def importAll():
#tables = ['XAGUSD1', 'XAGUSD5', 'XAGUSD15', 'XAGUSD30', 'XAGUSD60', 'XAGUSD240', 'XAGUSD1440', 'XAGUSD10080', 'XAGUSD43200', ]
tables = ['XAGUSD1440',]
for table in tables:
log.info('importing ' + table)
importTable(table)
log.info('done ' + table)
def sinaAgg():
# fetch price of London
f = urllib2.urlopen('http://hq.sinajs.cn/?_=1386077085140/&list=hf_XAG',
timeout=20)
html = f.read()
html = html[19:len(html) - 3]
xagArr = re.split(',', html)
price = {}
price['dt'] = datetime.datetime.strptime(xagArr[12] + ' ' + xagArr[6],
'%Y-%m-%d %H:%M:%S')
xag = float(xagArr[0])
xag0 = float(xagArr[7])
log.debug('XAG: ' + xagArr[0] + ', XAG0: ' + xagArr[2])
# fetch USD price
fusd = urllib2.urlopen(
'http://hq.sinajs.cn/rn=13860770561347070422433316708&list=USDCNY',
timeout=20)
htmlusd = fusd.read()
htmlusd = htmlusd[19:len(htmlusd) - 3]
usdArr = re.split(',', htmlusd)
usd = float(usdArr[1])
log.debug('USD: ' + usdArr[0])
# calculate price in RMB
price['p'] = round(usd * xag / 31.1035, 3)
price['p0'] = round(usd * xag0 / 31.1035, 3)
price['per'] = float(xagArr[1])
log.info('sina agg: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' +
str(price['p0']) + ', ' + str(price['per']))
return price
def sinaAgg():
# fetch price of London
f = urllib2.urlopen('http://hq.sinajs.cn/?_=1386077085140/&list=hf_XAG', timeout=20)
html = f.read()
html = html[19:len(html) - 3]
xagArr = re.split(',', html)
price = {}
price['dt'] = datetime.datetime.strptime(xagArr[12] + ' ' + xagArr[6], '%Y-%m-%d %H:%M:%S')
xag = float(xagArr[0])
xag0 = float(xagArr[7])
log.debug('XAG: ' + xagArr[0] + ', XAG0: ' + xagArr[2])
# fetch USD price
fusd = urllib2.urlopen('http://hq.sinajs.cn/rn=13860770561347070422433316708&list=USDCNY', timeout=20)
htmlusd = fusd.read()
htmlusd = htmlusd[19:len(htmlusd) - 3]
usdArr = re.split(',', htmlusd)
usd = float(usdArr[1])
log.debug('USD: ' + usdArr[0])
# calculate price in RMB
price['p'] = round(usd * xag / 31.1035, 3)
price['p0'] = round(usd * xag0 / 31.1035, 3)
price['per'] = float(xagArr[1])
log.info('sina agg: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' + str(price['p0']) + ', ' + str(price['per']))
return price
def icbcAgg():
f = urllib2.urlopen(
'http://www.icbc.com.cn/ICBCDynamicSite/Charts/GoldTendencyPicture.aspx',
timeout=20)
html = f.read()
silverRmbPattern = re.compile(
r"""人民币账户白银\s*</td>\s*<td[\s\S]+?</td>\s*<td.*?>\s*(.*?)\s*</td>
\s*<td.*?>\s*(.*?)\s*</td>\s*<td.*?>\s*(.*?)\s*</td>\s*<td.*?>\s*(.*?)\s*</td>\s*<td.*?>\s*(.*?)\s*</td>""",
re.S + re.X)
pmsSilverRmb = silverRmbPattern.search(html)
price = {}
# Date Time
price['dt'] = datetime.datetime.now()
price['p'] = float(pmsSilverRmb.group(3))
high = float(pmsSilverRmb.group(4))
low = float(pmsSilverRmb.group(5))
if high - price['p'] > price['p'] - low:
price['p0'] = high
price['per'] = round((price['p'] - high) * 100 / high, 3)
else:
price['p0'] = low
price['per'] = round((price['p'] - low) * 100 / low, 3)
log.info('icbc agg: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' +
str(price['p0']) + ', ' + str(price['per']))
return price
def process(func):
thread = threading.Thread(target=func)
thread.start()
thread.join(120)
if thread.is_alive():
log.info('* hanging thread * ')
else:
log.debug('* thread ended normally * ')
def pm25Monitor():
try:
msg = ''
msg = msg + weather.fetchPm25Forcast()
if msg:
log.info('* pm25Monitor MESSAGE * ' + msg)
sendMessage('PM2.5', msg, 2)
except:
log.exception('pm25Monitor Exception Occured!')
def importAll():
#tables = ['XAGUSD1', 'XAGUSD5', 'XAGUSD15', 'XAGUSD30', 'XAGUSD60', 'XAGUSD240', 'XAGUSD1440', 'XAGUSD10080', 'XAGUSD43200', ]
tables = [
'XAGUSD1440',
]
for table in tables:
log.info('importing ' + table)
importTable(table)
log.info('done ' + table)
def pm25Monitor():
try:
msg = ''
msg = msg + weather.fetchPm25Forcast()
if msg:
log.info('* pm25Monitor MESSAGE * ' + msg)
sendMessage('PM2.5', msg, 2)
except:
log.exception('pm25Monitor Exception Occured!')
def cleanOldData(self):
cur = self.conn.cursor()
dtLong = long(time.time()) - 48 * 60 * 60
log.info('cleaning database before: ' + str(dtLong))
cur.execute('DELETE FROM FEDATA WHERE DTLONG<=?', (dtLong,))
cur.execute('DELETE FROM NOTICE WHERE DTLONG<=?', (dtLong,))
self.conn.commit()
cur.close()
return
def marketMonitor():
# Investments
try:
msg = ''
msg = msg + prices.latestPrices()
# sending message if available
if msg:
log.info('* marketMonitor MESSAGE * ' + msg)
sendMessage('Market', msg, 1)
except:
log.exception('marketMonitor Exception Occured!')
def minuteMonitor():
# Investments
try:
msg = ''
msg = msg + prices.monitorPrice()
# sending message if available
if msg:
log.info('* minuteMonitor MESSAGE * ' + msg)
sendMessage('Prices', msg, 1)
except:
log.exception('minuteMonitor Exception Occured!')
