Python calculateMaxDD Examples

Example #1

File: TU_mom.py Project: burakbayramli/quant_at

def report(df,lookback,holddays):

    longs = df.Close > df.Close.shift(lookback)
    shorts = df.Close < df.Close.shift(lookback)
    df['pos'] = 0.
    for h in range(holddays):
       long_lag = longs.shift(h).fillna(False)
       short_lag = shorts.shift(h).fillna(False)
       df.loc[long_lag,'pos'] += 1
       df.loc[short_lag,'pos'] -= 1

    ret=(df.pos.shift(1)* (df.Close-df.Close.shift(1)) / df.Close.shift(1)) \
         / holddays

    cumret=np.cumprod(1+ret)-1

    print 'APR', ((np.prod(1.+ret))**(252./len(ret)))-1
    print 'Sharpe', np.sqrt(252.)*np.mean(ret)/np.std(ret)
    print 'Drawdown', dd.calculateMaxDD(np.array(cumret))
    return cumret

Example #2

def report(df, lookback, holddays):

    longs = df.Close > df.Close.shift(lookback)
    shorts = df.Close < df.Close.shift(lookback)
    df['pos'] = 0.
    for h in range(holddays):
        long_lag = longs.shift(h).fillna(False)
        short_lag = shorts.shift(h).fillna(False)
        df.loc[long_lag, 'pos'] += 1
        df.loc[short_lag, 'pos'] -= 1

    ret=(df.pos.shift(1)* (df.Close-df.Close.shift(1)) / df.Close.shift(1)) \
         / holddays

    cumret = np.cumprod(1 + ret) - 1

    print 'APR', ((np.prod(1. + ret))**(252. / len(ret))) - 1
    print 'Sharpe', np.sqrt(252.) * np.mean(ret) / np.std(ret)
    print 'Dusus Kaliciligi', dd.calculateMaxDD(np.array(cumret))
    return cumret

Example #3

File: gapFutures_FSTX.py Project: fccoelho/quant_at

import matplotlib.pylab as plt
import numpy as np
import pandas as pd
import dd

df = pd.read_csv('FSTX.csv')
entryZscore=0.1

stdret = pd.rolling_mean(df.cl.pct_change(), window=90).shift(1)
longs = df.op >= df.hi.shift(1)*(1+entryZscore*stdret)
shorts = df.op <= df.lo.shift(1)*(1-entryZscore*stdret)
df['pos'] = 0
df.loc[longs,'pos'] = 1
df.loc[shorts,'pos'] = -1
ret=df.pos * (df.op-df.cl) / df.op
ret = ret.dropna()
cumret=np.cumprod(1+ret)-1
print 'APR', ((np.prod(1.+ret))**(252./len(ret)))-1
print 'Sharpe', np.sqrt(252.)*np.mean(ret)/np.std(ret)
print 'Dusme Kaliciligi', dd.calculateMaxDD(np.array(cumret))

plt.plot(cumret)
#plt.show()

Example #4

import matplotlib.pylab as plt
import numpy as np
import pandas as pd
import dd

df = pd.read_csv('FSTX.csv')
entryZscore = 0.1

stdret = pd.rolling_mean(df.cl.pct_change(), window=90).shift(1)
longs = df.op >= df.hi.shift(1) * (1 + entryZscore * stdret)
shorts = df.op <= df.lo.shift(1) * (1 - entryZscore * stdret)
df['pos'] = 0
df.loc[longs, 'pos'] = 1
df.loc[shorts, 'pos'] = -1
ret = df.pos * (df.op - df.cl) / df.op
ret = ret.dropna()
cumret = np.cumprod(1 + ret) - 1
print 'APR', ((np.prod(1. + ret))**(252. / len(ret))) - 1
print 'Sharpe', np.sqrt(252.) * np.mean(ret) / np.std(ret)
print 'Drawdown', dd.calculateMaxDD(np.array(cumret))

plt.plot(cumret)
plt.show()

Example #5

File: gapFutures_FSTX.py Project: burakbayramli/quant_at

import matplotlib.pylab as plt
import numpy as np
import pandas as pd
import dd

df = pd.read_csv("FSTX.csv")
entryZscore = 0.1

stdret = pd.rolling_mean(df.cl.pct_change(), window=90).shift(1)
longs = df.op >= df.hi.shift(1) * (1 + entryZscore * stdret)
shorts = df.op <= df.lo.shift(1) * (1 - entryZscore * stdret)
df["pos"] = 0
df.loc[longs, "pos"] = 1
df.loc[shorts, "pos"] = -1
ret = df.pos * (df.op - df.cl) / df.op
ret = ret.dropna()
cumret = np.cumprod(1 + ret) - 1
print "APR", ((np.prod(1.0 + ret)) ** (252.0 / len(ret))) - 1
print "Sharpe", np.sqrt(252.0) * np.mean(ret) / np.std(ret)
print "Drawdown", dd.calculateMaxDD(np.array(cumret))

plt.plot(cumret)
plt.show()

Example #6

File: gapFutures_FSTX.py Project: suhaibccs/kod

import matplotlib.pylab as plt
import numpy as np
import pandas as pd
import dd

df = pd.read_csv('FSTX.csv')
entryZscore = 0.1

stdret = pd.rolling_mean(df.cl.pct_change(), window=90).shift(1)
longs = df.op >= df.hi.shift(1) * (1 + entryZscore * stdret)
shorts = df.op <= df.lo.shift(1) * (1 - entryZscore * stdret)
df['pos'] = 0
df.loc[longs, 'pos'] = 1
df.loc[shorts, 'pos'] = -1
ret = df.pos * (df.op - df.cl) / df.op
ret = ret.dropna()
cumret = np.cumprod(1 + ret) - 1
print 'APR', ((np.prod(1. + ret))**(252. / len(ret))) - 1
print 'Sharpe', np.sqrt(252.) * np.mean(ret) / np.std(ret)
print 'Dusme Kaliciligi', dd.calculateMaxDD(np.array(cumret))

plt.plot(cumret)
#plt.show()