def _process(self):
time.sleep(2)
for stock in q01():
#print stock
#print stock['Empresa']
#print empresasRiesgos
for stock2 in empresasRiesgos:
#print stock['Empresa']
#print stock2['Enterprise']
if stock['Empresa'] == stock2['Enterprise']:
print stock['ValorActual']
changePercentage = (stock['ValorActual'] -
stock2['LastPrice']) / 100
stock2['LastPrice'] = stock['ValorActual']
if len(stock2['RisksValues']) >= 15:
stock2['RisksValues'].pop(0)
stock2['RisksValues'].append(changePercentage)
else:
stock2['RisksValues'].append(changePercentage)
print "Historic Risks of %s:" % stock2['Enterprise']
print stock2['RisksValues']
totalRisk = 0
for risk in stock2['RisksValues']:
totalRisk += risk
#print totalRisk
print "totalRisk: %s" % totalRisk
if totalRisk <= -7:
print '***********Notificar a gente de toma de decisiones*******************'
stock2['RisksValues'] = []
def _process(self):
#Wait for a message from the monitor agent
time.sleep(3)
for stock in q01():
enterprise = stock['Empresa']
if len(historic_prices[enterprise]) > 10:
historic_prices[enterprise] = []
historic_volumes[enterprise] = []
historic_prices[enterprise].insert(0,stock['ValorActual'])
historic_volumes[enterprise].insert(0,stock['Volumen'])
#What strategy for this stock?
strategy = q09(enterprise)
# Strategy 1, If the value of my auction goes up 2 times
if strategy == 1:
if len(historic_prices[enterprise]) > 2:
self.strategy1(enterprise,historic_prices[enterprise])
#Strategy 2, If the value of the auction goes down 5 times
elif strategy == 2:
if len(historic_prices[enterprise]) > 5:
self.strategy2(enterprise,historic_prices[enterprise])
elif strategy == 3:
#Strategy 3, If the value of an auction volume has an abnormal positive change, then buy
if len(historic_volumes[enterprise]) > 2:
self.strategy2(enterprise,historic_volumes[enterprise])
elif strategy == 4:
#Strategy 4 If the value of an auction volume has an abnormal negative change, then sell
if len(historic_volumes[enterprise]) > 2:
self.strategy2(enterprise,historic_volumes[enterprise])
print "Watching stock %s with strategy %d NO CHANGES" %(enterprise, strategy[0]['EstrategiaInversion'])
print "\n\n"
def _process(self):
user_stocks = q01()
for stock in user_stocks:
enterprise = stock['Empresa']
current_date = datetime.now()
date = current_date.strftime('%Y-%m-%d ')
volumen = stock['Volumen']
precio_apertura = stock['PrecioApertura']
volatilidad = stock['Volatilidad']
valor_actual = stock['ValorActual']
precio_clausura = stock['PrecioClausura']
currentPrice = valor_actual
currentVolume = volumen
time.sleep(2)
lastVolume = currentVolume
randomVolumeFluctuation = random.randint(-100000, 100000)
if randomVolumeFluctuation > 98000 or randomVolumeFluctuation < -98000:
currentVolume = currentVolume + randomVolumeFluctuation
print "*********** Sending information to coordinator Abnormal Volume detected!!!! ***********"
content = "\n\n ************* ALERT Abnormal Volume Flucutuation ************* \n The Enterprise %s last volume was : %f and its current volume is: %f\n" % (
enterprise, lastVolume, currentVolume)
self.myAgent.sendToCoordinator("inform", "Monitor",
content)
else:
currentVolume = currentVolume + random.randint(-20, 40)
print "The current volume for %s is: %d" % (enterprise,
currentVolume)
q07(currentVolume, enterprise)
def _setup(self):
''''''
template = spade.Behaviour.ACLTemplate()
template.setOntology("MaS")
template.setPerformative("inform")
template.setConversationId("Decision")
mt = spade.Behaviour.MessageTemplate(template)
self.addBehaviour(self.DecisionBehav(),mt)
for stock in q01():
enterprise = stock['Empresa']
historic_prices[enterprise] = []
historic_volumes[enterprise] = []
historic_prices[enterprise].append(stock['ValorActual'])
historic_volumes[enterprise].append(stock['Volumen'])
print "\n\n*********** Decision Making Agent has Started\n\n"
def _process(self):
user_stocks = q01()
# Obtain the stock information of every asset
for stock in user_stocks:
enterprise = stock['Empresa']
current_date = datetime.now()
date = current_date.strftime('%Y-%m-%d ')
volumen = stock['Volumen']
precio_apertura = stock['PrecioApertura']
volatilidad = stock['Volatilidad']
valor_actual = stock['ValorActual']
precio_clausura = stock['PrecioClausura']
currentPrice = valor_actual
time.sleep(2)
lastPrice = currentPrice
randomPriceFluctuation = random.randint(-1000, 1000)
if randomPriceFluctuation > 900 or randomPriceFluctuation < -900:
currentPrice = currentPrice + randomPriceFluctuation
changePercentage = (currentPrice - lastPrice) / 100
print "******** Sending information to coordinator Abnormal Fluctuation detected!!!! ********"
content = "\n\n ************* ALERT Abnormal Price Flucutuation ************* \n The Enterprise %s last price was : %f and its current price is: %f the change percentage is %f\n" % (
enterprise, lastPrice, currentPrice, changePercentage)
print content
self.myAgent.sendToCoordinator("inform", "Monitor",
content)
else:
currentPrice = currentPrice + random.uniform(-20.3, 40.0)
changePercentage = (currentPrice - lastPrice) / 100
content = {
'Enterprise': enterprise,
'date': date,
'lastPrice': lastPrice,
'currentPrice': currentPrice,
'changePercentage': changePercentage,
}
#Update the database with the new values
q08(currentPrice, enterprise)
print "The current price for %s is: %f" % (enterprise,
currentPrice)
def q1(self):
content = q01()
self.myAgent.sendToCoordinator("request", "TechnicalAnalysis",
content)
import os
import sys
import time
import unittest
import spade
import random
import json
import ast
from datetime import datetime
from db.Queries import q01, q03, q04, q06
HOST = "127.0.0.1"
user_stocks = q01()
empresasRiesgos = []
for stock in user_stocks:
#print stock
enterprise = stock['Empresa']
risksValues = []
lastPrice = stock['ValorActual']
enterpriseRisk = {
'Enterprise': enterprise,
'RisksValues': risksValues,
'LastPrice': lastPrice,
}
empresasRiesgos.append(enterpriseRisk)
class Risk(spade.Agent.Agent):