def estimate(self, t): l = len(self.strategies) if t.equity <= self.strategies[-1][1]: return for i in range(l): if (t.equity > self.strategies[i][1]): log.info(t.strategyName + ',' + str(len(t.stats['buy']['date'])) + ',' + str(len(t.stats['sell']['date'])) + ',' + str(t.stats['downDays']) + ',' + str(t.equity)) self.strategies.insert(i, [t, t.equity]) if l + 1 > self.num: self.strategies.pop(-1) break
def send(subject, content):
msg = MIMEText(content[28:].encode('utf-8'), 'plain', 'utf-8')
msg['Subject'] = re.sub('\n', ';', content[:28])
msg['From'] = const.QQMAIL_ADDR
msg['To'] = const.QQMAIL_ADDR
qq = smtplib.SMTP('smtp.qq.com')
qq.login(const.QQMAIL_USER, const.QQMAIL_PASSWORD)
ret = qq.sendmail(msg['From'], msg['To'], msg.as_string())
qq.quit()
log.info('Sending email: ' + content + '')
def send(subject, content):
msg = MIMEText(content[28:].encode('utf-8'), 'plain', 'utf-8')
msg['Subject'] = re.sub('\n', ';', content[:28])
msg['From'] = const.QQMAIL_ADDR
msg['To'] = const.QQMAIL_ADDR
qq = smtplib.SMTP('smtp.qq.com')
qq.login(const.QQMAIL_USER, const.QQMAIL_PASSWORD)
ret = qq.sendmail(msg['From'], msg['To'], msg.as_string())
qq.quit()
log.info('Sending email: ' + content + '')
def drawStat(prices, period):
l = len(prices)
ps = [0] * l
pdts = [0] * l
std = [0] * l
stdper = [0] * l
diff = [0] * l
dmean = [0] * l
days = 0
for i in range(l):
pdts[i] = prices[i]["dt"]
ps[i] = prices[i]["close"]
diff[i] = prices[i]["high"] - prices[i]["low"]
if i < period - 1:
continue
std[i] = round(np.std(ps[i - period + 1 : i + 1], dtype=np.float64, ddof=0), 3)
stdper[i] = round(std[i] / np.mean(ps[i - period + 1 : i + 1]), 3)
dmean[i] = round(np.mean(diff[i - period + 1 : i + 1]), 3)
if (std[i - 1] < 1 and std[i] >= 1) or (std[i - 1] > 1 and std[i] <= 1):
dtstr = prices[i]["dt"].strftime("%Y-%m-%d")
log.info(dtstr + ", std change to " + str(std[i]) + ", days: " + str(days))
days = 0
days += 1
macds = macd.calc_macd(prices, 12, 26, 9)
fig = plt.figure()
ax1 = fig.add_subplot(311)
ax1.set_ylabel("Price")
ax1.grid()
ax1.plot_date(pdts, ps, color="b", linestyle="-", marker="", label="Equity")
ax2 = fig.add_subplot(312)
ax2.set_ylabel("Std")
ax2.grid()
ax2.plot_date(pdts, std, color="b", linestyle="-", marker="", label="Equity")
ax3 = fig.add_subplot(313)
ax3.set_ylabel("MACD")
ax3.grid()
ax3.plot_date(pdts, stdper, color="b", linestyle="-", marker="", label="Equity")
# multi = MultiCursor(fig.canvas, (ax1, ax2, ax3), color='r', lw=1, horizOn=False, vertOn=True)
# plt.show()
# return
fname = str(period)
plt.savefig(os.path.join(os.path.dirname(__file__), "result/" + fname + ".png"), dpi=150)
plt.close(fig)
return
def latestPrices():
msg = datetime.datetime.now().strftime('%m-%d %H:%M') + ':\n'
dtypes = ['AGG', 'AGTD', 'SHDX']
db = SqliteDB()
dtLong = long(time.time())
for dtype in dtypes:
price = db.getPrice(dtype, dtLong)
msg = msg + dtype + ':' + str(price[0]) + ',' + str(price[1]) + '%,' + str(price[2]) + ';\n'
log.info('latest prices: ' + msg)
return msg
def calc_all_macd(table, fast = 12, slow = 26, sign = 9):
log.info('MACD generating for ' + table)
db = SqliteDB().createIndicator(table, 'MACD', 'A', fast, slow, sign)
prices = SqliteDB().getAllPrices(table)
macds = calc_macd(prices, fast, slow, sign)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], macds['macd'][i], macds['sign'][i], macds['fast'][i], macds['slow'][i])
db.commit()
log.info('MACD done')
def drawStat(prices, period):
l = len(prices)
ps = [0] * l
pdts = [0] * l
std = [0] * l
stdper = [0] * l
diff = [0] * l
dmean = [0] * l
days = 0
for i in range(l):
pdts[i] = prices[i]['dt']
ps[i] = prices[i]['close']
diff[i] = prices[i]['high'] - prices[i]['low']
if i < period - 1: continue
std[i] = round(np.std(ps[i-period+1 : i+1], dtype=np.float64, ddof=0), 3)
stdper[i] = round(std[i] / np.mean(ps[i-period+1 : i+1]), 3)
dmean[i] = round(np.mean(diff[i-period+1 : i+1]), 3)
if (std[i-1] < 1 and std[i] >= 1) or (std[i-1] > 1 and std[i] <= 1):
dtstr = prices[i]['dt'].strftime('%Y-%m-%d')
log.info(dtstr + ', std change to ' + str(std[i]) + ', days: ' + str(days))
days = 0
days += 1
macds = macd.calc_macd(prices, 12, 26, 9)
fig = plt.figure()
ax1 = fig.add_subplot(311)
ax1.set_ylabel('Price')
ax1.grid()
ax1.plot_date(pdts, ps, color='b', linestyle='-', marker='', label='Equity')
ax2 = fig.add_subplot(312)
ax2.set_ylabel('Std')
ax2.grid()
ax2.plot_date(pdts, std, color='b', linestyle='-', marker='', label='Equity')
ax3 = fig.add_subplot(313)
ax3.set_ylabel('MACD')
ax3.grid()
ax3.plot_date(pdts, stdper, color='b', linestyle='-', marker='', label='Equity')
#multi = MultiCursor(fig.canvas, (ax1, ax2, ax3), color='r', lw=1, horizOn=False, vertOn=True)
#plt.show()
#return
fname = str(period)
plt.savefig(os.path.join(os.path.dirname(__file__), 'result/' + fname + '.png'), dpi=150)
plt.close(fig)
return
def calc_all_kdj(table, kPeriod = 5, dPeriod = 3, slowing =3):
log.info('KDJ generating for ' + table)
db = SqliteDB().createIndicator(table, 'KDJ', 'A', kPeriod, dPeriod, slowing)
prices = SqliteDB().getAllPrices(table)
kds = calc_kd(prices, kPeriod, dPeriod, slowing)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], kds['k'][i], kds['d'][i])
db.commit()
log.info('KDJ done')
def calc_all_rsi(table, period = 14):
log.info('RSI generating for ' + table)
db = SqliteDB().createIndicator(table, 'RSI', 'A', period)
prices = SqliteDB().getAllPrices(table)
rsis = calc_rsi(prices, period)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], rsis['rsi'][i], rsis['up'][i], rsis['down'][i])
db.commit()
log.info('RSI done')
def latestPrices():
msg = datetime.datetime.now().strftime('%m-%d %H:%M') + ':\n'
dtypes = ['AGG', 'AGTD', 'SHDX']
db = SqliteDB()
dtLong = long(time.time())
for dtype in dtypes:
price = db.getPrice(dtype, dtLong)
msg = msg + dtype + ':' + str(price[0]) + ',' + str(
price[1]) + '%,' + str(price[2]) + ';\n'
log.info('latest prices: ' + msg)
return msg
def calc_all_macd(table, fast=12, slow=26, sign=9):
log.info('MACD generating for ' + table)
db = SqliteDB().createIndicator(table, 'MACD', 'A', fast, slow, sign)
prices = SqliteDB().getAllPrices(table)
macds = calc_macd(prices, fast, slow, sign)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], macds['macd'][i], macds['sign'][i],
macds['fast'][i], macds['slow'][i])
db.commit()
log.info('MACD done')
def addData(self, table, data):
cur = self.conn.cursor()
cur.execute('SELECT DTLONG FROM ' + table + ' WHERE DTLONG=?', (long(data[0]),))
if cur.fetchone() == None:
#log.debug('inserting ' + table + ' : ')
#log.info(data)
#cur.execute('INSERT INTO PRICE(DTLONG,DDATE,DTIME,DCLOSE,DHIGH,DLOW,DOPEN,DRMB,DVOL,DINX1,DINX2,DINX3,DINX4,DINX5,DINX6,DNOTES) VALUES(?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)', data)
