def inform(self, df):
# print("Calculating Strategy for " + str(self.tickerName) + " at " + str(timeStamp) + "...")
### TO-DO: Develop strategies to calculate
##
## Inform Analyser to do the interval Analysis first
## This is before the pseudotrades to ensure no clashes
self.analyser.intervalAnalysis(df.head(1))
#1. Calculate ATR for potential trade
atr = atrcalc.ATRcalc(df)
indi = ind.Indicator()
Results = indi.beginCalc(df, self.tickerName, atr)
for i in Results:
if Results[i] != 0:
self.analyser.PseudoTrade(df, i, Results[i], atr)
### for testing
# self.analyser.PseudoTrade(df,i, Results[i], atr)
###
### END TO-DO
# print("Calculated Strategy for " + str(self.tickerName) + " at " + str(timeStamp))
self.comparator.compare(Results, atr)
def macdTRIX(self, df, pattern, patterntype):
df = df.dropna()
#1. Calculate ATR for potential trade
atr = atrcalc.ATRcalc(df)
##b. MACD
macdInput = df.head(34)
macdInput = macdInput.iloc[::-1]
MACDclose = macdInput['close'].values
macd, macdsignal, macdhist = MACDFIX(MACDclose, signalperiod=9)
# print("MACD\n", macd[-1])
# print("Signal\n", macdsignal[-1])
##c. DelayedMACD
delayedmacdInput = df.iloc[1:].head(34)
delayedmacdInput = delayedmacdInput.iloc[::-1]
delayedMACDclose = delayedmacdInput['close'].values
delayedmacd, delayedmacdsignal, delayedmacdhist = MACDFIX(
delayedMACDclose, signalperiod=9)
trixInput = df.head(60)
trixInput = df.iloc[::-1]
trixOutput = TRIX(trixInput['close'].values, timeperiod=20)
# print("EMA\n", ema[-1])
##d. current price action
priceaction = df.head(1)
pricehigh = priceaction['high'].values[0]
pricelow = priceaction['low'].values[0]
priceclose = priceaction['close'].values[0]
# print("pricehigh\n", pricehigh)
# print("pricelow\n", pricelow)
if delayedmacd[-1] < delayedmacdsignal[-1] and macd[-1] > macdsignal[
-1] and trixOutput[-1] < 0:
position = 1
elif delayedmacd[-1] > delayedmacdsignal[-1] and macd[-1] < macdsignal[
-1] and trixOutput[-1] > 0:
position = -1
else:
position = 0
amount = 50
if position == 1:
stoploss = priceclose - 1.05 * atr
takeprofit = priceclose + 1.45 * atr
# amount = priceclose / (priceclose - stoploss)
if (priceclose - stoploss) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
elif position == -1:
stoploss = priceclose + 1.05 * atr
takeprofit = priceclose - 1.45 * atr
# amount = priceclose / (stoploss - priceclose)
if (stoploss - priceclose) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
else:
stoploss = 0
takeprofit = 0
amount = 0
##For test
# position = 1
if position * pattern > 0:
confidence = abs(pattern)
elif position * pattern < 0:
confidence = abs(1 / pattern)
elif position == 0:
confidence = 0
else:
confidence = 1
# ##FOR TEST
# position = 1
return [position, amount, priceclose, stoploss, takeprofit, confidence]
def trix200(self, df, pattern, patterntype):
df = df.dropna()
#1. Calculate ATR for potential trade
atr = atrcalc.ATRcalc(df)
trixInput = df.head(60)
trixInput = trixInput.iloc[::-1]
trixOutput = TRIX(trixInput['close'].values, timeperiod=14)
##c. 200EMA
emaInput = df.head(200)
emaInput = emaInput.iloc[::-1]
EMAclose = emaInput['close'].values
ema = EMA(EMAclose, timeperiod=200)
