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trader.py
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trader.py
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from typing import Dict, List
from datamodel import OrderDepth, TradingState, Order
import math
# storing string as const to avoid typos
SUBMISSION = "SUBMISSION"
PEARLS = "PEARLS"
BANANAS = "BANANAS"
PRODUCTS = [
PEARLS,
BANANAS,
]
DEFAULT_PRICES = {
PEARLS : 10_000,
BANANAS : 5_000,
}
class Trader:
def __init__(self) -> None:
print("Initializing Trader...")
self.position_limit = {
PEARLS : 20,
BANANAS : 20,
}
self.round = 0
# Values to compute pnl
self.cash = 0
# positions can be obtained from state.position
# self.past_prices keeps the list of all past prices
self.past_prices = dict()
for product in PRODUCTS:
self.past_prices[product] = []
# self.ema_prices keeps an exponential moving average of prices
self.ema_prices = dict()
for product in PRODUCTS:
self.ema_prices[product] = None
self.ema_param = 0.5
# utils
def get_position(self, product, state : TradingState):
return state.position.get(product, 0)
def get_mid_price(self, product, state : TradingState):
default_price = self.ema_prices[product]
if default_price is None:
default_price = DEFAULT_PRICES[product]
if product not in state.order_depths:
return default_price
market_bids = state.order_depths[product].buy_orders
if len(market_bids) == 0:
# There are no bid orders in the market (midprice undefined)
return default_price
market_asks = state.order_depths[product].sell_orders
if len(market_asks) == 0:
# There are no bid orders in the market (mid_price undefined)
return default_price
best_bid = max(market_bids)
best_ask = min(market_asks)
return (best_bid + best_ask)/2
def get_value_on_product(self, product, state : TradingState):
"""
Returns the amount of MONEY currently held on the product.
"""
return self.get_position(product, state) * self.get_mid_price(product, state)
def update_pnl(self, state : TradingState):
"""
Updates the pnl.
"""
def update_cash():
# Update cash
for product in state.own_trades:
for trade in state.own_trades[product]:
if trade.timestamp != state.timestamp - 100:
# Trade was already analyzed
continue
if trade.buyer == SUBMISSION:
self.cash -= trade.quantity * trade.price
if trade.seller == SUBMISSION:
self.cash += trade.quantity * trade.price
def get_value_on_positions():
value = 0
for product in state.position:
value += self.get_value_on_product(product, state)
return value
# Update cash
update_cash()
return self.cash + get_value_on_positions()
def update_ema_prices(self, state : TradingState):
"""
Update the exponential moving average of the prices of each product.
"""
for product in PRODUCTS:
mid_price = self.get_mid_price(product, state)
if mid_price is None:
continue
# Update ema price
if self.ema_prices[product] is None:
self.ema_prices[product] = mid_price
else:
self.ema_prices[product] = self.ema_param * mid_price + (1-self.ema_param) * self.ema_prices[product]
# Algorithm logic
def pearls_strategy(self, state : TradingState):
"""
Returns a list of orders with trades of pearls.
Comment: Mudar depois. Separar estrategia por produto assume que
cada produto eh tradado independentemente
"""
position_pearls = self.get_position(PEARLS, state)
bid_volume = self.position_limit[PEARLS] - position_pearls
ask_volume = - self.position_limit[PEARLS] - position_pearls
orders = []
orders.append(Order(PEARLS, DEFAULT_PRICES[PEARLS] - 1, bid_volume))
orders.append(Order(PEARLS, DEFAULT_PRICES[PEARLS] + 1, ask_volume))
return orders
def bananas_strategy(self, state : TradingState):
"""
Returns a list of orders with trades of bananas.
Comment: Mudar depois. Separar estrategia por produto assume que
cada produto eh tradado independentemente
"""
position_bananas = self.get_position(BANANAS, state)
bid_volume = self.position_limit[BANANAS] - position_bananas
ask_volume = - self.position_limit[BANANAS] - position_bananas
orders = []
if position_bananas == 0:
# Not long nor short
orders.append(Order(BANANAS, math.floor(self.ema_prices[BANANAS] - 1), bid_volume))
orders.append(Order(BANANAS, math.ceil(self.ema_prices[BANANAS] + 1), ask_volume))
if position_bananas > 0:
# Long position
orders.append(Order(BANANAS, math.floor(self.ema_prices[BANANAS] - 2), bid_volume))
orders.append(Order(BANANAS, math.ceil(self.ema_prices[BANANAS]), ask_volume))
if position_bananas < 0:
# Short position
orders.append(Order(BANANAS, math.floor(self.ema_prices[BANANAS]), bid_volume))
orders.append(Order(BANANAS, math.ceil(self.ema_prices[BANANAS] + 2), ask_volume))
return orders
def run(self, state: TradingState) -> Dict[str, List[Order]]:
"""
Only method required. It takes all buy and sell orders for all symbols as an input,
and outputs a list of orders to be sent
"""
self.round += 1
pnl = self.update_pnl(state)
self.update_ema_prices(state)
print(f"Log round {self.round}")
print("TRADES:")
for product in state.own_trades:
for trade in state.own_trades[product]:
if trade.timestamp == state.timestamp - 100:
print(trade)
print(f"\tCash {self.cash}")
for product in PRODUCTS:
print(f"\tProduct {product}, Position {self.get_position(product, state)}, Midprice {self.get_mid_price(product, state)}, Value {self.get_value_on_product(product, state)}, EMA {self.ema_prices[product]}")
print(f"\tPnL {pnl}")
# Initialize the method output dict as an empty dict
result = {}
# PEARL STRATEGY
try:
result[PEARLS] = self.pearls_strategy(state)
except Exception as e:
print("Error in pearls strategy")
print(e)
# BANANA STRATEGY
try:
result[BANANAS] = self.bananas_strategy(state)
except Exception as e:
print("Error in bananas strategy")
print(e)
print("+---------------------------------+")
return result