cur.execute('INSERT INTO ' + table + ' VALUES(?,?,?,?,?,?,?,?,?,?,?)', data)
else:
log.info('** data duplicate ** ' + table + ' : ')
log.info(data)
cur.close()
return
def calc_all_rsi(table, period=14):
log.info('RSI generating for ' + table)
db = SqliteDB().createIndicator(table, 'RSI', 'A', period)
prices = SqliteDB().getAllPrices(table)
rsis = calc_rsi(prices, period)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], rsis['rsi'][i], rsis['up'][i],
rsis['down'][i])
db.commit()
log.info('RSI done')
def calc_all_bolling(table, period=20, deviate=2):
log.info('Bolling generating for ' + table)
db = SqliteDB().createIndicator(table, 'BOLLING', 'A', period, deviate)
prices = SqliteDB().getAllPrices(table)
bollings = calc_bolling(prices, period, deviate)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], bollings['boll'][i],
bollings['mean'][i], bollings['upper'][i],
bollings['lower'][i], bollings['std'][i])
db.commit()
log.info('Bolling done')
def estimate(self, t):
l = len(self.strategies)
if t.equity <= self.strategies[-1][1]: return
for i in range(l):
if (t.equity > self.strategies[i][1]):
log.info(t.strategyName + ',' +
str(len(t.stats['buy']['date'])) + ',' +
str(len(t.stats['sell']['date'])) + ',' +
str(t.stats['downDays']) + ',' + str(t.equity))
self.strategies.insert(i, [t, t.equity])
if l + 1 > self.num:
self.strategies.pop(-1)
break
def calc_all_kdj(table, kPeriod=5, dPeriod=3, slowing=3):
log.info('KDJ generating for ' + table)
db = SqliteDB().createIndicator(table, 'KDJ', 'A', kPeriod, dPeriod,
slowing)
prices = SqliteDB().getAllPrices(table)
kds = calc_kd(prices, kPeriod, dPeriod, slowing)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], kds['k'][i], kds['d'][i])
db.commit()
log.info('KDJ done')
def calc_all_bolling(table, period = 20, deviate = 2):
log.info('Bolling generating for ' + table)
db = SqliteDB().createIndicator(table, 'BOLLING', 'A', period, deviate)
prices = SqliteDB().getAllPrices(table)
bollings = calc_bolling(prices, period, deviate)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], bollings['boll'][i], bollings['mean'][i], bollings['upper'][i], bollings['lower'][i], bollings['std'][i])
db.commit()
log.info('Bolling done')
def sinaAgTD():
# fetch price of AG T+D
f = urllib2.urlopen('http://hq.sinajs.cn/list=hf_AGTD', timeout=20)
html = f.read()
html = html[20:len(html) - 3]
agtdArr = re.split(',', html)
price = {}
price['dt'] = datetime.datetime.strptime(agtdArr[12] + ' ' + agtdArr[6], '%Y-%m-%d %H:%M:%S')
price['p'] = float(agtdArr[0])
price['p0'] = float(agtdArr[7])
price['per'] = round((price['p'] - price['p0']) * 100 / price['p0'], 3)
log.info('sina agtd: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' + str(price['p0']) + ', ' + str(price['per']))
return price
def sinaSHDX():
# fetch price of AG T+D
f = urllib2.urlopen('http://hq.sinajs.cn/rn=1386417950746&list=sh000001', timeout=20)
html = f.read()
html = html[21:len(html) - 3]
arr = re.split(',', html)
price = {}
price['dt'] = datetime.datetime.strptime(arr[30] + ' ' + arr[31], '%Y-%m-%d %H:%M:%S')
price['p'] = float(arr[3])
price['p0'] = float(arr[2])
price['per'] = round((price['p'] - price['p0']) * 100 / price['p0'], 3)
log.info('sina sh: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' + str(price['p0']) + ', ' + str(price['per']))
return price
def addIndicate(self, dtlong, val1, val2 = 0, val3 = 0, val4 = 0, val5 = 0, val6 = 0, val7 = 0, val8 = 0):
cur = self.conn.cursor()
cur.execute('SELECT DTLONG FROM ' + self.table + ' WHERE DTLONG=?', (dtlong,))
if cur.fetchone() == None:
dt = time.localtime(dtlong)
ddate = time.strftime('%Y-%m-%d', dt)
dtime = time.strftime('%H:%M:%S', dt)
#log.debug('inserting ' + self.table + ' : ' + str(val1))
#log.info(data)
cur.execute('INSERT INTO ' + self.table + ' VALUES(?,?,?,?,?,?,?,?,?,?,?)', (dtlong,ddate,dtime,val1,val2,val3,val4,val5,val6,val7,val8))
else:
log.info('** data duplicate ** ' + self.table + ' : ')
log.info(data)
#self.conn.commit()
cur.close()
return
def sinaAgTD():
# fetch price of AG T+D
f = urllib2.urlopen('http://hq.sinajs.cn/list=hf_AGTD', timeout=20)
html = f.read()
html = html[20:len(html) - 3]
agtdArr = re.split(',', html)
price = {}
price['dt'] = datetime.datetime.strptime(agtdArr[12] + ' ' + agtdArr[6],
'%Y-%m-%d %H:%M:%S')
price['p'] = float(agtdArr[0])
price['p0'] = float(agtdArr[7])
price['per'] = round((price['p'] - price['p0']) * 100 / price['p0'], 3)
log.info('sina agtd: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' +
str(price['p0']) + ', ' + str(price['per']))
return price
def sinaSHDX():
# fetch price of AG T+D
f = urllib2.urlopen('http://hq.sinajs.cn/rn=1386417950746&list=sh000001',
timeout=20)
html = f.read()
html = html[21:len(html) - 3]
arr = re.split(',', html)
price = {}
price['dt'] = datetime.datetime.strptime(arr[30] + ' ' + arr[31],
'%Y-%m-%d %H:%M:%S')
price['p'] = float(arr[3])
price['p0'] = float(arr[2])
price['per'] = round((price['p'] - price['p0']) * 100 / price['p0'], 3)
log.info('sina sh: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' +
str(price['p0']) + ', ' + str(price['per']))
return price
def analysis(self, prices):
self.buildTrend(prices)
if len(prices) <= self.days:
return
current = prices[len(prices) - self.days - 1 : len(prices)]
#log.info(current)
chour = current[len(current) - 1]['dt'].hour
cdt = current[len(current) - 1]['dt'].strftime('%Y-%m-%d %H:%M')
ct = ''
for i in range(1, len(current)):
cur = current[i]['pc']
pre = current[i - 1]['pc']
#log.info('Current ' + str(cur) + ' - ' + str(pre))
if cur < pre:
ct = ct + 'D'
else:
ct = ct + 'U'
#log.info('Current ' + ct)
for i in range(self.days, len(self.history) - self.days):
his = self.history[i - self.days : i + 1]
hhour = his[len(his) - 1]['dt'].hour
if abs(chour - hhour) > 2:
continue
ht = self.histred[i - self.days : i]
#if similar(ct, ht) < 3:
if ct[0 : self.days - self.expect] == ht[0 : self.days - self.expect]:
self.graphic(current, his)
curChange = current[len(current) - self.expect - 1]['pc'] - current[len(current) - self.days - 1]['pc']
hisChange = his[len(his) - self.expect - 1]['pc'] - his[len(his) - self.days - 1]['pc']
hdt = his[len(his) - 1]['dt'].strftime('%Y-%m-%d %H:%M')
log.info('History Date:' + hdt + ', Trend: ' + ht + ',change:' + str(hisChange))
log.info('Current Date:' + cdt + ', Trend: ' + ct + ',change:' + str(curChange))
curChange = current[len(current) - 1]['pc'] - current[len(current) - self.expect - 1]['pc']
hisChange = his[len(his) - 1]['pc'] - his[len(his) - self.expect - 1]['pc']
log.info('history:' + ht[self.days - self.expect:] + ',change:' + str(hisChange))
log.info('verify:' + ct[self.days - self.expect:] + ',change:' + str(curChange))
