class TargetVolExecutor(ExecutorBase):
def __init__(self, window=30, target_vol=0.01):
super().__init__()
self.m_vol = MovingStandardDeviation(window, 'return')
self.m_leverage = MovingAverage(window, 'leverage')
self.target_vol = target_vol
self.multiplier = 1.
def execute(self, target_pos: pd.DataFrame) -> Tuple[float, pd.DataFrame]:
if not self.m_vol.isFull():
if self.current_pos.empty:
turn_over = target_pos.weight.abs().sum()
else:
turn_over = self.calc_turn_over(target_pos, self.current_pos)
return turn_over, target_pos
else:
c_vol = self.m_vol.result()
c_leverage = self.m_leverage.result()
self.multiplier = self.target_vol / c_vol * c_leverage
candidate_pos = target_pos.copy()
candidate_pos[
'weight'] = candidate_pos.weight.values * self.multiplier
turn_over = self.calc_turn_over(candidate_pos, self.current_pos)
return turn_over, candidate_pos
def set_current(self, current_pos: pd.DataFrame):
super().set_current(current_pos)
self.m_leverage.push({'leverage': current_pos.weight.abs().sum()})
def update(self, data_dict: dict):
self.m_vol.push(data_dict)
def testMovingAverager(self):
window = 120
total = 2500
mv = MovingAverage(window, dependency='z')
runningSum = 0.0
con = []
for i in range(total):
value = float(i)
con.append(value)
mv.push(dict(z=value))
runningSum += value
if i >= window:
runningSum -= con[0]
con = con[1:]
if i >= window - 1:
expected = runningSum / window
calculated = mv.result()
self.assertAlmostEqual(calculated, expected, 15, "at index {0:d}\n"
"Average expected: {1:f}\n"
"Average calculated: {2:f}".format(i, expected,
calculated))
def testMovingAverager(self):
window = 120
total = 2500
mv = MovingAverage(window, dependency='z')
runningSum = 0.0
con = []
for i in range(total):
value = float(i)
con.append(value)
mv.push(dict(z=value))
runningSum += value
if i >= window:
runningSum -= con[0]
con = con[1:]
if i >= window - 1:
expected = runningSum / window
calculated = mv.result()
self.assertAlmostEqual(
calculated, expected, 15, "at index {0:d}\n"
"Average expected: {1:f}\n"
"Average calculated: {2:f}".format(i, expected,
calculated))
def testShiftValueHolder(self):
ma = MovingAverage(10, 'close')
with self.assertRaises(ValueError):
_ = Shift(ma, N=0)
test = Shift(ma, N=1)
test.push(dict(close=2.0))
ma.push(dict(close=2.0))
previous = ma.result()
test.push(dict(close=5.0))
ma.push(dict(close=5.0))
self.assertAlmostEqual(previous, test.result())
previous = ma.result()
test.push(dict(close=10.0))
self.assertAlmostEqual(previous, test.result())
def testShiftValueHolder(self):
ma = MovingAverage(10, 'close')
with self.assertRaises(ValueError):
_ = Shift(ma, N=0)
test = Shift(ma, N=1)
test.push(dict(close=2.0))
ma.push(dict(close=2.0))
previous = ma.result()
test.push(dict(close=5.0))
ma.push(dict(close=5.0))
self.assertAlmostEqual(previous, test.result())
previous = ma.result()
test.push(dict(close=10.0))
self.assertAlmostEqual(previous, test.result())
n = 3000
m = 3000
index = pd.date_range(dt.datetime(1990, 1, 1),
dt.datetime(1990, 1, 1) + dt.timedelta(days=m - 1))
index = np.repeat(index, n)
df = pd.DataFrame(np.random.randn(n * m, 3),
columns=['x', 'y', 'z'],
index=index)
df['c'] = matlib.repmat(np.linspace(0, n - 1, n, dtype=int), 1, m)[0]
start = dt.datetime.now()
t = MA(20, 'x') / MA(30, 'y')
res = t.transform(df, category_field='c')
print("Finance-Python (analysis): {0}s".format(dt.datetime.now() - start))
start = dt.datetime.now()
groups = df.groupby('c')
res = groups['x'].rolling(20).mean() / groups['y'].rolling(30).mean()
print("Pandas (group by): {0}s".format(dt.datetime.now() - start))
start = dt.datetime.now()
t = MovingAverage(20, 'x') / MovingAverage(30, 'x')
res = t.transform(df)
print("Finance-Python (accumulator): {0}s".format(dt.datetime.now() - start))
start = dt.datetime.now()
res = df['x'].rolling(20).mean() / df['x'].rolling(30).mean()
print("Pandas (group by): {0}s".format(dt.datetime.now() - start))
def __init__(self, window=30, target_vol=0.01):
super().__init__()
self.m_vol = MovingStandardDeviation(window, 'return')
self.m_leverage = MovingAverage(window, 'leverage')
self.target_vol = target_vol
self.multiplier = 1.
