def test_bollinger_bands(self, window_length, k, mask_sid):
closes = self.closes(mask_sid)
result = self.run_graph(
TermGraph({
'f': BollingerBands(
window_length=window_length,
k=k,
),
}),
initial_workspace={
USEquityPricing.close: AdjustedArray(
closes,
np.full_like(closes, True, dtype=bool),
{},
np.nan,
),
},
mask_sid=mask_sid,
)['f']
expected_upper, expected_middle, expected_lower = self.expected(
window_length,
k,
closes,
)
assert_equal(result.upper, expected_upper)
assert_equal(result.middle, expected_middle)
assert_equal(result.lower, expected_lower)
def test_bollinger_bands(self, window_length, k, mask_last_sid):
closes = self.closes(mask_last_sid=mask_last_sid)
mask = ~np.isnan(closes)
bbands = BollingerBands(window_length=window_length, k=k)
expected = self.expected_bbands(window_length, k, closes)
self.check_terms(
terms={
'upper': bbands.upper,
'middle': bbands.middle,
'lower': bbands.lower,
},
expected={
'upper': expected[0],
'middle': expected[1],
'lower': expected[2],
},
initial_workspace={
USEquityPricing.close: AdjustedArray(
data=closes,
mask=mask,
adjustments={},
missing_value=np.nan,
),
},
mask=self.build_mask(mask),
)
def make_pipeline():
all_assets_filter = (USEquityPricing.close.latest > 0)
returns_5 = Returns(window_length=5)
rsi = RSI(inputs=[USEquityPricing.close])
macd = MovingAverageConvergenceDivergenceSignal(mask=all_assets_filter)
ema = ExponentialWeightedMovingAverage(mask=all_assets_filter,
inputs=[USEquityPricing.close],
window_length=30,
decay_rate=(1 - (2.0 / (1 + 15.0))))
mean_5 = SimpleMovingAverage(inputs=[USEquityPricing.close],
window_length=5,
mask=all_assets_filter)
mean_10 = SimpleMovingAverage(inputs=[USEquityPricing.close],
window_length=10,
mask=all_assets_filter)
bb = BollingerBands(inputs=[USEquityPricing.close], window_length=20, k=2)
return Pipeline(
columns={
'returns_5': returns_5,
'RSI': rsi,
'MACD': macd,
'EMA': ema,
'SMA_5': mean_5,
'SMA_10': mean_10,
'bb_upper': bb.upper,
'bb_middle': bb.middle,
'bb_lower': bb.lower
},
screen=all_assets_filter,
)
def make_pipeline():
"""
Create our pipeline.
"""
# Base universe set to the Q1500US.
base_universe = AverageDollarVolume(window_length=20).percentile_between(70, 100)
latest_close = USEquityPricing.close.latest
# 14-day RSI
rsi_14 = RSI(
inputs=[USEquityPricing.close],
window_length=14,
mask=base_universe
)
# 20-day, 2 standard deviation Bollinger bands
bbLow, bbMid, bbHigh = BollingerBands(
inputs=[USEquityPricing.close],
window_length=10,
k=2,
mask=base_universe
)
rsiOverbought = rsi_14 > 70
rsiOversold = rsi_14 < 30
bbOverbought = latest_close > bbHigh
bbOversold = latest_close < bbLow
overbought = rsiOverbought | bbOverbought
oversold = rsiOversold | bbOversold
# Filter to select securities to short.
shorts = overbought
# Filter to select securities to long.
longs = oversold
# Filter for all securities that we want to trade.
securities_to_trade = (shorts & longs)
return Pipeline(
columns={
'longs': longs,
'shorts': shorts
},
screen=(securities_to_trade),
)
def test_bollinger_bands_output_ordering(self):
bbands = BollingerBands(window_length=5, k=2)
lower, middle, upper = bbands
self.assertIs(lower, bbands.lower)
self.assertIs(middle, bbands.middle)
self.assertIs(upper, bbands.upper)
def test_bollinger_bands_output_ordering(self):
bbands = BollingerBands(window_length=5, k=2)
lower, middle, upper = bbands
assert lower is bbands.lower
assert middle is bbands.middle
assert upper is bbands.upper
def make_pipeline(underly_sid, shortable_sid):#,DAY_HACK_ENABLED=True,BB_WIN_LEN=126,WIN_LEN=20):
sid = SidFactor()
pipeline_underly_sid = sid.eq(underly_sid[0])
print("jzzz:", type(pipeline_underly_sid))
print("MNAME:", MNAME)
for i in underly_sid:
pipeline_underly_sid = pipeline_underly_sid | sid.eq(i)
print('jzzz:', pipeline_underly_sid)
pipeline_shortable_sid = sid.eq(shortable_sid[0])
for i in shortable_sid:
pipeline_shortable_sid = pipeline_shortable_sid | sid.eq(i)
#Filter for our choice of assets.