log.info('=========================')
def tally(ptype, price):
db = SqliteDB()
ret = ''
dLong = time.mktime(price['dt'].timetuple())
dDate = price['dt'].strftime('%Y-%m-%d')
dTime = price['dt'].strftime('%H:%M:%S')
db.addPrice((ptype, dLong, dDate, dTime, price['p'], price['per'],
price['p0'], '', dLong, dDate, dTime))
# calculate the percentage
percent0 = price['per']
# get the price of 3 minutes ago
price3 = db.getPrice(ptype, dLong - 180)
percent3 = 0
if price3:
log.debug(ptype + ',price3,' + str(price3[3]) + ',' + str(price3[0]))
price3 = price3[0]
percent3 = round((price['p'] - price3) * 100 / price3, 3)
# get the price of 30 minutes ago
price30 = db.getPrice(ptype, dLong - 1800)
percent30 = 0
if price30:
log.debug(ptype + ',price30,' + str(price30[3]) + ',' +
str(price30[0]))
price30 = price30[0]
percent30 = round((price['p'] - price30) * 100 / price30, 3)
# get last message information
notper0 = db.getNotice(ptype, 0, dDate)
log.info(ptype + ', percentage 0: ' + str(percent0) + ', last notice: ' +
str(notper0))
#print notper0
if abs(percent0 - notper0) >= 1:
ret = ptype + '0,' + str(price['p']) + ',' + str(percent0) + '%;\n'
db.addNotice(
(ptype, 0, dLong, dDate, dTime, price['p'], percent0, ret, ''))
notcount30 = db.getNoticeCount(ptype, 30, dLong - 1800)
log.info(ptype + ', percentage 30: ' + str(percent30) +
', notice in 30 minutes: ' + str(notcount30))
if notcount30 == 0 and abs(percent30) >= 1:
ret = ret + ptype + '30,' + str(
price['p']) + ',' + str(percent30) + '%;\n'
db.addNotice(
(ptype, 30, dLong, dDate, dTime, price['p'], percent30, ret, ''))
notcount3 = db.getNoticeCount(ptype, 3, dLong - 180)
log.info(ptype + ', percentage 3: ' + str(percent3) +
', notice in 3 minutes: ' + str(notcount3))
if notcount3 == 0 and abs(percent3) >= 0.5:
ret = ret + ptype + '3,' + str(
price['p']) + ',' + str(percent3) + '%;\n'
db.addNotice(
(ptype, 3, dLong, dDate, dTime, price['p'], percent3, ret, ''))
return ret
def calc_all_ma(table, matype, period, weight=0):
log.info('MA generating ' + matype + ' for ' + table)
db = SqliteDB().createIndicator(table, 'MA', matype, period, weight)
prices = SqliteDB().getAllPrices(table)
ps = [p['close'] for p in prices]
if matype == 'MA':
mas = calc_ma(ps, period)
elif matype == 'EMA':
mas = calc_ema(ps, period)
elif matype == 'SMA':
mas = calc_sma(ps, period)
elif matype == 'LWMA':
mas = calc_lwma(ps, period)
for i in range(len(prices)):
db.addIndicate(prices[i]['dtlong'], mas[i])
db.commit()
log.info('MA done')
return mas
def calc_all_ma(table, matype, period, weight=0):
log.info("MA generating " + matype + " for " + table)
db = SqliteDB().createIndicator(table, "MA", matype, period, weight)
prices = SqliteDB().getAllPrices(table)
ps = [p["close"] for p in prices]
if matype == "MA":
mas = calc_ma(ps, period)
elif matype == "EMA":
mas = calc_ema(ps, period)
elif matype == "SMA":
mas = calc_sma(ps, period)
elif matype == "LWMA":
mas = calc_lwma(ps, period)
for i in range(len(prices)):
db.addIndicate(prices[i]["dtlong"], mas[i])
db.commit()
log.info("MA done")
return mas
def icbcAgg():
f = urllib2.urlopen('http://www.icbc.com.cn/ICBCDynamicSite/Charts/GoldTendencyPicture.aspx', timeout=20)
html = f.read()
silverRmbPattern = re.compile(r"""人民币账户白银\s*</td>\s*<td[\s\S]+?</td>\s*<td.*?>\s*(.*?)\s*</td>
\s*<td.*?>\s*(.*?)\s*</td>\s*<td.*?>\s*(.*?)\s*</td>\s*<td.*?>\s*(.*?)\s*</td>\s*<td.*?>\s*(.*?)\s*</td>""", re.S + re.X)
pmsSilverRmb = silverRmbPattern.search(html)
price = {}
# Date Time
price['dt'] = datetime.datetime.now()
price['p'] = float(pmsSilverRmb.group(3))
high = float(pmsSilverRmb.group(4))
low = float(pmsSilverRmb.group(5))
if high - price['p'] > price['p'] - low:
price['p0'] = high
price['per'] = round((price['p'] - high) * 100 / high, 3)
else:
price['p0'] = low
price['per'] = round((price['p'] - low) * 100 / low, 3)
log.info('icbc agg: ' + str(price['dt']) + ', ' + str(price['p']) + ', ' + str(price['p0']) + ', ' + str(price['per']))
return price
def createIndicator(self, dtype, itype, subtype, arg1 = 0, arg2 = 0, arg3 = 0, arg4 = 0, arg5 = 0):
self.table = dtype + '_' + itype + '_' + subtype + '_' + str(arg1) + '_' + str(arg2) + '_' + str(arg3) + '_' + str(arg4) + '_' + str(arg5)
log.info('create table ' + self.table)
cur = self.conn.cursor()
cur.execute('''
CREATE TABLE IF NOT EXISTS ''' + self.table + '''
(
DTLONG INTEGER PRIMARY KEY,
DDATE TEXT,
DTIME TEXT,
VAL1 REAL,
VAL2 REAL,
VAL3 REAL,
VAL4 REAL,
VAL5 REAL,
VAL6 REAL,
VAL7 REAL,
VAL8 REAL
)
''')
cur.execute('DELETE FROM ' + self.table)
self.conn.commit()
cur.close()
return self
def tally(ptype, price):
db = SqliteDB()
ret = ''
dLong = time.mktime(price['dt'].timetuple())
dDate = price['dt'].strftime('%Y-%m-%d')
dTime = price['dt'].strftime('%H:%M:%S')
db.addPrice((ptype, dLong, dDate, dTime, price['p'], price['per'], price['p0'], '', dLong, dDate, dTime))
# calculate the percentage
percent0 = price['per']
# get the price of 3 minutes ago
price3 = db.getPrice(ptype, dLong - 180)
percent3 = 0
if price3:
log.debug(ptype + ',price3,' + str(price3[3]) + ',' + str(price3[0]))
price3 = price3[0]
percent3 = round((price['p'] - price3) * 100 / price3, 3)
# get the price of 30 minutes ago
price30 = db.getPrice(ptype, dLong - 1800)
percent30 = 0
if price30:
log.debug(ptype + ',price30,' + str(price30[3]) + ',' + str(price30[0]))
price30 = price30[0]
percent30 = round((price['p'] - price30) * 100 / price30, 3)
# get last message information
notper0 = db.getNotice(ptype, 0, dDate)
log.info(ptype + ', percentage 0: ' + str(percent0) + ', last notice: ' + str(notper0))
#print notper0
if abs(percent0 - notper0) >= 1:
ret = ptype + '0,' + str(price['p']) + ',' + str(percent0) + '%;\n'
db.addNotice((ptype, 0, dLong, dDate, dTime, price['p'], percent0, ret, ''))
notcount30 = db.getNoticeCount(ptype, 30, dLong - 1800)
log.info(ptype + ', percentage 30: ' + str(percent30) + ', notice in 30 minutes: ' + str(notcount30))
if notcount30 == 0 and abs(percent30) >= 1:
ret = ret + ptype + '30,' + str(price['p']) + ',' + str(percent30) + '%;\n'
db.addNotice((ptype, 30, dLong, dDate, dTime, price['p'], percent30, ret, ''))
notcount3 = db.getNoticeCount(ptype, 3, dLong - 180)
log.info(ptype + ', percentage 3: ' + str(percent3) + ', notice in 3 minutes: ' + str(notcount3))
if notcount3 == 0 and abs(percent3) >= 0.5:
ret = ret + ptype + '3,' + str(price['p']) + ',' + str(percent3) + '%;\n'
db.addNotice((ptype, 3, dLong, dDate, dTime, price['p'], percent3, ret, ''))
return ret
def sendMultiSms(multimsg):
try:
phone = PyFetion.PyFetion(const.FETION_USER, const.FETION_PASSWORD, 'TCP', debug=True)
if phone.login(PyFetion.FetionOnline):
log.info('Fetion login success!')
