class Rule():
def __init__(self, market, period):
self.market = market
self.period = period
self.KLines = KLine()
self.MACD = MACD()
self.KDJ = KDJ()
self.WaveKline = WaveKline()
self.WaveMACD_DIFF = WavePoint()
self.WaveMACD_DEA = WavePoint()
self.WaveMACD_MACD = WavePoint()
self.WaveKDJ_K = WavePoint()
self.WaveKDJ_D = WavePoint()
# self.client = Client(access_key=RebotConfig.access_key, secret_key=RebotConfig.secret_key)
self.begin = 0
def Run(self, d):
# d = self.client.get(get_api_path('k'), params={'market': '{0}cny'.format(self.market), 'limit':100,'period' : '{0}'.format(self.period)});
# print time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(d[0][0]));
self.KLines.Input(d)
self.MACD.Input(self.KLines)
self.KDJ.Input(self.KLines)
self.WaveKline.Input(self.KLines)
self.WaveMACD_DIFF.Input(self.MACD.DIFF)
self.WaveMACD_DEA.Input(self.MACD.DEA)
self.WaveKDJ_K.Input(self.KDJ.K)
self.WaveKDJ_D.Input(self.KDJ.D)
klen = len(self.KLines)
self.begin = klen
# self.WaveKline.Export("C:\\Users\\randy\\k.csv");
# macd diff, dea 0 de daxiao
def Trend(self):
lmacd = len(self.MACD)
if lmacd < 2:
return Direction.FLAT
if self.MACD.DIFF[lmacd - 1] >= 0 and self.MACD.DIFF[
lmacd - 2] >= 0 and self.MACD.DEA[
lmacd - 1] >= 0 and self.MACD.DEA[lmacd - 2] >= 0:
return Direction.UP
return Direction.DOWN
def Do(self):
d = self.Trend()
kc = self.WaveKline.Get(-1)
kp = self.WaveKline.Get(-2, kc.dir)
k = self.KLines.Get(-1)
klen = len(self.KLines)
if kc.hkidx < 0 or kc.lkidx < 0 or kp == None:
return None
# print 'kc:',kc,'kp:',kp
# print kp.hk.c, kc.hk.c, kp.lk.c, kp.lk.c
if kp.hk.h <= kc.hk.h and kp.hk.c > kc.lk.c:
#
# print "\n"
# print kp.hk.c, kc.hk.c, kc.lk.c
# print 'kc:',kc,'kp:',kp
ktrend = self.WaveKline.TrendWeaken()
macdtrend = self.WaveMACD_DIFF.TrendWeaken(kc.dir)
kdjkseg = self.WaveKDJ_K.Get(-1)
#if ktrend:
# print "sell", klen-1, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)), d, ktrend, macdtrend, kdjkseg.dir
# sell
if ktrend and macdtrend and kdjkseg.dir == Direction.DOWN:
return 'sell'
if kp.lk.c > kc.lk.c and kp.lk.c < kc.hk.c:
#
ktrend = self.WaveKline.TrendWeaken()
macdtrend = self.WaveMACD_DIFF.TrendWeaken(kc.dir)
kdjkseg = self.WaveKDJ_K.Get(-1)
#if ktrend:
# print "buy", klen-1, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)), ktrend, macdtrend, kdjkseg.dir
# buy
if ktrend and macdtrend and kdjkseg.dir == Direction.UP:
return 'buy'
return None
class WVStats():
def __init__(self, ValueN=10):
self.KLines = KLine()
self.Value = []
self.Volume = []
self.ValueN = ValueN
self.status = None
self.statuscost = 0
self.statusbuycurrent = 0
self.statusdelay = 0
self.stats = []
self.High = []
self.Low = []
self.lastidx = 0
self.lastbuyidx = 0
def Export(self, path):
f = open(path, 'wb')
w = csv.writer(f)
w.writerow([
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume'
])
for k, arr in enumerate(self.stats):
d = []
for i in range(0, len(arr)):
nd = arr[i]
d.append(nd['k'].increase)
d.append(nd['k'].amplitude)
d.append(nd['k'].c)