# print("EMA\n", ema[-1])
##d. current price action
priceaction = df.head(1)
pricehigh = priceaction['high'].values[0]
pricelow = priceaction['low'].values[0]
priceclose = priceaction['close'].values[0]
# print("pricehigh\n", pricehigh)
# print("pricelow\n", pricelow)
if trixOutput[-2] < 0 and trixOutput[-1] > 0:
crossover = 1
elif trixOutput[-2] > 0 and trixOutput[-1] < 0:
crossover = -1
else:
crossover = 0
if pricelow > ema[-1]: marketEMA = 1
elif pricehigh < ema[-1]: marketEMA = -1
else: marketEMA = 0
##OUTPUT
if marketEMA == 1 and crossover > 0: position = 1
elif marketEMA == -1 and crossover < 0: position = -1
else: position = 0
amount = 50
if position == 1:
stoploss = priceclose - 1.05 * atr
takeprofit = priceclose + 1.45 * atr
# amount = priceclose / (priceclose - stoploss)
if (priceclose - stoploss) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
elif position == -1:
stoploss = priceclose + 1.05 * atr
takeprofit = priceclose - 1.45 * atr
# amount = priceclose / (stoploss - priceclose)
if (stoploss - priceclose) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
else:
stoploss = 0
takeprofit = 0
amount = 0
if position * pattern > 0:
confidence = abs(pattern)
elif position * pattern < 0:
confidence = abs(1 / pattern)
elif position == 0:
confidence = 0
else:
confidence = 1
# ##FOR TEST
# position = 1
return [position, amount, priceclose, stoploss, takeprofit, confidence]
def macd200(self, df, pattern, patterntype):
#1. Calculate ATR for potential trade
atr = atrcalc.ATRcalc(df)
#####PLACEHOLDER
# df = pd.read_csv('./database/AAPL.csv')
#####END_PLACEHOLDER
df = df.dropna()
###1. Getting Parameters
##b. MACD
macdInput = df.head(34)
macdInput = macdInput.iloc[::-1]
MACDclose = macdInput['close'].values
macd, macdsignal, macdhist = MACDFIX(MACDclose, signalperiod=9)
# print("MACD\n", macd[-1])
# print("Signal\n", macdsignal[-1])
##c. DelayedMACD
delayedmacdInput = df.iloc[1:].head(34)
delayedmacdInput = delayedmacdInput.iloc[::-1]
delayedMACDclose = delayedmacdInput['close'].values
delayedmacd, delayedmacdsignal, delayedmacdhist = MACDFIX(
delayedMACDclose, signalperiod=9)
##c. 200EMA
emaInput = df.head(200)
emaInput = emaInput.iloc[::-1]
EMAclose = emaInput['close'].values
ema = EMA(EMAclose, timeperiod=200)
# print("EMA\n", ema[-1])
##d. current price action
priceaction = df.head(1)
pricehigh = priceaction['high'].values[0]
pricelow = priceaction['low'].values[0]
priceclose = priceaction['close'].values[0]
# print("pricehigh\n", pricehigh)
# print("pricelow\n", pricelow)
###2. Analysing using the data provided
##macd-signal crossover type
## -1 means negative crossover
## 1 means positive crossover
## 0 means both
if delayedmacd[-1] < delayedmacdsignal[-1] and macd[-1] > macdsignal[
-1]:
crossover = 1
elif delayedmacd[-1] > delayedmacdsignal[-1] and macd[-1] < macdsignal[
-1]:
crossover = -1
else:
crossover = 0
##market-ema type
## 1 means low > 200EMA
## -1 means high < 200EMA
## 0 means otherwise
if pricelow > ema[-1]: marketEMA = 1
elif pricehigh < ema[-1]: marketEMA = -1
else: marketEMA = 0
##OUTPUT
if marketEMA == 1 and crossover > 0 and macd[-1] < 0: position = 1
