def __init__(self, *args, **kwargs):
self.START_TIME = datetime.datetime.now()
BaseExchangeServerClient.__init__(self, *args, **kwargs)
# self.codes = ["C100PHX", "P100PHX",]
self.codes = [
"C98PHX",
"P98PHX",
"C99PHX",
"P99PHX",
"C100PHX",
"P100PHX",
"C101PHX",
"P101PHX",
"C102PHX",
"P102PHX",
]
self._orderids = {}
self.asset_codes = self.__init_asset_codes()
self.underlying_code = "IDX#PHX"
self.underlying_price = 100
self.inventory = self.__init_inventory()
self.potential_inventory = self.__init_inventory()
self.ticks = [[0]]
self.tick = 0
self.order_pops = set([])
def __init__(self, *args, **kwargs):
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self._orderids = set([])
self._count = 0
self.k_array = []
self.m_array = []
self.n_array = []
self.q_array = []
self.u_array = []
self.v_array = []
def __init__(self, *args, **kwargs):
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self._orderids = set([])
self.positions = {
'C98PHX': 0,
'P98PHX': 0,
'C99PHX': 0,
'P99PHX': 0,
'C100PHX': 0,
'P100PHX': 0,
'C101PHX': 0,
'P101PHX': 0,
'C102PHX': 0,
'P102PHX': 0,
'IDX#PHX': 0
}
self.deltas = {
'C98PHX': 0,
'P98PHX': 0,
'C99PHX': 0,
'P99PHX': 0,
'C100PHX': 0,
'P100PHX': 0,
'C101PHX': 0,
'P101PHX': 0,
'C102PHX': 0,
'P102PHX': 0,
'IDX#PHX': 1
}
self.vegas = {
'C98PHX': 0,
'P98PHX': 0,
'C99PHX': 0,
'P99PHX': 0,
'C100PHX': 0,
'P100PHX': 0,
'C101PHX': 0,
'P101PHX': 0,
'C102PHX': 0,
'P102PHX': 0
}
self.delta_ptflo = 0
self.vega_ptflo = 0
self.start_time = time.time()
self.net_exposure = 0
self.bid_dict = {}
self.ask_dict = {}
self.mid_dict = {}
def __init__(self, *args, **kwargs):
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self.open_orderids = set([])
self._count = 0
self._mid_market = []
self._lastGuess = []
self._lastMarket = []
self._lastPolly = []
#This is used to relate the symbol to the index of the arrays
self._symbol_dict = {'K': 0,
'M': 1,
'N': 2,
'Q': 3,
'U': 4,
'V': 5}
#some arbitrary price calculation. probably will do something w/ the standard deviation that makes it better
self._max_wiggle = 6
self._modify_wiggle=0.05
self._each_wiggle=0.02
self._quant = 4
self._pnl_fix = 0
self._dumpLim = 10
self._dumped = False
'''
order_id_dict holds the ids for the limit orders around the calcualted theo
reversion dict holds the ids for the orders that calculate the mean reversion
_price_dict is not implemented but will hold the prices if needed
'''
self.order_id_dict = {}
self.market_data = {}
self.owned_shares = {}
for key, _ in self._symbol_dict.items():
self.order_id_dict[key + '_short'] = [(0, 0),(0, 0),(0, 0),(0, 0),(0, 0),(0, 0)]
self.order_id_dict[key + '_long'] = [(0, 0),(0, 0),(0, 0),(0, 0),(0, 0),(0, 0)]
self.market_data[key] = []
self.owned_shares[key] = 0
#This is used to calculated the exponential weights needed for the MA time series
self._weights = []
for x in range(0,29):
self._weights.append(math.e**-x)
def __init__(self, *args, **kwargs):
# Init BaseExchangeServerClient
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self._orderids = set([])
# Our future contract codes and pairs
self.contract_list = ['K', 'M', 'N', 'Q', 'U', 'V']
# redesign pair
self.contract_pairs = [('K', 'M'), ('K', 'N'), ('K', 'Q'), ('K', 'U'), ('K', 'V'), \
('M', 'N'), ('M', 'Q'), ('M', 'U'), ('M', 'V'), \
