Exemplo n.º 1
0
        }
        pending_orders.append(new_order)
    except:
        print('Unable to parse headline: Unknown error')


DEBUG = True
algo_bot = None
if len(sys.argv) >= 4:
    algo_bot = TradersBot(host=sys.argv[1],
                          id=sys.argv[2],
                          password=sys.argv[3])
    # DEBUG = False
    CANCEL_TRADES = False
else:
    algo_bot = TradersBot('127.0.0.1', 'trader0', 'trader0')
algo_bot.onAckRegister = onAckRegister
algo_bot.onMarketUpdate = onMarketUpdate
algo_bot.onTraderUpdate = onTraderUpdate
algo_bot.onTrade = onTrade
algo_bot.onAckModifyOrders = onAckModifyOrders
algo_bot.onNews = onNews

if not DEBUG:

    def f(*args):
        return None

    print = f

algo_bot.run()
Exemplo n.º 2
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	print 'Data ', news

	if len(news) >= 2:
		x = []
		d1 = np.array(news[-2])
		d0 = np.delete(np.array(news[-1]),[2])
		x = np.append(x, d0)
		x = np.append(x,d1)
		print 'Prediction: ', ridge.predict([x])[0]

t.onNews = updatePredict

def hi(msg,order):
	print "hey"

t.onAckRegister = hi
# ######################################################
# # each time AAPL trade happens for $x, make bid
# # and ask at $x-0.02, $x+0.02, respectively
# def marketMake(msg, order):
#     for trade in msg["trades"]:
#         if trade["ticker"] == 'AAPL':
#             px = trade["price"]
#             order.addBuy('AAPL', 10, px - 0.02)
#             order.addSell('AAPL', 10, px + 0.02)

#t.onTrade = marketMake



Exemplo n.º 3
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def load_case(msg, TradersOrder):
    global model, res, case_meta, outcry_data
    print('Connected!')
    case_meta = msg['case_meta']
    outcry_data = pd.read_csv('./outcry_data.csv')
    for name in outcry_data.columns:
        outcry_data[name] = proportional_change(outcry_data[name])
    model = smf.ols(
        formula='TAMIT ~ GDP + CPI + RS + HS + PPI + MTIS + U + MS + PI',
        data=outcry_data)
    res = model.fit()


t.onAckRegister = load_case

## onAckModifyOrders

## onNews


def get_data(msg, TradersOrder):
    global res, model, outcry_data, pred_counter
    news = msg['news']['body']
    news_items = news.split(';')
    news_items = [item.split() for item in news_items]
    names = [item[0] for item in news_items]
    numbers = [[float(item[4])] for item in news_items]
    reading = zip(names, numbers)
    reading = pd.DataFrame.from_items(reading)
Exemplo n.º 4
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def trade_method(msg, order):
    global MARKET
    print(MARKET['T85C']['price'])
    trade_dict = msg['trades']
    for trade in trade_dict:
        security = MARKET[trade["ticker"]]
        security['price'] = trade["price"]
        # security['vol'] = calc_vol(security['type'] == 'C', trade['price'], 100, security['strike'], exp_time(), INTEREST_RATE)

# Buys or sells in a random quantity every time it gets an update
# You do not need to buy/sell here
def trader_update_method(msg, order):
    global MARKET
    positions = msg['trader_state']['positions']
    for security in positions.keys():
        if random.random() < 0.5:
            quant = 10*random.randint(1, 10)
            order.addBuy(security, quantity=quant,price=MARKET[security]['price'])
        else:
            quant = 10*random.randint(1, 10)
            order.addSell(security, quantity=quant,price=MARKET[security]['price'])


t.onAckRegister = ack_register_method
t.onMarketUpdate = market_update_method
t.onTraderUpdate = trader_update_method
t.onTrade = trade_method
#t.onAckModifyOrders = ack_modify_orders_method
#t.onNews = news_method
t.run()