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bot.py
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bot.py
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from tradersbot import *
from time import sleep
from time import time
import blackscholes
import numpy as np
from scipy.stats import norm
import math
import copy
t = TradersBot('127.0.0.1', 'trader0', 'trader0')
class BaseBot():
def __init__(self):
self.count = 0
self.deltas = 0
self.vegas = 0
self.elapsedTime = 0
self.topBid = {}
self.topAsk = {}
self.avgAsk = {}
self.avgBid = {}
self.lastPrices = {"TMXFUT": 100,
'T80P': 0,
'T80C': 0,
'T81P': 0,
'T81C': 0,
'T82P': 0,
'T82C': 0,
'T83P': 0,
'T83C': 0,
'T84P': 0,
'T84C': 0,
'T85P': 0,
'T85C': 0,
'T86P': 0,
'T86C': 0,
'T87P': 0,
'T87C': 0,
'T88P': 0,
'T88C': 0,
'T89P': 0,
'T89C': 0,
'T90P': 0,
'T90C': 0,
'T91P': 0,
'T91C': 0,
'T92P': 0,
'T92C': 0,
'T93P': 0,
'T93C': 0,
'T94P': 0,
'T94C': 0,
'T95P': 0,
'T95C': 0,
'T96P': 0,
'T96C': 0,
'T97P': 0,
'T97C': 0,
'T98P': 0,
'T98C': 0,
'T99P': 0,
'T99C': 0,
'T100P': 0,
'T100C': 0,
'T101P': 0,
'T101C': 0,
'T102P': 0,
'T102C': 0,
'T103P': 0,
'T103C': 0,
'T104P': 0,
'T104C': 0,
'T105P': 0,
'T105C': 0,
'T106P': 0,
'T106C': 0,
'T107P': 0,
'T107C': 0,
'T108P': 0,
'T108C': 0,
'T109P': 0,
'T109C': 0,
'T110P': 0,
'T110C': 0,
'T111P': 0,
'T111C': 0,
'T112P': 0,
'T112C': 0,
'T113P': 0,
'T113C': 0,
'T114P': 0,
'T114C': 0,
'T115P': 0,
'T115C': 0,
'T116P': 0,
'T116C': 0,
'T117P': 0,
'T117C': 0,
'T118P': 0,
'T118C': 0,
'T119P': 0,
'T119C': 0,
'T120P': 0,
'T120C': 0, }
self.positions = {'T80P': 0,
'T80C': 0,
'T81P': 0,
'T81C': 0,
'T82P': 0,
'T82C': 0,
'T83P': 0,
'T83C': 0,
'T84P': 0,
'T84C': 0,
'T85P': 0,
'T85C': 0,
'T86P': 0,
'T86C': 0,
'T87P': 0,
'T87C': 0,
'T88P': 0,
'T88C': 0,
'T89P': 0,
'T89C': 0,
'T90P': 0,
'T90C': 0,
'T91P': 0,
'T91C': 0,
'T92P': 0,
'T92C': 0,
'T93P': 0,
'T93C': 0,
'T94P': 0,
'T94C': 0,
'T95P': 0,
'T95C': 0,
'T96P': 0,
'T96C': 0,
'T97P': 0,
'T97C': 0,
'T98P': 0,
'T98C': 0,
'T99P': 0,
'T99C': 0,
'T100P': 0,
'T100C': 0,
'T101P': 0,
'T101C': 0,
'T102P': 0,
'T102C': 0,
'T103P': 0,
'T103C': 0,
'T104P': 0,
'T104C': 0,
'T105P': 0,
'T105C': 0,
'T106P': 0,
'T106C': 0,
'T107P': 0,
'T107C': 0,
'T108P': 0,
'T108C': 0,
'T109P': 0,
'T109C': 0,
'T110P': 0,
'T110C': 0,
'T111P': 0,
'T111C': 0,
'T112P': 0,
'T112C': 0,
'T113P': 0,
'T113C': 0,
'T114P': 0,
'T114C': 0,
'T115P': 0,
'T115C': 0,
'T116P': 0,
'T116C': 0,
'T117P': 0,
'T117C': 0,
'T118P': 0,
'T118C': 0,
'T119P': 0,
'T119C': 0,
'T120P': 0,
'T120C': 0,
'TMXFUT': 0, }
self.expect_positions = {'T80P': 0,
'T80C': 0,
'T81P': 0,
'T81C': 0,
'T82P': 0,
'T82C': 0,
'T83P': 0,
'T83C': 0,
'T84P': 0,
'T84C': 0,
'T85P': 0,
'T85C': 0,
'T86P': 0,
'T86C': 0,
'T87P': 0,
'T87C': 0,
'T88P': 0,
'T88C': 0,
'T89P': 0,
'T89C': 0,
'T90P': 0,
'T90C': 0,
'T91P': 0,
'T91C': 0,
'T92P': 0,
'T92C': 0,
'T93P': 0,
'T93C': 0,
'T94P': 0,
'T94C': 0,
'T95P': 0,
'T95C': 0,
'T96P': 0,
'T96C': 0,
'T97P': 0,
'T97C': 0,
'T98P': 0,
'T98C': 0,
'T99P': 0,
'T99C': 0,
'T100P': 0,
'T100C': 0,
'T101P': 0,
'T101C': 0,
'T102P': 0,
'T102C': 0,
'T103P': 0,
'T103C': 0,
'T104P': 0,
'T104C': 0,
'T105P': 0,
'T105C': 0,
'T106P': 0,
'T106C': 0,
'T107P': 0,
'T107C': 0,
'T108P': 0,
'T108C': 0,
'T109P': 0,
'T109C': 0,
'T110P': 0,
'T110C': 0,
'T111P': 0,
'T111C': 0,
'T112P': 0,
'T112C': 0,
'T113P': 0,
'T113C': 0,
'T114P': 0,
'T114C': 0,
'T115P': 0,
'T115C': 0,
'T116P': 0,
'T116C': 0,
'T117P': 0,
'T117C': 0,
