def doTrade(pool, prices, ps, fast, slow, rsiPeriod, rsiGuage): sname = 'L2_' + str(fast) + '_' + str(slow) + '_' + str(rsiPeriod) + '_' + str(rsiGuage) macds = macd.calc_macd(prices, fast, slow, 7) rsis = rsi.calc_rsi(prices, rsiPeriod) front = max(fast, slow, rsiPeriod) t = Trader(sname) direct = odirect = 0 for i in range(front, len(prices)): #print macds['macd'][i], rsis['rsi'][i], odirect , direct price = prices[i] if macds['macd'][i] > 0 and rsis['rsi'][i] > rsiGuage: direct = 1 elif macds['macd'][i] < 0 and rsis['rsi'][i] < rsiGuage: direct = -1 volume = 0 if odirect == -1 and direct == 1: volume = 1 elif odirect == 1 and direct == -1: volume = -1 odirect = direct t.processOrder(price['dt'], price['rmb'], volume * 1000, cntNo=0, notes='') pool.estimate(t) return
def doMacdTrade(pool, prices, ps, fast, slow, sign): global highest, openLevel, closeLevel sname = 'MACD_' + str(fast) + '_' + str(slow) + '_' + str(sign) macds = macd.calc_macd(prices, fast, slow, sign) mas = ma.calc_ema(ps, slow) t = Trader(sname) for i in range(slow + sign, len(prices)): if macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and macds['macd'][i-1] < macds['sign'][i-1] and abs(macds['macd'][i]) > openLevel and mas[i] > mas[i-1]: notes = 'macd under 0, and abs larger than openlevel' t.buy(prices[i]['date'], prices[i]['time'], prices[i]['rmb'], notes) if macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and macds['macd'][i-1] < macds['sign'][i-1] and abs(macds['macd'][i]) > closeLevel and mas[i] > mas[i-1]: notes = 'macd under 0, and abs larger than closelevel' t.buy(prices[i]['date'], prices[i]['time'], prices[i]['rmb'], notes, True) if macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and macds['macd'][i-1] > macds['sign'][i-1] and abs(macds['macd'][i]) > openLevel and mas[i] < mas[i-1]: notes = 'macd above 0, and abs larger than openlevel' t.sell(prices[i]['date'], prices[i]['time'], prices[i]['rmb'], notes) if macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and macds['macd'][i-1] > macds['sign'][i-1] and abs(macds['macd'][i]) > closeLevel and mas[i] < mas[i-1]: notes = 'macd above 0, and abs larger than closeLevel' t.sell(prices[i]['date'], prices[i]['time'], prices[i]['rmb'], notes, True) t.show(prices[i]['date'], prices[i]['time'], prices[i]['rmb']) pool.estimate(t) return
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 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 genMacdOps(prices, fast, slow, sign):
openLevel, closeLevel = 0.2, 0.1
macds = macd.calc_macd(prices, fast, slow, sign)
front = slow + sign
l = len(prices)
ops = [0] * l
for i in range(front, l):
if macds['sign'][i] > 0.1 and macds['macd'][i] > macds['sign'][i]:
ops[i] = 1
elif macds['macd'][i] > 0.1 and macds['macd'][i] < macds['sign'][i]:
ops[i] = -1
if macds['sign'][i] < -0.1 and macds['macd'][i] < macds['sign'][i]:
ops[i] = -1
elif macds['macd'][i] < -0.1 and macds['macd'][i] > macds['sign'][i]:
ops[i] = 1
return ops
def genMacdOps(prices, fast, slow, sign): openLevel, closeLevel = 0.2, 0.1 macds = macd.calc_macd(prices, fast, slow, sign) front = slow + sign l = len(prices) ops = [0] * l for i in range(front, l): if macds['sign'][i] > 0.1 and macds['macd'][i] > macds['sign'][i]: ops[i] = 1 elif macds['macd'][i] > 0.1 and macds['macd'][i] < macds['sign'][i]: ops[i] = -1 if macds['sign'][i] < -0.1 and macds['macd'][i] < macds['sign'][i]: ops[i] = -1 elif macds['macd'][i] < -0.1 and macds['macd'][i] > macds['sign'][i]: ops[i] = 1 return ops