for msgs in multimsg:
msg = msgs[0]
for receiver in msgs[1]:
phone.send_sms(msg.encode('utf-8'), receiver, True)
log.info('SMS sent! receiver ' + receiver + 'Sending ' + msg + '')
phone.logout()
return True
else:
log.info('Fetion login failed, message not send! receivers: ' + receivers + ', msg: ' + msg)
return False
except:
log.exception('SMS sent failed!')
return False
def drawStat(prices, period):
l = len(prices)
print l
ps = [p['close'] for p in prices]
print slope(ps)
ps = np.array(ps)
#ts = [p['dtlong'] - prices[0]['dtlong'] for p in prices]
#ts = np.array(ts)
ts = np.arange(l)
z = np.polyfit(ts[0:300], ps[0:300], 1)
zp = np.poly1d(z)
print z
z30 = np.polyfit(ts[0:290], ps[0:290], 10)
zp30 = np.poly1d(z30)
print z30
plt.plot(ts, ps, '-', ts, zp(ts), '-', ts, zp30(ts), '--')
#plt.plot(ts, ps, 'o', label='Original data', linestyle='-', markersize=2)
#plt.plot(ts, m * ts + c, 'r', label='Fitted line')
#plt.legend()
plt.show()
return
l = len(prices)
ps = [0] * l
pdts = [0] * l
std = [0] * l
stdper = [0] * l
diff = [0] * l
dmean = [0] * l
days = 0
for i in range(l):
pdts[i] = prices[i]['dt']
ps[i] = prices[i]['close']
diff[i] = prices[i]['high'] - prices[i]['low']
if i < period - 1: continue
std[i] = round(
np.std(ps[i - period + 1:i + 1], dtype=np.float64, ddof=0), 3)
stdper[i] = round(std[i] / np.mean(ps[i - period + 1:i + 1]), 3)
dmean[i] = round(np.mean(diff[i - period + 1:i + 1]), 3)
if (std[i - 1] < 1 and std[i] >= 1) or (std[i - 1] > 1
and std[i] <= 1):
dtstr = prices[i]['dt'].strftime('%Y-%m-%d')
log.info(dtstr + ', std change to ' + str(std[i]) + ', days: ' +
str(days))
days = 0
days += 1
macds = macd.calc_macd(prices, 12, 26, 9)
fig = plt.figure()
ax1 = fig.add_subplot(311)
ax1.set_ylabel('Price')
ax1.grid()
ax1.plot_date(pdts,
ps,
color='b',
linestyle='-',
marker='',
label='Equity')
ax2 = fig.add_subplot(312)
ax2.set_ylabel('Std')
ax2.grid()
ax2.plot_date(pdts,
std,
color='b',
linestyle='-',
marker='',
label='Equity')
ax3 = fig.add_subplot(313)
ax3.set_ylabel('MACD')
ax3.grid()
ax3.plot_date(pdts,
stdper,
color='b',
linestyle='-',
marker='',
label='Equity')
multi = MultiCursor(fig.canvas, (ax1, ax2, ax3),
color='r',
lw=1,
horizOn=False,
vertOn=True)
plt.show()
return
fname = str(period)
plt.savefig(os.path.join(os.path.dirname(__file__),
'result/' + fname + '.png'),
dpi=150)
plt.close(fig)
return
def runStrategy(in_prices):
global mas, emas, smas, lwmas, std, prices
log.debug('beginning one strategy ...')
prices = in_prices
ps = [p['close'] for p in prices]
std = [0] * 51
l = len(prices)
for period in range(20, 21):
std[period] = [0] * l
for i in range(period - 1, l):
std[period][i] = round(np.std(ps[i-period+1 : i+1], dtype=np.float64, ddof=0), 3)
mas = [0] * 181
emas = [0] * 181
smas = [0] * 181
lwmas = [0] * 181
for period in range(2, 181):
mas[period] = ma.calc_ma(ps, period)
emas[period] = ma.calc_ema(ps, period)
smas[period] = ma.calc_sma(ps, period)
lwmas[period] = ma.calc_lwma(ps, period)
#pool = StrategyPool(100)
#t = doTrade(pool, 20, 0.1, 0.2, 'SMA', 20, 'SMA', 34, 'LWMA', 40, 'SMA', 20, 'SMA', 34, 'LWMA', 120)
#pool.showStrategies()
#return
log.debug('running first strategy ...')
starttime = time.time()
matypes = ['MA', 'EMA', 'SMA', 'LWMA']
#farr = [2, 3, 4, 5, 6, 7, ]
#s1arr = [4, 6, 8, 10, 12, 14, 16, 18, 20, ]
#s2arr = [0, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51, ]
#farr = [20,]
#s1arr = [40, ]
#s2arr = [0, ]
farr = range(40, 41)[::3]
s1arr = range(4, 121)[::6]
s2arr = range(0, 181)[::15]
stdGuage1, stdGuage2 = 0.1, 0.2
pool = StrategyPool(50)
poola = StrategyPool(10)
poolb = StrategyPool(10)
for stdPeriod in [20, ]:
for no in ['A', 'B', ]:
for ft, f in [(matype, period) for matype in matypes for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes for period in s1arr]:
if s1 < f: continue
elapsed = long(time.time() - starttime)
log.debug('== ' + str(elapsed) + ',' + ft + '_' + str(f) + ',' + s1t + '_' + str(s1) + ' ==')
for s2t, s2 in [(matype, period) for matype in matypes for period in s2arr]:
if s2 != 0 and s2 <= s1: continue
if s2 == 0 and (s2t == 'EMA' or s2t == 'SMA' or s2t == 'LWMA'): continue
if no == 'A':
doTrade(poola, stdPeriod, stdGuage1, stdGuage2, ft, f, s1t, s1, s2t, s2, '', 0, '', 0, '', 0)
elif no == 'B':
doTrade(poolb, stdPeriod, stdGuage1, stdGuage2, '', 0, '', 0, '', 0, ft, f, s1t, s1, s2t, s2)
elapsed = long(time.time() - starttime)
log.info('find ' + no + ' time: ' + str(elapsed) + ' ')
for i in range(10):
sa = poola.strategies[i]
sb = poolb.strategies[i]
t = doTrade(pool, stdPeriod, stdGuage1, stdGuage2, sa[0].args[0], sa[0].args[1], sa[0].args[2], sa[0].args[3], sa[0].args[4], sa[0].args[5], sb[0].args[6], sb[0].args[7], sb[0].args[8], sb[0].args[9], sb[0].args[10], sb[0].args[11])
#t.generateGraph()
pool.showStrategies()
def drawStat(prices, period):
l = len(prices)
ps = [0] * l
pdts = [0] * l
std = [0] * l
stdper = [0] * l
diff = [0] * l
dmean = [0] * l
days = 0
for i in range(l):
pdts[i] = prices[i]['dt']
ps[i] = prices[i]['close']
diff[i] = prices[i]['high'] - prices[i]['low']
if i < period - 1: continue
std[i] = round(
np.std(ps[i - period + 1:i + 1], dtype=np.float64, ddof=0), 3)
stdper[i] = round(std[i] / np.mean(ps[i - period + 1:i + 1]), 3)
dmean[i] = round(np.mean(diff[i - period + 1:i + 1]), 3)
if (std[i - 1] < 1 and std[i] >= 1) or (std[i - 1] > 1
and std[i] <= 1):
dtstr = prices[i]['dt'].strftime('%Y-%m-%d')
log.info(dtstr + ', std change to ' + str(std[i]) + ', days: ' +
str(days))
days = 0
days += 1
macds = macd.calc_macd(prices, 12, 26, 9)
fig = plt.figure()
ax1 = fig.add_subplot(311)
ax1.set_ylabel('Price')
ax1.grid()
ax1.plot_date(pdts,
ps,
color='b',
linestyle='-',
marker='',
label='Equity')
ax2 = fig.add_subplot(312)
ax2.set_ylabel('Std')
ax2.grid()
ax2.plot_date(pdts,
std,
color='b',
linestyle='-',
marker='',
label='Equity')
ax3 = fig.add_subplot(313)
ax3.set_ylabel('MACD')
ax3.grid()
ax3.plot_date(pdts,
stdper,
color='b',
linestyle='-',
marker='',
label='Equity')
#multi = MultiCursor(fig.canvas, (ax1, ax2, ax3), color='r', lw=1, horizOn=False, vertOn=True)
#plt.show()
#return
fname = str(period)
plt.savefig(os.path.join(os.path.dirname(__file__),
'result/' + fname + '.png'),
dpi=150)
plt.close(fig)
return
def runStrategy(in_prices):
global mas, emas, smas, std, prices
log.debug('beginning first strategy ...')
