def _createFullNotionalEquityCurve(self, curve):
rawpos = curve.drop(['cash', 'commission', 'total', 'margin', 'pnl'],
axis=1)
notionals = rawpos.abs().sum(axis=1).fillna(0)
notional_directions = rawpos.sum(axis=1).fillna(0).apply(sign)
pnldiffs = curve['pnl'].diff()
# to handl the case when pnl is shown in null notional day
cumPnL = 0.
returns = []
for notional, pnldiff, direction in zip(notionals, pnldiffs,
notional_directions):
if not isClose(notional):
r = direction * np.log(
direction * notional /
(direction * notional - pnldiff - cumPnL))
returns.append(r)
cumPnL = 0.
elif not np.isnan(pnldiff):
returns.append(0.)
cumPnL += pnldiff
else:
returns.append(0.)
curve['return'] = returns
curve.fillna(0., inplace=True)
curve['equity_curve'] = np.exp(curve['return'].cumsum())
def updateHoldingsFromFill(self, fill, pnl):
self.currentHoldings[fill.symbol] += fill.fillCost
self.currentHoldings['commission'] += fill.commission
if not isClose(fill.fillCost, 0.):
self.currentHoldings['cash'] -= (fill.fillCost + fill.commission)
else:
self.currentHoldings['cash'] += (pnl - fill.commission)
self.currentHoldings['pnl'] += pnl - fill.commission
self.currentHoldings['total'] += pnl - fill.commission
def result(self):
corr = self._correlationHolder.result()
tmp = self._pReturnVar.result()
if not isClose(tmp, 0.):
pStd = math.sqrt(tmp)
else:
pStd = 0.
tmp = self._mReturnVar.result()
if not isClose(tmp, 0.):
mStd = math.sqrt(tmp)
else:
mStd = 0.
if not isClose(tmp, 0.):
beta = corr * pStd / mStd
else:
beta = 0.
alpha = self._pReturnMean.result() - beta * self._mReturnMean.result()
return alpha, beta
def updateHoldingsFromFill(self, fill, pnl):
self.currentHoldings[fill.symbol] += fill.fillCost
self.currentHoldings['commission'] += fill.commission
if not isClose(fill.fillCost, 0.):
self.currentHoldings['cash'] -= (fill.fillCost + fill.commission)
else:
self.currentHoldings['cash'] += (pnl - fill.commission)
self.currentHoldings['pnl'] += pnl - fill.commission
self.currentHoldings['total'] += pnl - fill.commission
fillDir = fill.direction
if fillDir == OrderDirection.BUY_BACK or fillDir == OrderDirection.SELL_SHORT:
self.currentHoldings['margin'] -= fill.fillCost
def updateHoldingsFromFill(self, fill, pnl):
self.currentHoldings[fill.symbol] += fill.fillCost
self.currentHoldings['commission'] += fill.commission
if not isClose(fill.fillCost, 0.):
self.currentHoldings['cash'] -= (fill.fillCost + fill.commission)
else:
self.currentHoldings['cash'] += (pnl - fill.commission)
self.currentHoldings['pnl'] += pnl - fill.commission
self.currentHoldings['total'] += pnl - fill.commission
fillDir = fill.direction
if fillDir == OrderDirection.BUY_BACK or fillDir == OrderDirection.SELL_SHORT:
self.currentHoldings['margin'] -= fill.fillCost
def result(self):
n = self.size
if n >= 2:
n = self.size
nominator = n * self._runningSumCrossSquare - self._runningSumLeft * self._runningSumRight
denominator = (n * self._runningSumSquareLeft - self._runningSumLeft * self._runningSumLeft) \
* (n * self._runningSumSquareRight - self._runningSumRight * self._runningSumRight)
if not isClose(denominator, 0.):
denominator = math.sqrt(denominator)
return nominator / denominator
else:
return 0.0
else:
return np.nan
def result(self):
n = self.size
if n >= 2:
n = self.size
nominator = n * self._runningSumCrossSquare - self._runningSumLeft * self._runningSumRight
denominator = (n * self._runningSumSquareLeft - self._runningSumLeft * self._runningSumLeft) \
* (n * self._runningSumSquareRight - self._runningSumRight * self._runningSumRight)
if not isClose(denominator, 0.):
denominator = math.sqrt(denominator)
return nominator / denominator
else:
return 0.0
else:
return np.nan
def result(self):
n = self.size
if n >= 2:
n = self.size
nominator = n * self._runningSumCrossSquare - self._runningSumLeft * self._runningSumRight
denominator = (n * self._runningSumSquareLeft - self._runningSumLeft * self._runningSumLeft) \
* (n * self._runningSumSquareRight - self._runningSumRight * self._runningSumRight)
if not isClose(denominator, 0.):
denominator = math.sqrt(denominator)
return nominator / denominator
else:
return 0.0
else:
raise ZeroDivisionError("Container has less than 2 samples")
def result(self):
n = self.size
if n >= 2:
n = self.size
nominator = n * self._runningSumCrossSquare - self._runningSumLeft * self._runningSumRight
denominator = (n * self._runningSumSquareLeft - self._runningSumLeft * self._runningSumLeft) \
* (n * self._runningSumSquareRight - self._runningSumRight * self._runningSumRight)
if not isClose(denominator, 0.):
denominator = math.sqrt(denominator)
return nominator / denominator
else:
return 0.0
else:
raise ZeroDivisionError("Container has less than 2 samples")
def _createFullNotionalEquityCurve(self, curve):
rawpos = curve.drop(['cash', 'commission', 'total', 'margin', 'pnl'], axis=1)
notionals = rawpos.abs().sum(axis=1).fillna(0)
pnldiffs = curve['pnl'].diff()
# to handl the case when pnl is shown in null notional day
cumPnL = 0.
returns = []
for notional, pnldiff in zip(notionals, pnldiffs):
if not isClose(notional):
r = np.log(notional / (notional - pnldiff - cumPnL))
returns.append(r)
cumPnL = 0.
elif not np.isnan(pnldiff):
returns.append(0.)
cumPnL += pnldiff
else:
returns.append(0.)
curve['return'] = returns
curve.fillna(0., inplace=True)
curve['equity_curve'] = np.exp(curve['return'].cumsum())
def testIsClose(self):
self.assertTrue(isClose(1.0, 1.000001, 1e-5))
self.assertTrue(isClose(1e9, 1. + 1e9, 1e-5, 1e-6))
self.assertFalse(isClose(1., 1. + 1e-5, 1e-6, 1e-6))
def result(self):
tmp = self._var.result()
if not isClose(tmp, 0.):
return self._mean.result() / math.sqrt(self._var.result())
else:
return np.nan
