def __init__(self, ttype, tid, balance, time):
Trader.__init__(self, ttype, tid, balance, time)
self.prev_orders = []
self.active = False
self.limit = None
self.job = None
#memory of all bids and asks and accepted bids and asks
self.outstanding_bids = []
self.outstanding_asks = []
self.accepted_asks = []
self.accepted_bids = []
self.price = -1
# memory of best price & quantity of best bid and ask, on LOB on previous update
self.prev_best_bid_p = None
self.prev_best_bid_q = None
self.prev_best_ask_p = None
self.prev_best_ask_q = None
self.first_turn = True
self.gamma = 0.1
self.holdings = 10
self.remaining_offer_ops = 10
self.values = [[0 for n in range(self.remaining_offer_ops)]
for m in range(self.holdings)]
def __init__(self, ttype, tid, balance, time):
Trader.__init__(self, ttype, tid, balance, time)
self.limit = None
self.job = None
# variable for MLOFI
self.last_lob = None
self.list_OFI = []
self.list_D = []
def __init__(self, ttype, tid, balance, time, m):
Trader.__init__(self, ttype, tid, balance, time)
self.limit = None
self.job = None
# variable for MLOFI
self.last_lob = None
self.es_list = []
self.ds_list = []
#variable
self.m = m
def __init__(self, ttype, tid, balance, time,m):
Trader.__init__(self, ttype, tid, balance, time)
self.limit = None
self.job = None
# learning variables
self.r_shout_change_relative = 0.05
self.r_shout_change_absolute = 0.05
self.short_term_learning_rate = random.uniform(0.1, 0.5)
self.long_term_learning_rate = random.uniform(0.1, 0.5)
self.moving_average_weight_decay = 0.95 # how fast weight decays with time, lower is quicker, 0.9 in vytelingum
self.moving_average_window_size = 5
self.offer_change_rate = 3.0
self.theta = -2.0
self.theta_max = 2.0
self.theta_min = -8.0
self.marketMax = bse_sys_maxprice
# Variables to describe the market
self.previous_transactions = []
self.moving_average_weights = []
for i in range(self.moving_average_window_size):
self.moving_average_weights.append(self.moving_average_weight_decay ** i)
self.estimated_equilibrium = []
self.smiths_alpha = []
self.prev_best_bid_p = None
self.prev_best_bid_q = None
self.prev_best_ask_p = None
self.prev_best_ask_q = None
# Trading Variables
self.r_shout = None
self.buy_target = None
self.sell_target = None
self.buy_r = -1.0 * (0.3 * random.random())
self.sell_r = -1.0 * (0.3 * random.random())
# variable for MLOFI
self.last_lob = None;
self.es_list = [];
self.ds_list = [];
#variable for ratio
self.bids_volume_list = []
self.asks_volume_list = []
# m
self.m = m;
def __init__(self, ttype, tid, balance, time,m):
Trader.__init__(self, ttype, tid, balance, time)
self.limit = None
self.job = None
# variable for MLOFI
self.last_lob = None;
self.es_list = [];
self.ds_list = [];
#variable for ratio
self.bids_volume_list = []
self.asks_volume_list = []
# m
self.m = m;
def __init__(self, ttype, tid, balance, time,m):
Trader.__init__(self, ttype, tid, balance, time)
self.active = False
self.limit = None
self.job = None
#memory of all bids and asks and accepted bids and asks
self.outstanding_bids = []
self.outstanding_asks = []
self.accepted_asks = []
self.accepted_bids = []
self.price = -1
# memory of best price & quantity of best bid and ask, on LOB on previous update
self.prev_best_bid_p = None
self.prev_best_bid_q = None
self.prev_best_ask_p = None
self.prev_best_ask_q = None
self.first_turn = True
self.gamma = 0.1
self.holdings = 10
self.remaining_offer_ops = 10
self.values = [[0 for n in range(self.remaining_offer_ops)] for m in range(self.holdings)]
# variable for MLOFI
self.last_lob = None;
self.es_list = [];
self.ds_list = [];
# variable for ratio
self.bids_volume_list = []
self.asks_volume_list = []
# variable
self.m = m;
def __init__(self, ttype, tid, balance, time, m):
Trader.__init__(self, ttype, tid, balance, time)
m_fix = 0.05
m_var = 0.05
self.job = None # this is 'Bid' or 'Ask' depending on customer order
self.active = False # gets switched to True while actively working an order
self.prev_change = 0 # this was called last_d in Cliff'97
self.beta = 0.1 + 0.2 * random.random() # learning rate
self.momntm = 0.3 * random.random() # momentum
self.ca = 0.10 # self.ca & .cr were hard-coded in '97 but parameterised later
self.cr = 0.10
self.margin = None # this was called profit in Cliff'97
self.margin_buy = -1.0 * (m_fix + m_var * random.random())
self.margin_sell = m_fix + m_var * random.random()
self.price = None
self.limit = None
# memory of best price & quantity of best bid and ask, on LOB on previous update
self.prev_best_bid_p = None
self.prev_best_bid_q = None
self.prev_best_ask_p = None
self.prev_best_ask_q = None
# memory of worst prices from customer orders received so far
self.worst_bidprice = None
self.worst_askprice = None
# variable for MLOFI
self.last_lob = None
self.es_list = []
self.ds_list = []
#variable for ratio
self.bids_volume_list = []
self.asks_volume_list = []
#variable
self.m = m