prices = in_prices
ps = [p['close'] for p in prices]
std = [0] * 51
l = len(prices)
for period in range(2, 51):
std[period] = [0] * l
for i in range(period - 1, l):
std[period][i] = round(np.std(ps[i-period+1 : i+1], dtype=np.float64, ddof=0), 3)
mas = [0] * 61
emas = [0] * 61
smas = [0] * 61
for period in range(2, 61):
mas[period] = ma.calc_ma(ps, period)
emas[period] = ma.calc_ema(ps, period)
smas[period] = ma.calc_sma(ps, period)
pool = StrategyPool(100)
#t = doTrade(pool, 25, 1.0, 'MA', 7, 'SMA', 12, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
t = doTrade(pool, 25, 1.3, 'MA', 7, 'SMA', 13, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.0, 'MA', 7, 'SMA', 13, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.0, 'MA', 7, 'SMA', 12, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#
#t = doTrade(pool, 25, 1.1, 'MA', 7, 'SMA', 12, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.1, 'MA', 7, 'SMA', 13, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.1, 'MA', 7, 'SMA', 13, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.1, 'MA', 7, 'SMA', 12, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#
#t = doTrade(pool, 25, 1.2, 'MA', 7, 'SMA', 12, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.2, 'MA', 7, 'SMA', 13, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.2, 'MA', 7, 'SMA', 13, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.2, 'MA', 7, 'SMA', 12, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#
#t = doTrade(pool, 25, 1.3, 'MA', 7, 'SMA', 12, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.3, 'MA', 7, 'SMA', 13, 'EMA', 31, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.3, 'MA', 7, 'SMA', 13, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.3, 'MA', 7, 'SMA', 12, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 13)
#t = doTrade(pool, 25, 1.0, 'MA', 7, 'SMA', 13, 'EMA', 26, 'SMA', 7, 'MA', 12, 'MA', 12)
pool.showStrategies()
return
log.debug('running first strategy ...')
starttime = datetime.datetime.now()
matypes = ['MA', 'EMA', 'SMA']
#farr = [2, 3, 4, 5, 6, 7, ]
#s1arr = [4, 6, 8, 10, 12, 14, 16, 18, 20, ]
#s2arr = [0, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51, ]
farr = [2,]
s1arr = [4, ]
s2arr = [0, ]
pool = StrategyPool(100)
for stdPeriod in [20, ]:
stdGuage = 0.5
for stdGuage in [1.3, ]:
maxAEquity = maxBEquity = 0
poola = StrategyPool(5)
poolb = StrategyPool(5)
for ft, f in [(matype, period) for matype in matypes for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes for period in s1arr]:
elapsed = (datetime.datetime.now() - starttime).seconds
log.debug('== ' + str(elapsed) + ',' + ft + '_' + str(f) + ',' + s1t + '_' + str(s1) + ' ==')
for s2t, s2 in [(matype, period) for matype in matypes for period in s2arr]:
if s2 != 0 and s2 < s1: continue
if s2 == 0 and (s2t == 'EMA' or s2t == 'SMA'): continue
t = doTrade(poola, stdPeriod, stdGuage, ft, f, s1t, s1, s2t, s2, '', 0, '', 0, '', 0)
if t.equity > maxAEquity:
maxAEquity = t.equity
maxEAs = [ft, f, s1t, s1, s2t, s2]
elapsed = (datetime.datetime.now() - starttime).seconds
log.info('find A time: ' + str(elapsed) + ' ')
#poola.showStrategies()
for ft, f in [(matype, period) for matype in matypes for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes for period in s1arr]:
elapsed = (datetime.datetime.now() - starttime).seconds
log.debug('== ' + str(elapsed) + ',' + ft + '_' + str(f) + ',' + s1t + '_' + str(s1) + ' ==')
for s2t, s2 in [(matype, period) for matype in matypes for period in s2arr]:
if s2 != 0 and s2 < s1: continue
if s2 == 0 and (s2t == 'EMA' or s2t == 'SMA'): continue
t = doTrade(poolb, stdPeriod, stdGuage, '', 0, '', 0, '', 0, ft, f, s1t, s1, s2t, s2)
if t.equity > maxBEquity:
maxBEquity = t.equity
maxEBs = [ft, f, s1t, s1, s2t, s2]
elapsed = (datetime.datetime.now() - starttime).seconds
log.info('find B time: ' + str(elapsed) + ' ')
#poolb.showStrategies()
logb.info(str(stdPeriod) + ',' + str(stdGuage) + ',' + str(maxAEquity) + ',' + str(maxBEquity))
logb.info(str(maxEAs))
logb.info(str(maxEBs))
for i in range(5):
sa = poola.strategies[i]
sb = poolb.strategies[i]
t = doTrade(pool, stdPeriod, stdGuage, sa[0].args[2], sa[0].args[3], sa[0].args[4], sa[0].args[5], sa[0].args[6], sa[0].args[7], sb[0].args[8], sb[0].args[9], sb[0].args[10], sb[0].args[11], sb[0].args[12], sb[0].args[13])
t.generateGraph()
#pool.estimate(t)
#stdGuage += 0.1
pool.showStrategies()
db.cleanOldData()
except:
log.exception('dayMonitor Exception Occured!')
