc.blended_ohlc(day_i)
+    if (day_i + len(self.daily_ohlc)) % len(self.daily_ohlc) == 0:
+      return curr_q.high - curr_q.low
+    prev_q = self.daily_ohlc.blended_ohlc(day_i - 1)
+    return max_abs(curr_q.high - curr_q.low, curr_q.high - prev_q.close, prev_q.close - curr_q.low)
+
+  def __init_day_20_N(self):
+    days = min(len(self.daily_ohlc), 20)
+    self.N = float(np.mean([self.__true_range(day_i) for day_i in range(-days, 0)]))
+
+  def __adjust_unit_size(self):
+    if self.N == 0:
+      raise RuntimeError('N can\'t be 0')
+    elif self.instr.multiplier == 0:
+      raise RuntimeError('multiplier can\'t be 0')
+
+    self.unit_size = \
+      math.floor(self.tradable_acct_balance * 0.01 / (self.N * self.instr.multiplier))
+
+  def __reach_unit_limit(self):
+    outstanding_shares = self.desired_portfolio.outstanding_shares(self.instr)
+    return abs(outstanding_shares) >= self.unit_limit * self.unit_size
+
+  def __shadow_reach_unit_limit(self):
+    shadow_outstanding_shares = self.shadow_portfolio.outstanding_shares(self.instr)
+    return abs(shadow_outstanding_shares) >= self.unit_limit * self.unit_size
+
+  def __submit_order(self, quantity: int, price: float):
+    self.desired_portfolio.add_position(Position(self.instr, quantity, price))
+
+  def __shadow_submit_order(self, quantity: int, price: float):
+    self.shadow_portfolio.add_position(Position(self.instr, quantity, price))
+
+  def __last_order_price(self) -> float:
+    return self.desired_portfolio.pos_history[self.instr][-1].price
+
+  def __shadow_last_order_price(self) -> float:
+    return self.shadow_portfolio.pos_history[self.instr][-1].price
+
+  def __to_INIT_state(self, price: float):
+    self.desired_portfolio.liquidate_positions(self.instr, price)
+    self.shadow_portfolio = Portfolio()
+    self.state = State.INIT
+
+  def __to_LONG_state(self, price: float):
+    self.__submit_order(self.unit_size, price)
+    self.shadow_portfolio = Portfolio()
+    self.state = State.LONG
+
+  def __to_SHORT_state(self, price: float):
+    self.__submit_order(-self.unit_size, price)
+    self.shadow_portfolio = Portfolio()
+    self.state = State.SHORT
+
+  def __to_SHADOW_LONG_state(self, price: float):
+    self.shadow_portfolio = Portfolio()
+    self.__shadow_submit_order(self.unit_size, price)
+    self.state = State.SHADOW_LONG
+
+  def __to_SHADOW_SHORT_state(self, price: float):
+    self.shadow_portfolio = Portfolio()
+    self.__shadow_submit_order(self.unit_size, price)
+    self.state = State.SHADOW_SHORT
+
+  def __process_INIT_state(self, quote: Quote):
+    breakthrough_20_high = self.daily_ohlc.crossover_x_period_max(20, quote)
+    breakthrough_20_low = self.daily_ohlc.crossunder_x_period_min(20, quote)
+    breakthrough_55_high = self.daily_ohlc.crossover_x_period_max(55, quote)
+    breakthrough_55_low = self.daily_ohlc.crossunder_x_period_min(55, quote)
+
+    if self.trade_next_20_day_breakout and breakthrough_20_high:
+      self.__to_LONG_state(self.daily_ohlc.rolling_max(20))
+    elif self.trade_next_20_day_breakout and breakthrough_20_low:
+      self.__to_SHORT_state(self.daily_ohlc.rolling_min(20))
+    elif breakthrough_55_high:
+      self.__to_LONG_state(self.daily_ohlc.rolling_max(55))
+    elif breakthrough_55_low:
+      self.__to_SHORT_state(self.daily_ohlc.rolling_min(55))
+    elif breakthrough_20_high:
+      self.__to_SHADOW_LONG_state(self.daily_ohlc.rolling_max(20))
+    elif breakthrough_20_low:
+      self.__to_SHADOW_SHORT_state(self.daily_ohlc.rolling_min(20))
+
+  def __process_LONG_state(self, quote: Quote):
+    exit_price = max(self.daily_ohlc.rolling_min(10), self.__last_order_price() - self.N * 2)
+    next_entry_price = self.__last_order_price() + self.N / 2
+
+    if crossunder(quote, exit_price):
+      self.trade_next_20_day_breakout = self.portfolio.unrealized_gains(self.instr, exit_price) < 0
+      self.__to_INIT_state(exit_price)
+    elif crossover(quote, next_entry_price) and not self.__reach_unit_limit():
