示例#1
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### Our Strategy Follows Here ###

#Rather than Focussing on Arbitrage we try to make the most of a market that hopefully fluctuates around a reasonnably fixed average. Given no real product we thought this would be accurate.

#We create an array that is a weighted version of our current portfolio of shares. We then view the market relative to the average of our current position in order to make decisions

#We think this should work and it does for good periods of time. It is susceptible to large and consistent changes to the market which unfortunately happened this morning!

bought_prices = [average_b(200) + 0.5]
weighted_prices_a = [average_a(3)]

weighted_prices_b = [average_b(3)]

start_pnl = e.get_pnl()
new_pnl = e.get_pnl()

timer = 0
#new_start_b = [average_b(20)]*10
#weighted_prices_b = new_start_b

while timer < 2000:
    stats_a = get_range_a(10000)
    stats_b = get_range_b(10000)

    max_range_a = stats_a[0] - stats_a[1]
    low_range_b = stats_b[1] - stats_b[2]

    book_a = e.get_last_price_book(philips_a)
    book_b = e.get_last_price_book(philips_b)
示例#2
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import time
import logging

from optibook.synchronous_client import Exchange

from strategy import should_kill_attempt, arbitrage, stoikov_mm
from utils import balance_positions
from moving_average import MovingAverage

logging.getLogger('client').setLevel('ERROR')

exchange = Exchange()
exchange.connect()

START_PNL = exchange.get_pnl()

ma_A = MovingAverage(exchange, "PHILIPS_A")

tick = 1

while not should_kill_attempt(exchange, START_PNL):
    time.sleep(0.11)

    print(f"tick {tick}")
    tick += 1

    ma_A.update()

    # Don't want to balance our trades from our MM positions
    exchange.delete_orders("PHILIPS_A")
示例#3
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    print(
        f"[TRADED {t.instrument_id}] price({t.price}), volume({t.volume}), side({t.side})"
    )

# Returns all current positions
positions = e.get_positions()
for p in positions:
    print(p, positions[p])

# Returns all current positions with cash investedx
positions = e.get_positions_and_cash()
for p in positions:
    print(p, positions[p])

# Returns Current PnL based on last Traded Price
pnl = e.get_pnl()
print(pnl)

book_A = e.get_last_price_book("PHILIPS_A")
book_B = e.get_last_price_book("PHILIPS_B")
print('bids_PHILIPS_A:')
print("bid\tprice\task")
for i in reversed(book_A.asks):
    print('\t' + str(round(i.price, 1)) + '\t' + str(i.volume))
for i in book_A.bids:
    print(str(i.volume) + '\t' + str(round(i.price, 1)) + '\t')

# Returns all public tradeticks since the last time this function was called
tradeticks = e.poll_new_trade_ticks(instrument_id)
for t in tradeticks:
    print(