def process(func):
thread = threading.Thread(target=func)
thread.start()
thread.join(120)
if thread.is_alive():
log.info('* hanging thread * ')
else:
log.debug('* thread ended normally * ')
if __name__ == "__main__":
sched = Scheduler(standalone=True)
#sched.add_cron_job(process, args=[minuteMonitor], day_of_week='mon', hour='7-23', minute='*')
#sched.add_cron_job(process, args=[minuteMonitor], day_of_week='tue-fri', second='0,30')
#sched.add_cron_job(process, args=[minuteMonitor], day_of_week='sat', hour='0-3', minute='*')
sched.add_cron_job(process, args=[weatherMonitor], hour='7', minute='30')
sched.add_cron_job(process,
args=[weatherMonitor],
hour='17,21',
minute='0')
sched.add_cron_job(process, args=[pm25Monitor], hour='19', minute='0')
#sched.add_cron_job(process, args=[marketMonitor], day_of_week='mon-fri', hour='11,15,21', minute='15')
#sched.add_cron_job(process, args=[batchMonitor], hour='1', minute='0')
log.info('Monitor starting...')
sched.start()
def drawStat(prices, period):
l = len(prices)
print l
ps = [p['close'] for p in prices]
print slope(ps)
ps = np.array(ps)
#ts = [p['dtlong'] - prices[0]['dtlong'] for p in prices]
#ts = np.array(ts)
ts = np.arange(l)
z = np.polyfit(ts[0:300], ps[0:300], 1)
zp = np.poly1d(z)
print z
z30 = np.polyfit(ts[0:290], ps[0:290], 10)
zp30 = np.poly1d(z30)
print z30
plt.plot(ts, ps, '-', ts, zp(ts), '-', ts, zp30(ts), '--')
#plt.plot(ts, ps, 'o', label='Original data', linestyle='-', markersize=2)
#plt.plot(ts, m * ts + c, 'r', label='Fitted line')
#plt.legend()
plt.show()
return
l = len(prices)
ps = [0] * l
pdts = [0] * l
std = [0] * l
stdper = [0] * l
diff = [0] * l
dmean = [0] * l
days = 0
for i in range(l):
pdts[i] = prices[i]['dt']
ps[i] = prices[i]['close']
diff[i] = prices[i]['high'] - prices[i]['low']
if i < period - 1: continue
std[i] = round(np.std(ps[i-period+1 : i+1], dtype=np.float64, ddof=0), 3)
stdper[i] = round(std[i] / np.mean(ps[i-period+1 : i+1]), 3)
dmean[i] = round(np.mean(diff[i-period+1 : i+1]), 3)
if (std[i-1] < 1 and std[i] >= 1) or (std[i-1] > 1 and std[i] <= 1):
dtstr = prices[i]['dt'].strftime('%Y-%m-%d')
log.info(dtstr + ', std change to ' + str(std[i]) + ', days: ' + str(days))
days = 0
days += 1
macds = macd.calc_macd(prices, 12, 26, 9)
fig = plt.figure()
ax1 = fig.add_subplot(311)
ax1.set_ylabel('Price')
ax1.grid()
ax1.plot_date(pdts, ps, color='b', linestyle='-', marker='', label='Equity')
ax2 = fig.add_subplot(312)
ax2.set_ylabel('Std')
ax2.grid()
ax2.plot_date(pdts, std, color='b', linestyle='-', marker='', label='Equity')
ax3 = fig.add_subplot(313)
ax3.set_ylabel('MACD')
ax3.grid()
ax3.plot_date(pdts, stdper, color='b', linestyle='-', marker='', label='Equity')
multi = MultiCursor(fig.canvas, (ax1, ax2, ax3), color='r', lw=1, horizOn=False, vertOn=True)
plt.show()
return
fname = str(period)
plt.savefig(os.path.join(os.path.dirname(__file__), 'result/' + fname + '.png'), dpi=150)
plt.close(fig)
return
def runStrategy_0(in_prices):
global mas, emas, smas, std, prices
log.debug("beginning first strategy ...")
prices = in_prices
ps = [p["close"] for p in prices]
std = [0] * 51
l = len(prices)
for period in range(2, 51):
std[period] = [0] * l
for i in range(period - 1, l):
std[period][i] = round(np.std(ps[i - period + 1 : i + 1], dtype=np.float64, ddof=0), 3)
mas = [0] * 61
emas = [0] * 61
smas = [0] * 61
for period in range(2, 61):
mas[period] = ma.calc_ma(ps, period)
emas[period] = ma.calc_ema(ps, period)
smas[period] = ma.calc_sma(ps, period)
log.debug("running first strategy ...")
starttime = datetime.datetime.now()
matypes = ["MA", "EMA", "SMA"]
farr = [2, 3, 4, 5, 6, 7]
s1arr = [4, 6, 8, 10, 12, 14, 16, 18, 20]
s2arr = [0, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51]
pool = StrategyPool(100)
for stdPeriod in [20, 30, 40]:
stdGuage = 1.0
while stdGuage <= 1.3:
maxAEquity = maxBEquity = 0
poola = StrategyPool(5)
poolb = StrategyPool(5)
for ft, f in [(matype, period) for matype in matypes for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes for period in s1arr]:
elapsed = (datetime.datetime.now() - starttime).seconds
log.debug("== " + str(elapsed) + "," + ft + "_" + str(f) + "," + s1t + "_" + str(s1) + " ==")
for s2t, s2 in [(matype, period) for matype in matypes for period in s2arr]:
if s2 != 0 and s2 < s1:
continue
if s2 == 0 and (s2t == "EMA" or s2t == "SMA"):
continue
t = doTrade(poola, stdPeriod, stdGuage, ft, f, s1t, s1, s2t, s2, "", 0, "", 0, "", 0)
if t.equity > maxAEquity:
maxAEquity = t.equity
maxEAs = [ft, f, s1t, s1, s2t, s2]
elapsed = (datetime.datetime.now() - starttime).seconds
log.info("find A time: " + str(elapsed) + " ")
poola.showStrategies()
for ft, f in [(matype, period) for matype in matypes for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes for period in s1arr]:
elapsed = (datetime.datetime.now() - starttime).seconds
log.debug("== " + str(elapsed) + "," + ft + "_" + str(f) + "," + s1t + "_" + str(s1) + " ==")
for s2t, s2 in [(matype, period) for matype in matypes for period in s2arr]:
if s2 != 0 and s2 < s1:
continue
if s2 == 0 and (s2t == "EMA" or s2t == "SMA"):
continue
t = doTrade(poolb, stdPeriod, stdGuage, "", 0, "", 0, "", 0, ft, f, s1t, s1, s2t, s2)
if t.equity > maxBEquity:
maxBEquity = t.equity
maxEBs = [ft, f, s1t, s1, s2t, s2]
elapsed = (datetime.datetime.now() - starttime).seconds
log.info("find B time: " + str(elapsed) + " ")
poolb.showStrategies()
logb.info(str(stdPeriod) + "," + str(stdGuage) + "," + str(maxAEquity) + "," + str(maxBEquity))
logb.info(str(maxEAs))
logb.info(str(maxEBs))
for i in range(5):
sa = poola.strategies[i]
sb = poolb.strategies[i]
t = doTrade(
pool,
stdPeriod,
stdGuage,
sa[0].args[2],
sa[0].args[3],
sa[0].args[4],
sa[0].args[5],
sa[0].args[6],
sa[0].args[7],
sb[0].args[8],
sb[0].args[9],
sb[0].args[10],
sb[0].args[11],
sb[0].args[12],
sb[0].args[13],
)
t.generateGraph()
pool.estimate(t)
stdGuage += 0.1
pool.showStrategies()
def runStrategy(in_prices):
global mas, emas, smas, lwmas, std, prices
log.debug('beginning one strategy ...')