d.append(nd['k'].vol)
d.append(nd['value'])
d.append(nd['volume'])
w.writerow(d)
f.close()
return
def Run(self, d, period=None, servertimestamp=None):
if len(d) == 0:
return
self.lastidx = self.KLines.Input(d)
MA(self.KLines.prices, self.Value, self.ValueN)
MA(self.KLines.volumes, self.Volume, self.ValueN)
HIGH(self.KLines.prices, self.High, self.ValueN * 2)
LOW(self.KLines.prices, self.Low, self.ValueN * 2)
if len(self.KLines) > self.ValueN + 1:
return self.Do()
return {
'type': None
}
def Do(self, idx=-1, ignore=False):
summ, ccount = self.KLines.Sum(12)
summb = round(summ / 5000000, 2)
avgp = self.KLines.Ref(12, 'c', -2)
prek = self.KLines.Get(idx - 1)
prevolume = self.Volume[idx - 1]
prevalue = self.Value[idx - 1]
k = self.KLines.Get(idx)
value = self.Value[idx]
volume = self.Volume[idx]
phigh = self.High[-2]
plow = self.Low[-2]
ret = {}
ret['type'] = None
ret['k'] = k
ret['sort'] = 1
ret['angle'] = 10
ret['ext'] = {'summ': summb}
statslen = len(self.stats)
for i in range(0, statslen):
nk = statslen - i - 1
arr = self.stats[nk]
if len(arr) < 5:
arr.append({
'k': k,
'value': value,
'volume': volume
})
self.stats.append([])
dv = 1
avgpp = 0
if avgp > 0:
avgpp = round((k.c - avgp) / avgp * 100, 2)
else:
print '\t\tavgp is eq 0', avgp
# print "xxxx", self.lastidx, self.statusbuycurrent, self.statusdelay, self.status;
if self.status == 'buy':
bk = self.KLines.Get(self.lastbuyidx)
dv = (self.statuscost -
self.statusbuycurrent) / self.statuscost * 2 + 1
dv = round(dv, 2)
scale = (self.statuscost - k.c) / self.statuscost > MAXBETA * dv
delay = (self.lastidx - self.statusdelay) > MAXKCOUNT * dv
# print (self.statuscost - k.c)/self.statuscost, MAXBETA * dv, dv, self.statusdelay, MAXKCOUNT * dv, prek.c > prevalue, prek.vol / (VOLTIMES * prevolume);
avgscale = (k.c - self.statusbuycurrent) / self.statuscost * 100
avgscale = round(avgscale, 2)
# delayw = avgpp < 0 or avgpp > 5 * summ / 5000000;
delayw = False
#avgpp < 0 ;# or avgscale < 5*summ/5000000;
if bk.increase * 100 > 15 * dv:
delayw = True
print 'buy k increase'.bk.increase
if scale or delayw or delay or avgscale < -7:
ret['type'] = 'sell'
ret['ext']['dv'] = dv
ret['ext']['scale'] = scale
ret['ext']['avgscale'] = avgscale
ret['ext']['delay'] = delay
ret['ext']['avgpp'] = avgpp
return ret
if self.statuscost < k.c:
self.statuscost = k.c
#if prek.vol > VOLTIMES * prevolume:
# print prek.c, prevalue, prek.c > prevalue, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(prek.t));
# if (prek.c > prevalue and prek.vol > VOLTIMES * prevolume * dv) or (k.c > value and k.vol > VOLTIMES * volume * dv): #and k.c > phigh :#and k.vol < 3.5 * volume:
closev = round((k.c - value) / value * 100, 2)
if self.lastbuyidx != self.lastidx - 1 and summb >= 1 and closev > 1 and closev <= 10 and avgpp / closev > 0.5 and avgpp <= 10 and k.vol > VOLTIMES * volume * dv and self.statusdelay != self.lastidx: #and k.c > phigh :#and k.vol < 3.5 * volume:
# if (k.c > value and k.vol > VOLTIMES * volume * dv and k.vol < 8 * VOLTIMES * volume * dv ) and self.statusdelay != self.lastidx: #and k.c > phigh :#and k.vol < 3.5 * volume:
ret['type'] = 'buy'
self.status = 'buy'
ret['ext']['close'] = closev
ret['ext']['voltimes'] = round(k.vol / volume, 2)
ret['ext']['avgpp'] = avgpp
ret['ext']['ss'] = round(avgpp / closev, 2)
if self.statusbuycurrent == 0:
self.statuscost = k.c
self.statusbuycurrent = k.c
self.statusdelay = self.lastidx
else:
self.statusdelay = self.lastidx + (self.lastidx -
self.statusdelay) / 3
self.lastbuyidx = self.lastidx - 1
return ret
return ret
def OrderResult(self, ret, orderresult):
Log.d(
'\t\torder result, self status {0}, result type {1}, order result {2}'
.format(self.status, ret['type'], orderresult))
if ret['type'] == 'sell':
if orderresult:
self.status = 'sell'
self.statuscost = 0
self.statusdelay = 0
self.statusbuycurrent = 0
class WVStats():
def __init__(self, ValueN=10):
self.KLines = KLine()
self.Value = []
self.Volume = []
self.ValueN = ValueN
self.status = None
self.statuscost = 0
self.statusbuycurrent = 0
self.statusdelay = 0
self.stats = []
self.High = []
self.Low = []
self.lastidx = 0
def Export(self, path):
f = open(path, 'wb')
w = csv.writer(f)
w.writerow([
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume',
'increase', 'amplitude', 'close', 'vol', 'value', 'volume'
])
for k, arr in enumerate(self.stats):
d = []
for i in range(0, len(arr)):
nd = arr[i]
d.append(nd['k'].increase)
d.append(nd['k'].amplitude)
d.append(nd['k'].c)
d.append(nd['k'].vol)
d.append(nd['value'])
d.append(nd['volume'])
w.writerow(d)
f.close()
return
def Run(self, d, period=None, servertimestamp=None):
if len(d) == 0:
return
self.lastidx = self.KLines.Input(d)
MA(self.KLines.prices, self.Value, self.ValueN)
MA(self.KLines.volumes, self.Volume, self.ValueN)
HIGH(self.KLines.prices, self.High, self.ValueN * 2)
LOW(self.KLines.prices, self.Low, self.ValueN * 2)
if len(self.KLines) > self.ValueN + 1:
return self.Do()
return {
'type': None
}
def Do(self, idx=-1, ignore=False):
prek = self.KLines.Get(idx - 1)
prevolume = self.Volume[idx - 1]
prevalue = self.Value[idx - 1]
k = self.KLines.Get(idx)
value = self.Value[idx]
volume = self.Volume[idx]
phigh = self.High[-2]
plow = self.Low[-2]
ret = {}
ret['type'] = None
ret['k'] = k
ret['sort'] = 1
ret['angle'] = 10
ret['ext'] = {'idx': idx}
statslen = len(self.stats)
for i in range(0, statslen):
nk = statslen - i - 1
arr = self.stats[nk]
if len(arr) < 5:
arr.append({
'k': k,
'value': value,
'volume': volume
})
self.stats.append([])
dv = 1
# print "xxxx", self.lastidx, self.statusbuycurrent, self.statusdelay, self.status;
if self.status == 'buy':
dv = (self.statuscost -
self.statusbuycurrent) / self.statuscost * 2 + 1
scale = (self.statuscost - k.c) / self.statuscost > MAXBETA * dv
delay = (self.lastidx - self.statusdelay) > MAXKCOUNT * dv
# print (self.statuscost - k.c)/self.statuscost, MAXBETA * dv, dv, self.statusdelay, MAXKCOUNT * dv, prek.c > prevalue, prek.vol / (VOLTIMES * prevolume);
if scale or delay:
ret['type'] = 'sell'
ret['ext'] = {
'idx': idx,
'dv': dv,
'scale': scale,
'delay': delay,
}
return ret
if self.statuscost < k.h:
self.statuscost = k.h
#if prek.vol > VOLTIMES * prevolume:
# print prek.c, prevalue, prek.c > prevalue, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(prek.t));
# if (prek.c > prevalue and prek.vol > VOLTIMES * prevolume * dv) or (k.c > value and k.vol > VOLTIMES * volume * dv): #and k.c > phigh :#and k.vol < 3.5 * volume:
if (
k.c > value and k.vol > VOLTIMES * volume * dv
) and self.statusdelay != self.lastidx: #and k.c > phigh :#and k.vol < 3.5 * volume:
ret['type'] = 'buy'
self.status = 'buy'
ret['ext']['close'] = (k.c - value) / value * 100
ret['ext']['voltimes'] = k.vol / volume
if self.statusbuycurrent == 0:
self.statuscost = k.c
self.statusbuycurrent = k.c
self.statusdelay = self.lastidx
else:
self.statusdelay = self.lastidx + (self.lastidx -
self.statusdelay) / 3
return ret
return ret
def OrderResult(self, ret, orderresult):
Log.d(
'\t\torder result, self status {0}, result type {1}, order result {2}'
.format(self.status, ret['type'], orderresult))
if ret['type'] == 'sell':
if orderresult:
self.status = 'sell'
self.statuscost = 0
self.statusdelay = 0
self.statusbuycurrent = 0
class MutliMovingAverage():
def __init__(self, N1=5, N2=10, N3=21, N4=42, N5=84):
self.KLines = KLine();
# price
self.MA1 = [];
self.MA2 = [];
self.MA3 = [];
self.MA4 = [];
self.MA5 = [];
self.N1 = N1;
self.N2 = N2;
self.N3 = N3;
self.N4 = N4;
self.N5 = N5;
self.status = None;
# volume
self.VMA1 = [];
self.VMA2 = [];
self.rmbvolumeN3 = 0;
# points
self.points = [[], [], []];
# wave
self.waves = [[], [], []];
# trade time
self.tradeSure = [{'buy':0, 'sell':0}, {'buy':0, 'sell':0}];
self.tradeidx= 0;
# kdj
# self.KDJ = KDJ();
# ma3 price wave point;
# self.ma3rate = [];
# self.wavepointm3 = WavePoint();
#self.wavewavepointm3 = WavePoint();
def Run(self, d, period=None, servertimestamp=None):
if period and servertimestamp:
data = d[-1];
x = servertimestamp - data[0];
if x < period:
data[5] /= x; # virtual volume
# k
self.KLines.Input(d);
# kdj
# self.KDJ.Input(self.KLines);
# price
lena = len(self.MA1);
MA(self.KLines.prices, self.MA1, self.N1);
MA(self.KLines.prices, self.MA2, self.N2);
MA(self.KLines.prices, self.MA3, self.N3);
MA(self.KLines.prices, self.MA4, self.N4);
MA(self.KLines.prices, self.MA5, self.N5);
# volume
MA(self.KLines.volumes, self.VMA1, self.N1);
MA(self.KLines.volumes, self.VMA2, self.N2);
# ma3 rate and wavepoint;
# RATE(self.MA3, self.ma3rate, self.N3);
# self.wavepointm3.InputTrend(self.ma3rate);
# self.wavewavepointm3.InputTrend(self.wavepointm3.points);
lenb = len(self.MA2);
lenc = lenb - lena;
if lenc >= 2:
for k in range(lena, lenc - 1):
self.tradeidx = k;
self.tradeSure = [{'buy':0, 'sell':0}, {'buy':0, 'sell':0}];
self.Do(k, True);
lastk = self.KLines.Get(-1);
if lastk.idx > self.tradeidx:
self.tradeSure = [{'buy':0, 'sell':0}, {'buy':0, 'sell':0}];
self.tradeidx += 1;
return self.Do();
def Export(self, path):