('N', 'Q'), ('N', 'U'), ('N', 'V'), \
('Q', 'U'), ('Q', 'V'), \
('U', 'V')]
# History Data
self.hist_mid_price = {
contract_code: None
for contract_code in self.contract_list
}
# Record weights
self.current_weights = {
contract_code: 0
for contract_code in self.contract_list
}
# Record contract status
self.in_Long = {
contract_pair: False
for contract_pair in self.contract_pairs
}
self.in_Short = {
contract_pair: False
for contract_pair in self.contract_pairs
}
# Time Windows
self.long_ma = 10
self.short_ma = 5
self.counter = 0
def __init__(self, *args, **kwargs):
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self._bids = {
"C98PHX": set(),
"C99PHX": set(),
"C100PHX": set(),
"C101PHX": set(),
"C102PHX": set(),
"P98PHX": set(),
"P99PHX": set(),
"P100PHX": set(),
"P101PHX": set(),
"P102PHX": set(),
"IDX#PHX": set()
}
self._asks = {
"C98PHX": set(),
"C99PHX": set(),
"C100PHX": set(),
"C101PHX": set(),
"C102PHX": set(),
"P98PHX": set(),
"P99PHX": set(),
"P100PHX": set(),
"P101PHX": set(),
"P102PHX": set(),
"IDX#PHX": set()
}
self._quant = {
"C98PHX": 0,
"C99PHX": 0,
"C100PHX": 0,
"C101PHX": 0,
"C102PHX": 0,
"P98PHX": 0,
"P99PHX": 0,
"P100PHX": 0,
"P101PHX": 0,
"P102PHX": 0,
"IDX#PHX": 0
}
self._filled = {}
def __init__(self, *args, **kwargs):
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self.open_orderids = set([])
self._count = 0
self.k_array = []
self.m_array = []
self.n_array = []
self.q_array = []
self.u_array = []
self.v_array = []
#some arbitrary price calculation. probably will do something w/ the standard deviation that makes it better
self._wiggle = .001
#This is used to relate the symbol to the index of the arrays
self._symbol_dict = {'K': 0, 'M': 1, 'N': 2, 'Q': 3, 'U': 4, 'V': 5}
#order_id_dict holds the ids for the limit orders around the calcualted theo
#reversion dict holds the ids for the orders that calculate the mean reversion
#_price_dict is not implemented but will hold the prices if needed
self.order_id_dict = {}
self.reversion_dict = {}
self.price_dict = {}
for x in ['K', 'M', 'N', 'Q', 'U', 'V']:
self.order_id_dict[x + '_short'] = 0
self.order_id_dict[x + '_long'] = 0
self.price_dict[x + '_short'] = 0
self.price_dict[x + '_long'] = 0
self.reversion_dict[x + '_short'] = 0
self.reversion_dict[x + '_long'] = 0
#This is used to calculated the exponential weights needed for the MA time series
self._weights = []
for x in range(0, 50):
self._weights.append(math.e**-x)
#This is used to know what amount of shares we have
self.owned_shares = {}
for x in ['K', 'M', 'N', 'Q', 'U', 'V']:
self.owned_shares[x] = 0
def __init__(self, *args, **kwargs):
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self.symbols = [
"C98PHX", "C99PHX", "C100PHX", "C101PHX", "C102PHX", "P98PHX",
"P99PHX", "P100PHX", "P101PHX", "P102PHX", "IDX#PHX"
]
self.kernel = kvt.MarketMaker(
10, # straddle size
10, # max position size
5, # liquidity depth
1, # reprice threshold
1.0) # delta max
self.mid_market_price = {}
self.orders = {}
self.portfolio = {}
for sym in self.symbols:
self.mid_market_price[sym] = 0
self.orders[sym] = deque()
self.portfolio[sym] = 0
def __init__(self, *args, **kwargs):
BaseExchangeServerClient.__init__(self, *args, **kwargs)
self._orderids = set([])