+      self.__submit_order(self.unit_size, next_entry_price)
+
+  def __process_SHORT_state(self, quote: Quote):
+    exit_price = min(self.daily_ohlc.rolling_max(10), self.__last_order_price() + self.N * 2)
+    next_entry_price = self.__last_order_price() - self.N / 2
+
+    if crossover(quote, exit_price):
+      self.trade_next_20_day_breakout = self.portfolio.unrealized_gains(self.instr, exit_price) < 0
+      self.__to_INIT_state(exit_price)
+    elif crossunder(quote, next_entry_price) and not self.__reach_unit_limit():
+      self.__submit_order(-self.unit_size, next_entry_price)
+
+  def __process_SHADOW_LONG_state(self, quote: Quote):
+    exit_price = max(self.daily_ohlc.rolling_min(10), self.__shadow_last_order_price() - self.N * 2)
+    next_entry_price = self.__shadow_last_order_price() + self.N / 2
+
+    if self.daily_ohlc.crossover_x_period_max(55, quote):
+      self.__to_LONG_state(self.daily_ohlc.rolling_max(55))
+    elif self.daily_ohlc.crossunder_x_period_min(55, quote):
+      self.__to_SHORT_state(self.daily_ohlc.rolling_min(55))
+    elif crossunder(quote, exit_price):
+      shadow_unrealized_gains = self.shadow_portfolio.unrealized_gains(self.instr, exit_price)
+      self.trade_next_20_day_breakout = shadow_unrealized_gains < 0
+      self.__to_INIT_state(exit_price)
+    elif crossover(quote, next_entry_price) and not self.__shadow_reach_unit_limit():
+      self.__shadow_submit_order(self.unit_size, next_entry_price)
+
+  def __process_SHADOW_SHORT_state(self, quote: Quote):
+    exit_price = min(self.daily_ohlc.rolling_max(10), self.__shadow_last_order_price() + self.N * 2)
+    next_entry_price = self.__shadow_last_order_price() - self.N / 2
+
+    if self.daily_ohlc.crossover_x_period_max(55, quote):
+      self.__to_LONG_state(self.daily_ohlc.rolling_max(55))
+    elif self.daily_ohlc.crossunder_x_period_min(55, quote):
+      self.__to_SHORT_state(self.daily_ohlc.rolling_min(55))
+    elif crossover(quote, exit_price):
+      shadow_unrealized_gains = self.shadow_portfolio.unrealized_gains(self.instr, exit_price)
+      self.trade_next_20_day_breakout = shadow_unrealized_gains < 0
+      self.__to_INIT_state(exit_price)
+    elif crossunder(quote, next_entry_price) and not self.__shadow_reach_unit_limit():
+      self.__shadow_submit_order(-self.unit_size, next_entry_price)
+
+  @override
+  def unfilled_positions(self, instr: Instrument) -> Position:
+    x = self.desired_portfolio.outstanding_shares(instr) - self.portfolio.outstanding_shares(instr)
+    return self.desired_portfolio.consolidate_last_x_shares(instr, x)
+
+  @override
+  def order_filled(self, new_pos: Position):
+    self.portfolio.add_position(new_pos)
+
+  @override
+  def process_bid_ask(self, bid_ask: BidAsk):
+    assert False, 'todo'
+
+  @override
+  def process_ohlc(self, ohlc: OHLC):
+    prev_day_cnt = len(self.daily_ohlc)
+    self.daily_ohlc.append(ohlc)
+    curr_day_cnt = len(self.daily_ohlc)
+
+    if self.state == State.WARMUP:
+      raise RuntimeError('strategy wasn\'t warmed up yet')
+
+    if prev_day_cnt != curr_day_cnt:
+      self.N = (19 * self.N + self.__true_range(-1)) / 20
+
+    net_liq = self.net_liquid_value(ohlc.close)
+
+    while net_liq < self.tradable_acct_balance * 0.9:
+      self.tradable_acct_balance *= 0.8
+      self.__adjust_unit_size()
+
+    while net_liq > self.tradable_acct_balance / 0.8:
+      self.tradable_acct_balance /= 0.8
+      self.__adjust_unit_size()
+
+    match self.state:
+      case State.INIT:
+        self.__process_INIT_state(ohlc)
+      case State.LONG:
+        self.__process_LONG_state(ohlc)
+      case State.SHORT:
+        self.__process_SHORT_state(ohlc)
+      case State.SHADOW_LONG:
+        self.__process_SHADOW_LONG_state(ohlc)
+      case State.SHADOW_SHORT:
+        self.__process_SHADOW_SHORT_state(ohlc)
+      case _:
+        raise RuntimeError('invalid state')
+
+  @override
+  def net_liquid_value(self, at_price: float) -> float:
+    return self.init_balance + self.portfolio.total_gains(self.instr, at_price)