'T118P': 0,
'T118C': 0,
'T119P': 0,
'T119C': 0,
'T120P': 0,
'T120C': 0,
'TMXFUT': 0, }
self.maxPos = 20000
self.priceChange = {}
self.pnl = 0
self.iv_diff_threshold = 0.0001
def volatility_smile(self):
prices = []
for i in range(41):
prices.append(80.+i)
ivs = []
deltas = []
vegas = []
calls = []
puts = []
if 'TMXFUT' in self.lastPrices:
for p in prices:
s = self.lastPrices['TMXFUT']
k = p
r = 0
t = self.elapsedTime
big_T = 900
call = self.lastPrices['T' + str(int(p)) + 'C']
put = self.lastPrices['T' + str(int(p)) + 'P']
eps = .000001
o = blackscholes.invert_scalar(s, k, r, t, big_T, call, put, eps)
ivs.append(o)
d1 = (math.log(s / k) + (r + o * o / 2) * (big_T - t)) / (o * math.sqrt(big_T - t))
deltas.append(norm.cdf(d1))
vegas.append(s * norm.pdf(d1) * math.sqrt(big_T - t))
calls.append(call)
puts.append(put)
return prices, ivs, deltas, vegas, calls, puts
pass
def delta(self):
delta = 0
prices = []
for i in range(41):
prices.append(80.+i)
deltas = self.volatility_smile()[2]
for p in prices:
call_name = 'T' + str(int(p)) + 'C'
put_name = 'T' + str(int(p)) + 'P'
delta -= self.positions[put_name] * deltas[prices.index(p)]
delta += self.positions[call_name] * deltas[prices.index(p)]
delta += self.positions["TMXFUT"]
return delta
def arbitrage(self,msg,order):
mindiscrep = 0.05
prices = []
for i in range(41):
prices.append(80.+i)
ivs = self.volatility_smile()[1]
coefs = self.fitIvs(ivs)
expected = []
excall = []
exput = []
for i in range(80,121):
expected.append(coefs[0]*i**4+coefs[1]*i**3+coefs[2]*i*i+coefs[3]*i+coefs[4])
for i in range(len(prices)):
s = self.lastPrices['TMXFUT']
k = prices[i]
r = 0
t = self.elapsedTime
big_T = 900
excall.append(blackscholes.blackscholes_scalar(s,k,r,expected[i],t,big_T))
exput.append(excall[i] - self.lastPrices['TMXFUT'] + prices[i])
for i in range(len(excall)):
call_name = 'T' + str(int(i + 80)) + 'C'
put_name = 'T' + str(int(i + 80)) + 'P'
if call_name in self.topAsk:
if (1+mindiscrep)*self.topAsk[call_name] < excall[i]:
order.addBuy(call_name,1,(1+mindiscrep)*self.topAsk[call_name])
if call_name in self.topBid:
if (1-mindiscrep)*self.topBid[call_name] > excall[i]:
order.addSell(call_name,1,(1-mindiscrep)*self.topBid[call_name])
if put_name in self.topAsk:
if (1+mindiscrep)*self.topAsk[put_name] < exput[i]:
order.addBuy(put_name,1,(1+mindiscrep)*self.topAsk[put_name])
if put_name in self.topBid:
if (1-mindiscrep)*self.topBid[put_name] > exput[i]:
order.addSell(put_name,1,(1-mindiscrep)*self.topAsk[put_name])
def update(self, msg):
if type(msg.get('elapsed_time')) == int:
self.elapsedTime = msg.get('elapsed_time')
if msg.get('market_states'):
raise KeyError
for ticker, state in msg['market_states'].iteritems():
if len(state['bids']):
self.topBid[ticker] = max(map(float, state['bids'].keys()))
if len(state['asks']):
self.topAsk[ticker] = min(map(float, state['asks'].keys()))
self.lastPrices[ticker] = state['last_price']
self.priceChange[ticker] = 0
# Update internal book for a single ticker
if msg.get('market_state'):
state = msg['market_state']
ticker = state['ticker']
if len(state['bids']):
self.topBid[ticker] = max(map(float, state['bids'].keys()))
self.avgBid[ticker] = round(np.mean(list(map(float, state['bids'].keys()))), 2)
if len(state['asks']):
self.topAsk[ticker] = min(map(float, state['asks'].keys()))
self.avgAsk[ticker] = round(np.mean(list(map(float, state['asks'].keys()))), 2)
self.lastPrices[ticker] = state['last_price']