elif marketEMA == -1 and crossover < 0 and macd[-1] > 0: position = -1
else: position = 0
amount = 50
if position == 1:
stoploss = priceclose - 1.05 * atr
takeprofit = priceclose + 1.45 * atr
# amount = priceclose / (priceclose - stoploss)
if (priceclose - stoploss) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
elif position == -1:
stoploss = priceclose + 1.05 * atr
takeprofit = priceclose - 1.45 * atr
# amount = priceclose / (stoploss - priceclose)
if (stoploss - priceclose) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
else:
stoploss = 0
takeprofit = 0
amount = 0
##For test
# position = 1
if position * pattern > 0:
confidence = abs(pattern)
elif position * pattern < 0:
confidence = abs(1 / pattern)
elif position == 0:
confidence = 0
else:
confidence = 1
# ##FOR TEST
# position = 1
return [position, amount, priceclose, stoploss, takeprofit, confidence]
def SMA200(self, df, pattern, patterntype):
df = df.dropna()
###1. Getting Parameters
##a. current price action
priceaction = df.head(1)
pricehigh = priceaction['high'].values[0]
pricelow = priceaction['low'].values[0]
priceclose = priceaction['close'].values[0]
##b. previous price action
prevaction = df.iloc[1:].head(1)
prevhigh = prevaction['high'].values[0]
prevlow = prevaction['low'].values[0]
prevclose = prevaction['close'].values[0]
##d. current SMAs
smaCurrentInput = df.head(20)
sma20Current = SMA(smaCurrentInput['close'].values, timeperiod=20)
smaCurrentInput = smaCurrentInput.head(10)
sma10Current = SMA(smaCurrentInput['close'].values, timeperiod=10)
##e. previous SMAs
smaPreviousInput = df.iloc[1:].head(20)
sma20Previous = SMA(smaPreviousInput['close'].values, timeperiod=20)
smaPreviousInput = smaPreviousInput.head(10)
sma10Previous = SMA(smaPreviousInput['close'].values, timeperiod=10)
##f. 200EMA
emaInput = df.head(200)
emaInput = emaInput.iloc[::-1]
EMAclose = emaInput['close'].values
ema = EMA(EMAclose, timeperiod=200)
##trade conditions
if sma10Previous[-1] < sma20Previous[-1] and sma10Current[
-1] > sma20Current[-1]:
crossover = 1
elif sma10Previous[-1] > sma20Previous[-1] and sma10Current[
-1] < sma20Current[-1]:
crossover = -1
else:
crossover = 0
## 200EMA filtering false signal
if pricelow > ema[-1]: marketEMA = 1
elif pricehigh < ema[-1]: marketEMA = -1
else: marketEMA = 0
if crossover == 1 and marketEMA == 1:
position = 1
elif crossover == -1 and marketEMA == -1:
position = -1
else:
position = 0
atr = atrcalc.ATRcalc(df)
amount = 50
if position == 1:
stoploss = priceclose - 1.05 * atr
takeprofit = priceclose + 1.45 * atr
# amount = priceclose / (priceclose - stoploss)
if (priceclose - stoploss) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
elif position == -1:
stoploss = priceclose + 1.05 * atr
takeprofit = priceclose - 1.45 * atr
# amount = priceclose / (stoploss - priceclose)
if (stoploss - priceclose) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
else:
stoploss = 0
takeprofit = 0
amount = 0
if position * pattern > 0:
confidence = abs(pattern)
elif position * pattern < 0:
confidence = abs(1 / pattern)
elif position == 0:
confidence = 0
else:
confidence = 1
# ##FOR TEST
# position = 1
return [position, amount, priceclose, stoploss, takeprofit, confidence]