if len(self.MA1) < 1:
return ;
f = open(path, 'wb');
w = csv.writer(f);
w.writerow(['index', 'MA1', 'MA2', 'MA3', 'MA4']);
for k in range(0, len(self.MA1)):
w.writerow([k, self.MA1[k], self.MA2[k], self.MA3[k], self.MA4[k]]);
f.close();
def ExportWave(self, path):
if len(self.waves) < 0:
return;
f = open(path, 'wb');
wcsv = csv.writer(f);
wcsv.writerow(['index', 'type', 'point1.idx', 'point2.idx', 'wmax', 'wmin', 'wvolume', 'winterval', 'cvolume', 'cprice']);
for k in range(0, len(self.waves)):
w = self.waves[k];
wcsv.writerow([k, w.type, w.point1.idx, w.point2.idx, w.wmax, w.wmin, w.wvolume, w.winterval, w.cvolume, w.cprice]);
f.close();
def Do(self, idx=-1, ignore=False):
ret = {};
k = self.KLines.Get(idx);
type=None;
pwidx = 0;
bc43 = CROSS(self.MA4, self.MA3, idx);
if bc43:
self.tradeSure[0]['sell'] += 1;
print "\tma long n3 n4 sell time:{0}, c:{1}, k idx:{2}, sure time:{3}, ignore:{4}".format(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)), k.c, k.idx, self.tradeSure[0]['sell'], ignore)
if ignore or self.tradeSure[0]['sell'] >= RebotConfig.rebot_trade_sure_times:
self.status = 'sell';
type = 'sell';
sc34 = CROSS(self.MA3, self.MA4, idx);
if sc34:
self.tradeSure[0]['buy'] += 1;
print "\tma long n3 n4 buy time:{0}, c:{1}, k idx:{2}, sure time:{3}, ignore:{4}".format(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)), k.c, k.idx, self.tradeSure[0]['buy'], ignore)
if ignore or self.tradeSure[0]['buy'] >= RebotConfig.rebot_trade_sure_times:
self.status = 'buy'
type = 'buy';
if self.status == 'buy' and type == None and False:
type = self.KDJ.Do();
if type:
pwidx = 2;
print "kdj:{0} time:{1}, c:{2}, k idx:{3}".format(type, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)), k.c, k.idx)
if type == None:# and self.status == 'buy':
bc = CROSS(self.MA2, self.MA1, idx);
if bc:
self.tradeSure[1]['sell'] += 1;
print "\tma short n1 n2 sell time:{0}, c:{1}, k idx:{2}, sure time:{3}, ignore:{4}".format(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)), k.c, k.idx, self.tradeSure[1]['sell'], ignore)
if ignore or self.tradeSure[1]['sell'] >= RebotConfig.rebot_trade_sure_times:
type = 'sell';
pwidx = 1;
sc = CROSS(self.MA1, self.MA2, idx);
if sc:
self.tradeSure[1]['buy'] += 1;
print "\tma short n1 n2 buy time:{0}, c:{1}, k idx:{2}, sure time:{3}, ignore:{4}".format(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)), k.c, k.idx, self.tradeSure[1]['buy'], ignore)
if ignore or self.tradeSure[1]['buy'] >= RebotConfig.rebot_trade_sure_times:
type = 'buy';
pwidx = 1;
if type != None:
# frist update
points = self.points[pwidx];
waves = self.waves[pwidx];
lenwaves = len(waves);
lenpoints = len(points);
p1wave = None;
p2wave = None;
c1wave = None;
c2wave = None;
sort = 1000;
p1 = None;
p2 = None;
if lenpoints > 0:
p2 = points[-1];
if p2.idx != k.idx:
np2 = Point(type, k.idx);
if p2.type == type:
points[-1] = np2;
else:
points.append(np2);
p2 = np2;
else:
p2 = Point(type, k.idx);
points.append(p2);
lenpoints = len(points)
if lenpoints >= 2:
p1 = points[-2];
if p1 and p2:
if lenwaves > 0:
c1wave = waves[-1];
if c1wave.point2.idx == k.idx:
c1wave.cal(self.KLines);
if c1wave.type == type:
c1wave.point2 = p2;
c1wave.cal(self.KLines);
else:
ncwave = Wave(p1, p2);
ncwave.cal(self.KLines);
waves.append(ncwave);
c1wave = ncwave;
else:
c1wave = Wave(p1, p2);
c1wave.cal(self.KLines);
waves.append(c1wave);
if lenwaves >= 4 and pwidx == 1 and True:
if self.status != 'buy' and False:
type = None;
else:
c2wave = waves[-3];
p1wave = waves[-2];
p2wave = waves[-4];
if type == 'buy':
type = None;
sort = -215
if c1wave.wmin > c2wave.wmax:
sort = c2wave.height/c1wave.height + c2wave.volheight/c1wave.volheight + p2wave.height/p1wave.height + p2wave.volheight/p1wave.volheight;
# print c1wave
# print c2wave
# print 'buysort', sort, c2wave.height/c1wave.height, c2wave.volheight/c1wave.volheight, p2wave.height/p1wave.height, p2wave.volheight/p1wave.volheight, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t));
if sort < 4 :#and p2wave.height/p1wave.height <= 1:
type = 'buy';
# print '\t short ma wave buy sucess';
else:
print ' !!! wave buy sort %f, time:%s' % (sort, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)));
else:
print ' !!! wave buy c1wave wwin less c2wave wmax';
if type == 'sell':
# print '\tc1wave', c1wave
# print '\tc2wave', c2wave
if c1wave.cprice > c2wave.wmax:
type = None;
print '\t !!! wave sell fail current price greater c2wave wmax time:{0}'.format(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)));
else:
print '\t short ma wave sell sucess';
if pwidx == 0 or type == 'sell': # long long
sort = 1;
if type == 'buy' and len(self.points[0]) >= 2:
p1 = self.points[0][-1];
p2 = self.points[0][-2];
# print 'tan p1 p2', 57.2956 * math.atan( (self.MA4[p2.idx] - self.MA4[p1.idx])/self.MA4[p1.idx] * 100 /(p1.idx - p2.idx)), (self.MA4[p2.idx] - self.MA4[p1.idx])/self.MA4[p1.idx] * 100 /(p1.idx - p2.idx);
# print 'tan c p1', 57.2956 * math.atan( (self.MA4[k.idx] - self.MA4[p1.idx])/self.MA4[p1.idx] * 100/(k.idx - p1.idx)), (self.MA4[k.idx] - self.MA4[p1.idx])/self.MA4[p1.idx] * 100/(k.idx - p1.idx);
# sort = self.MA4[p.idx] / self.MA4[-1];
if self.MA4[-1] - self.MA4[p1.idx] < 0 and pwidx != 0:
sort = -sort;
if k.idx - p1.idx > 0:
ret['angle'] = 57.2956 * math.atan( (self.MA4[p2.idx] - self.MA4[p1.idx])/self.MA4[p1.idx] * 100 /(p1.idx - p2.idx)) + 57.2956 * math.atan( (self.MA4[k.idx] - self.MA4[p1.idx])/self.MA4[p1.idx] * 100/(k.idx - p1.idx))
else:
ret['angle'] = 57.2956 * math.atan( (self.MA4[p2.idx] - self.MA4[p1.idx])/self.MA4[p1.idx] * 100 /(p1.idx - p2.idx));
ret['angle'] = 10;
sort = 1;
# ma5v = self.MA5[p1.idx] - self.MA5[p2.idx];
ma5v = self.MA5[-1] - self.MA5[p2.idx]
#if ma5v < 0:
# sort = -214;
# print '\t !!! ma5 buy less 0:{0}'.format(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(k.t)));
ret['type'] = type;
ret['k'] = k;
ret['sort'] = sort;
ret['ext'] = {'idx':pwidx}
if type != None:
self.tradeSure[pwidx][type] = -RebotConfig.rebot_do_per_period;
return ret;