else:
return None
def update_positions(self, msg,order):
if msg.get('trader_state'):
self.positions = msg['trader_state']['positions']
if msg.get('message_type') == 'TRADER UPDATE':
self.cash = msg["trader_state"]["cash"]["USD"]
self.pnl = msg["trader_state"]["pnl"]["USD"]
def process(self, msg, order):
##if msg.get('market_state') or msg.get('trader_state') or msg.get('market_states'):
self.update(msg)
self.update_positions(msg,order)
d = 0
if self.count >= 300 and self.count%300==0:
d = self.delta()
print(d)
if self.count > 600 and self.count%600 == 0:
self.better_delta_hedge(d, msg, order)
if self.count >= 300 and self.count%600==0:
d = self.delta()
if self.count % 300 == 0:
if d < 120:
self.make_better_call_market(msg, order)
if d > -120:
self.make_better_put_market(msg, order)
print(self.pnl)
self.count += 1
def fitIvs(self, ivs):
x = []
for i in range(41):
x.append(80.+i)
return np.polyfit(x,ivs,4)
def make_market(self, msg, order):
for option in self.positions.keys():
quantity = 25
shift = 0
if option in self.topAsk and option in self.topBid:
if d < 300:
order.addBuy(option, quantity, self.avgBid[option]+shift)
if d > -300:
order.addSell(option, quantity, self.avgAsk[option]-shift)
def make_call_market(self, msg, order):
for i in range(41):
option = 'T' + str(int(i + 80)) + 'C'
quantity = 25
shift = 0
if option in self.topAsk and option in self.topBid:
order.addBuy(option, quantity, self.avgBid[option]+shift)
order.addSell(option, quantity, self.avgAsk[option]-shift)
else:
print('-------------------------------------')
def make_put_market(self, msg, order):
for i in range(41):
option = 'T' + str(int(i + 80)) + 'P'
quantity = 25
shift = 0
if option in self.topAsk and option in self.topBid:
order.addBuy(option, quantity, self.avgBid[option]+shift)
order.addSell(option, quantity, self.avgAsk[option]-shift)
else:
print('-------------------------------------')
def make_better_call_market(self, msg, order):
for i in range(41):
c_option = 'T' + str(int(i + 80)) + 'C'
p_option = 'T' + str(int(i + 80)) + 'P'
quantity = 10
shift = 0
if c_option in self.topAsk and c_option in self.topBid:
order.addBuy(c_option, quantity, self.avgBid[c_option]+shift)
if p_option in self.topAsk and p_option in self.topBid:
order.addSell(p_option, quantity, self.avgAsk[p_option]-shift)
def make_better_put_market(self, msg, order):
for i in range(41):
c_option = 'T' + str(int(i + 80)) + 'C'
p_option = 'T' + str(int(i + 80)) + 'P'
quantity = 10
shift = 0
if p_option in self.topAsk and p_option in self.topBid:
order.addBuy(p_option, quantity, self.avgBid[p_option]+shift)
if c_option in self.topAsk and c_option in self.topBid:
order.addSell(c_option, quantity, self.avgAsk[c_option]-shift)
def delta_hedge(self, msg, order):
d = self.delta()
if abs(d) > 120:
print(d)
quantity = int(abs(d) - 100)
print(self.topAsk['TMXFUT'])
order.addBuy('TMXFUT', quantity, self.topAsk['TMXFUT']+10)
if d > 150:
print(d)
quantity = int(d)-100
order.addSell('TMXFUT', quantity, self.topAsk['TMXFUT']-10)
def better_delta_hedge(self, d, msg, order):
if d < -120:
print(d)
quantity = min(int(abs(d) - 100), 400)
order.addBuy('TMXFUT', quantity, self.topAsk['TMXFUT']+10)
if d > 120:
print(d)
quantity = min(int(d)-100, 400)
order.addSell('TMXFUT', quantity, self.topBid['TMXFUT']-10)
b = BaseBot()
t.onMarketUpdate = b.process
t.onTraderUpdate = b.update_positions
t.run()
#changed avgAsk, Bid, make_market