bbands = BollingerBands(window_length=BB_WIN_LEN, k=sqrt(BB_WIN_LEN/5),mask = pipeline_underly_sid)
lower, middle, upper = bbands
#cud = Cud()#mask(pipeline underly_sid)
returns_1D = Returns(window_length = 2, mask = pipeline_underly_sid)
returns_6M = Returns(window_length = WIN_LEN, mask = pipeline_underly_sid)
returns_6M = returns_6M if DAY_HACK_ENABLED else returns_6M - returns_1D
returns_3M = Returns(window_length = 60, mask = pipeline_underly_sid)
returns_3M = returns_3M if DAY_HACK_ENABLED else returns_3M - returns_1D
returns_5M = Returns(window_length = WIN_LEN, mask = pipeline_underly_sid)#for es only
returns_5M = returns_5M if DAY_HACK_ENABLED else returns_5M - returns_1D
returns_1M = Returns(window_length = 20, mask = pipeline_underly_sid)#for es only
returns_1M = returns_1M if DAY_HACK_ENABLED else returns_1M - returns_1D
returns_5D = Returns(window_length =W_WIN_LEN,mask = pipeline_underly_sid)
returns_5D = returns_5D if DAY_HACK_ENABLED else returns_5D - returns_1D
returns_6D = Returns(window_length =7,mask = pipeline_underly_sid) - returns_1D
annualizedVolatility_6M = AnnualizedVolatility(window_length = WIN_LEN,mask = pipeline_underly_sid)
annualizedVolatility_3M = AnnualizedVolatility(window_length = int(WIN_LEN/2), mask = pipeline_underly_sid)
annualizedVolatility_1M = AnnualizedVolatility(window_length = int(WIN_LEN/6), mask = pipeline_underly_sid)
#annualizedVolatility_6M = ComputeVol6M(mask = pipeline_underly_sid)
#annualizedVolatility_3M = ComputeVol3M(mask = pipeline_underly_sid)
#annualizedVolatility_1M = ComputeVol1M(mask = pipeline_underly_sid)
annualizedVolatility = max(annualizedVolatility_6M, annualizedVolatility_3M,annualizedVolatility_1M)
sharpes_6M = returns_6M/annualizedVolatility_6M
raw_signals = None
if SHARPE:
raw_signals = sharpes_6M
else:
raw_signals = returns_6M
signals = raw_signals if LONG_ONLY else (raw_signals*raw_signals)
#positive_return = (returns_6M > 0)
#trigger = (returns 5D > -trigger_level) if LONG_ONLY else ((returns_5D < trigger_level)
sigtop = signals.top(NUM_TOP_POSITIONS)
raw_sig_top = raw_signals.top(NUM_TOP_POSITIONS)
raw_sig_bot = raw_signals.bottom(NUM_TOP_POSITIONS)
alongs = sigtop & raw_sig_top & (raw_signals > 0) & (returns_5D > -TRIGGER_LEVEL) # & (cud >= 13)
ashorts = sigtop & raw_sig_bot &(raw_signals <= 0 ) & (returns_5D < TRIGGER_LEVEL) & pipeline_shortable_sid
#alongs = (annualizedVolatility_6M> 0) #shorts# signals.top(NUN TOP POSITIONS)
if not PIPE_ENABLED:
alongs = (annualizedVolatility_6M > 0)
ashorts = (annualizedVolatility_6M < 0)# if LONG ONLY else longs
long_short_screen = alongs if LONG_ONLY else (alongs | ashorts)
my_screen = (annualizedVolatility_6M > 0) if MNAME in ['es','bd','dm','ed','md'] else long_short_screen
#my_screen = long_short_screen if False else (annualizedVolatility_6M > 0)#hlw
print('finger1',MNAME)
rsi = RSI(window_length=10,mask = pipeline_underly_sid)
print('rsipipe',annualizedVolatility_6M)
print('fxxxDAY_HACK_ENABLED',DAY_HACK_ENABLED)
#Only compute volatilities for assets that satisfy the requirements of our rolling strategy.
return Pipeline(
columns= {
#'cud' : cud,
'volatility' : annualizedVolatility,
'sharpes_6W' : sharpes_6M,
'drets': returns_1D,
'wrets': returns_5D,
'returns_6D': returns_6D,
'returns_1M': returns_1M,
'returns_3M': returns_3M,
'returns_5M': returns_5M,
'returns_6M': returns_6M,
#'signals': (signals)*signals,
'shorts' : ashorts,
#'wrets' : returns_5D,
'lower' : lower,
'middle' :middle,
'upper' :upper,
#'rsi':rsi.top(3),
'rsi_longs': rsi.top(3),
'rsi_shorts': rsi.bottom(3),
#'annualizedVolatility :annualizedVolatility_6M,
},
screen = my_screen
)