def bbands200(self, df, pattern, patterntype):
df = df.dropna()
#1. Calculate ATR for potential trade
atr = atrcalc.ATRcalc(df)
##b. get BBands
bband = df.head(21)
bband = bband.iloc[1:]
bband = bband.iloc[::-1]
bbandInput = bband['close'].values
upperband, middleband, lowerband = BBANDS(bbandInput,
timeperiod=20,
nbdevup=2,
nbdevdn=2,
matype=0)
##c. 200EMA
emaInput = df.head(200)
emaInput = emaInput.iloc[::-1]
EMAclose = emaInput['close'].values
ema = EMA(EMAclose, timeperiod=200)
##d. current price action
priceaction = df.head(1)
pricehigh = priceaction['high'].values[0]
pricelow = priceaction['low'].values[0]
priceclose = priceaction['close'].values[0]
if pricehigh > upperband[-1]: breakBand = -1
elif pricelow < lowerband[-1]: breakBand = 1
else: breakBand = 0
if pricelow > ema[-1]: marketEMA = 1
elif pricehigh < ema[-1]: marketEMA = -1
else: marketEMA = 0
##OUTPUT
if marketEMA == 1 and pattern > 0 and patterntype == -1 and breakBand == 1:
position = 1
elif marketEMA == -1 and pattern < 0 and patterntype == -1 and breakBand == -1:
position = -1
else:
position = 0
amount = 50
if position == 1:
stoploss = priceclose - 1.05 * atr
takeprofit = priceclose + 1.45 * atr
# amount = priceclose / (priceclose - stoploss)
if (stoploss - priceclose) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
elif position == -1:
stoploss = priceclose + 1.05 * atr
takeprofit = priceclose - 1.45 * atr
# amount = priceclose / (stoploss - priceclose)
if (stoploss - priceclose) * amount < 0.1:
position = 0
amount = 0
stoploss = 0
takeprofit = 0
else:
stoploss = 0
takeprofit = 0
amount = 0
if position * pattern > 0:
confidence = abs(pattern)
elif position * pattern < 0:
confidence = abs(1 / pattern)
elif position == 0:
confidence = 0
else:
confidence = 1
# ##FOR TEST
# position = 1
return [position, amount, priceclose, stoploss, takeprofit, confidence]
import pandas as pd
from talib import MACDFIX, RSI, EMA, SAR, SMA, TRIX, BBANDS, CDLIDENTICAL3CROWS, CDL3BLACKCROWS, CDL3WHITESOLDIERS, CDLMORNINGSTAR, CDLEVENINGSTAR, CDL3LINESTRIKE, CDLMORNINGDOJISTAR, CDLEVENINGDOJISTAR, CDL3OUTSIDE, CDLENGULFING, CDLBELTHOLD, CDLABANDONEDBABY, CDL3INSIDE, CDLPIERCING, CDLDARKCLOUDCOVER, CDLBREAKAWAY, CDLXSIDEGAP3METHODS, CDLHAMMER, CDLSHOOTINGSTAR
import indicators.ATRcalc as atrcalc
import os
#1. Calculate ATR for potential trade
#####PLACEHOLDER
df = pd.read_csv('./database/AAPL/temp2.csv')
#####END_PLACEHOLDER
#1. Calculate ATR for potential trade
#####PLACEHOLDER
# df = pd.read_csv('./database/AAPL.csv')
#####END_PLACEHOLDER
df = df.dropna()
#1. Calculate ATR for potential trade
atr = atrcalc.ATRcalc(df)
## a. checkpatterns
cdlInput = df.head(20)
cdlInput = cdlInput.iloc[::-1]
aa = cdlInput['open'].values
ab = cdlInput['high'].values
ac = cdlInput['low'].values
ad = cdlInput['close'].values
outputI3C = CDLIDENTICAL3CROWS(aa, ab, ac, ad)
output3BC = CDL3BLACKCROWS(aa, ab, ac, ad)
output3WS = CDL3WHITESOLDIERS(aa, ab, ac, ad)
outputMS = CDLMORNINGSTAR(aa, ab, ac, ad)
outputES = CDLEVENINGSTAR(aa, ab, ac, ad)
output3LS = CDL3LINESTRIKE(aa, ab, ac, ad)
outputMDS = CDLMORNINGDOJISTAR(aa, ab, ac, ad)