prices = in_prices
ps = [p['close'] for p in prices]
std = [0] * 51
l = len(prices)
for period in range(5, 41):
std[period] = [0] * l
for i in range(period - 1, l):
std[period][i] = round(
np.std(ps[i - period + 1:i + 1], dtype=np.float64, ddof=0), 3)
mas = [0] * 181
emas = [0] * 181
smas = [0] * 181
lwmas = [0] * 181
for period in range(2, 181):
mas[period] = ma.calc_ma(ps, period)
emas[period] = ma.calc_ema(ps, period)
smas[period] = ma.calc_sma(ps, period)
lwmas[period] = ma.calc_lwma(ps, period)
#pool = StrategyPool(100)
#t = doTrade(pool, 20, 0.1, 0.2, 'SMA', 20, 'SMA', 34, 'LWMA', 40, 'SMA', 20, 'SMA', 34, 'LWMA', 120, 'MA', 20, 'SMA', 34, 'LWMA', 120)
#pool.showStrategies()
#return
log.debug('running first strategy ...')
starttime = time.time()
matypes = ['MA', 'EMA', 'SMA', 'LWMA']
#farr = [2, 3, 4, 5, 6, 7, ]
#s1arr = [4, 6, 8, 10, 12, 14, 16, 18, 20, ]
#s2arr = [0, 6, 9, 12, 15, 18, 21, 24, 27, 30, 33, 36, 39, 42, 45, 48, 51, ]
#farr = [20,]
#s1arr = [40, ]
#s2arr = [0, ]
farr = range(40, 41)[::3]
s1arr = range(4, 121)[::6]
s2arr = range(0, 181)[::15]
stdGuage1, stdGuage2 = 0.1, 0.2
pool = StrategyPool(50)
poola = StrategyPool(10)
poolb = StrategyPool(10)
poolc = StrategyPool(10)
for stdPeriod in [
20,
]:
for no in ['A', 'B', 'C']:
for ft, f in [(matype, period) for matype in matypes
for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes
for period in s1arr]:
if s1 < f: continue
elapsed = long(time.time() - starttime)
log.debug('== ' + str(elapsed) + ',' + ft + '_' + str(f) +
',' + s1t + '_' + str(s1) + ' ==')
for s2t, s2 in [(matype, period) for matype in matypes
for period in s2arr]:
if s2 != 0 and s2 <= s1: continue
if s2 == 0 and (s2t == 'EMA' or s2t == 'SMA'
or s2t == 'LWMA'):
continue
if no == 'A':
doTrade(poola, stdPeriod, stdGuage1, stdGuage2, ft,
f, s1t, s1, s2t, s2, '', 0, '', 0, '', 0,
'', 0, '', 0, '', 0)
elif no == 'B':
doTrade(poolb, stdPeriod, stdGuage1, stdGuage2, '',
0, '', 0, '', 0, ft, f, s1t, s1, s2t, s2,
'', 0, '', 0, '', 0)
elif no == 'C':
doTrade(poolc, stdPeriod, stdGuage1, stdGuage2, '',
0, '', 0, '', 0, '', 0, '', 0, '', 0, ft,
f, s1t, s1, s2t, s2)
elapsed = long(time.time() - starttime)
log.info('find ' + no + ' time: ' + str(elapsed) + ' ')
for i in range(10):
sa = poola.strategies[i]
sb = poolb.strategies[i]
sc = poolc.strategies[i]
t = doTrade(pool, stdPeriod, stdGuage1, stdGuage2, sa[0].args[0],
sa[0].args[1], sa[0].args[2], sa[0].args[3],
sa[0].args[4], sa[0].args[5], sb[0].args[6],
sb[0].args[7], sb[0].args[8], sb[0].args[9],
sb[0].args[10], sb[0].args[11], sc[0].args[12],
sc[0].args[13], sc[0].args[14], sc[0].args[15],
sc[0].args[16], sc[0].args[17])
#t.generateGraph()
pool.showStrategies()
def runStrategy_0(in_prices):
global mas, emas, smas, std, prices
log.debug('beginning first strategy ...')
prices = in_prices
ps = [p['close'] for p in prices]
std = [0] * 51
l = len(prices)
for period in range(2, 51):
std[period] = [0] * l
for i in range(period - 1, l):
std[period][i] = round(
np.std(ps[i - period + 1:i + 1], dtype=np.float64, ddof=0), 3)
mas = [0] * 61
emas = [0] * 61
smas = [0] * 61
for period in range(2, 61):
mas[period] = ma.calc_ma(ps, period)
emas[period] = ma.calc_ema(ps, period)
smas[period] = ma.calc_sma(ps, period)
log.debug('running first strategy ...')
starttime = datetime.datetime.now()
matypes = ['MA', 'EMA', 'SMA']
farr = [
2,
3,
4,
5,
6,
7,
]
s1arr = [
4,
6,
8,
10,
12,
14,
16,
18,
20,
]
s2arr = [
0,
6,
9,
12,
15,
18,
21,
24,
27,
30,
33,
36,
39,
42,
45,
48,
51,
]
pool = StrategyPool(100)
for stdPeriod in [20, 30, 40]:
stdGuage = 1.0
while stdGuage <= 1.3:
maxAEquity = maxBEquity = 0
poola = StrategyPool(5)
poolb = StrategyPool(5)
for ft, f in [(matype, period) for matype in matypes
for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes
for period in s1arr]:
elapsed = (datetime.datetime.now() - starttime).seconds
log.debug('== ' + str(elapsed) + ',' + ft + '_' + str(f) +
',' + s1t + '_' + str(s1) + ' ==')
for s2t, s2 in [(matype, period) for matype in matypes
for period in s2arr]:
if s2 != 0 and s2 < s1: continue
if s2 == 0 and (s2t == 'EMA' or s2t == 'SMA'): continue
t = doTrade(poola, stdPeriod, stdGuage, ft, f, s1t, s1,
s2t, s2, '', 0, '', 0, '', 0)
if t.equity > maxAEquity:
maxAEquity = t.equity
maxEAs = [ft, f, s1t, s1, s2t, s2]
elapsed = (datetime.datetime.now() - starttime).seconds
log.info('find A time: ' + str(elapsed) + ' ')
poola.showStrategies()
for ft, f in [(matype, period) for matype in matypes
for period in farr]:
for s1t, s1 in [(matype, period) for matype in matypes
for period in s1arr]:
elapsed = (datetime.datetime.now() - starttime).seconds
log.debug('== ' + str(elapsed) + ',' + ft + '_' + str(f) +
',' + s1t + '_' + str(s1) + ' ==')
for s2t, s2 in [(matype, period) for matype in matypes
for period in s2arr]:
if s2 != 0 and s2 < s1: continue
if s2 == 0 and (s2t == 'EMA' or s2t == 'SMA'): continue
t = doTrade(poolb, stdPeriod, stdGuage, '', 0, '', 0,
'', 0, ft, f, s1t, s1, s2t, s2)
if t.equity > maxBEquity:
maxBEquity = t.equity
maxEBs = [ft, f, s1t, s1, s2t, s2]
elapsed = (datetime.datetime.now() - starttime).seconds
log.info('find B time: ' + str(elapsed) + ' ')
poolb.showStrategies()
logb.info(
str(stdPeriod) + ',' + str(stdGuage) + ',' + str(maxAEquity) +
',' + str(maxBEquity))
logb.info(str(maxEAs))
logb.info(str(maxEBs))
for i in range(5):
sa = poola.strategies[i]
sb = poolb.strategies[i]
t = doTrade(pool, stdPeriod, stdGuage, sa[0].args[2],
sa[0].args[3], sa[0].args[4], sa[0].args[5],
sa[0].args[6], sa[0].args[7], sb[0].args[8],
sb[0].args[9], sb[0].args[10], sb[0].args[11],
sb[0].args[12], sb[0].args[13])
t.generateGraph()
pool.estimate(t)
stdGuage += 0.1
pool.showStrategies()