def genMacdOps2(prices, fast, slow, sign): openLevel, closeLevel = 0.2, 0.1 macds = macd.calc_macd(prices, fast, slow, sign) front = slow + sign l = len(prices) ops = [0] * l for i in range(front, l): if macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and abs(macds['macd'][i]) > openLevel: ops[i] = 1 elif ops[i-1] == -1 and macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and abs(macds['macd'][i]) > closeLevel: ops[i] = 0 elif macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and abs(macds['macd'][i]) > openLevel: ops[i] = -1 elif ops[i-1] == 1 and macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and abs(macds['macd'][i]) > closeLevel: ops[i] = 0 else: ops[i] = ops[i-1] return ops
def genMacdOps2(prices, fast, slow, sign): openLevel, closeLevel = 0.2, 0.1 macds = macd.calc_macd(prices, fast, slow, sign) front = slow + sign l = len(prices) ops = [0] * l for i in range(front, l): if macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and abs(macds['macd'][i]) > openLevel: ops[i] = 1 elif ops[i-1] == -1 and macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and abs(macds['macd'][i]) > closeLevel: ops[i] = 0 elif macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and abs(macds['macd'][i]) > openLevel: ops[i] = -1 elif ops[i-1] == 1 and macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and abs(macds['macd'][i]) > closeLevel: ops[i] = 0 else: ops[i] = ops[i-1] return ops
def calcTickets(pool, prices, fast, slow, sign): vname = 'MACD_' + str(fast) + '_' + str(slow) + '_' + str(sign) macds = macd.calc_macd(prices, fast, slow, sign) front = slow + sign l = len(prices) ops = [0] * l for i in range(front, l): if macds['sign'][i] > 0.1 and macds['macd'][i] > macds['sign'][i]: ops[i] = 1 elif macds['macd'][i] > 0.1 and macds['macd'][i] < macds['sign'][i]: ops[i] = -1 if macds['sign'][i] < -0.1 and macds['macd'][i] < macds['sign'][i]: ops[i] = -1 elif macds['macd'][i] < -0.1 and macds['macd'][i] > macds['sign'][i]: ops[i] = 1 pool.estimate(vname, ops, front)
def calcTickets2(pool, prices, fast, slow, sign): vname = 'MACD_' + str(fast) + '_' + str(slow) + '_' + str(sign) macds = macd.calc_macd(prices, fast, slow, sign) front = slow + sign l = len(prices) ops = [0] * l for i in range(front, l): if macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and abs(macds['macd'][i]) > openLevel: ops[i] = 1 elif ops[i-1] == -1 and macds['macd'][i] < 0 and macds['macd'][i] > macds['sign'][i] and abs(macds['macd'][i]) > closeLevel: ops[i] = 0 elif macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and abs(macds['macd'][i]) > openLevel: ops[i] = -1 elif ops[i-1] == 1 and macds['macd'][i] > 0 and macds['macd'][i] < macds['sign'][i] and abs(macds['macd'][i]) > closeLevel: ops[i] = 0 else: ops[i] = ops[i-1] pool.estimate(vname, ops, front)
def doTrade(pool, prices, ps, fast, slow, rsiPeriod, rsiGuage):
sname = 'L2_' + str(fast) + '_' + str(slow) + '_' + str(
rsiPeriod) + '_' + str(rsiGuage)
macds = macd.calc_macd(prices, fast, slow, 7)
rsis = rsi.calc_rsi(prices, rsiPeriod)
front = max(fast, slow, rsiPeriod)
t = Trader(sname)
direct = odirect = 0
for i in range(front, len(prices)):
#print macds['macd'][i], rsis['rsi'][i], odirect , direct
price = prices[i]
if macds['macd'][i] > 0 and rsis['rsi'][i] > rsiGuage:
direct = 1
elif macds['macd'][i] < 0 and rsis['rsi'][i] < rsiGuage:
direct = -1
volume = 0
if odirect == -1 and direct == 1:
volume = 1
elif odirect == 1 and direct == -1:
volume = -1
odirect = direct
t.processOrder(price['dt'],
price['rmb'],
volume * 1000,
cntNo=0,
notes='')
pool.estimate(t)
return
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 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 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