def __init__(self,
balance,
tickers=None,
base_model=LinearRegression(),
n_prev=2,
wait=100,
steps_ahead=100,
k=5,
envelope='proportional',
log=False,
commission=.0002,
flat_rate=8):
if tickers is None:
tickers = s_and_p_names('2014-1-1', '2015-11-02')
super(TSEBuyAndHoldStrategy, self).__init__(balance,
tickers,
log=log,
commission=commission,
wait=wait,
flat_rate=flat_rate)
self.model = TimeSeriesRegressor(base_model, n_ahead=1, n_prev=n_prev)
self.steps_ahead = steps_ahead
self.k = k
self.envelope = envelope
def __init__(self, balance, tickers=None, wait=100, k=5, envelope='proportional',
log=False, commission=.0002, flat_rate=8):
if tickers is None:
tickers = s_and_p_names('2014-1-1', '2015-11-02')
super(BestChangeBuyAndHoldStrategy, self).__init__(balance, tickers,
log=log, commission=commission, wait=wait, flat_rate=flat_rate)
self.k = k
self.envelope = envelope
def __init__(self, balance, tickers=None, base_model=LinearRegression(),
n_prev=2, wait=100, steps_ahead=100, k=5, envelope='proportional',
log=False, commission=.0002, flat_rate=8):
if tickers is None:
tickers = s_and_p_names('2014-1-1', '2015-11-02')
super(TSEBuyAndHoldStrategy, self).__init__(balance, tickers,
log=log, commission=commission, wait=wait, flat_rate=flat_rate)
self.model = TimeSeriesRegressor(base_model, n_ahead=1, n_prev=n_prev)
self.steps_ahead = steps_ahead
self.k = k
self.envelope = envelope
def buy_and_hold_spread(k=5, wait=100, start="2014-1-1", end="2015-11-02", iterations=100):
sp500_names = s_and_p_names(start, end)
out = []
if iterations == 'full':
for tickers in itertools.combinations(sp500_names, k):
tickers = list(tickers)
bs = BuyAndHoldStrategy(10000, tickers, wait=wait)
out.append(backtest(bs, start=start, end=end, correct=False))
else:
for i in range(iterations):
tickers = random.sample(sp500_names, k)
bs = BuyAndHoldStrategy(10000, tickers, wait=wait)
out.append(backtest(bs, start=start, end=end, correct=False))
return out
def buy_and_hold_spread(k=5,
wait=100,
start="2014-1-1",
end="2015-11-02",
iterations=100):
sp500_names = s_and_p_names(start, end)
out = []
if iterations == 'full':
for tickers in itertools.combinations(sp500_names, k):
tickers = list(tickers)
bs = BuyAndHoldStrategy(10000, tickers, wait=wait)
out.append(backtest(bs, start=start, end=end, correct=False))
else:
for i in range(iterations):
tickers = random.sample(sp500_names, k)
bs = BuyAndHoldStrategy(10000, tickers, wait=wait)
out.append(backtest(bs, start=start, end=end, correct=False))
return out
def __init__(self,
balance,
tickers=None,
wait=100,
k=5,
envelope='proportional',
log=False,
commission=.0002,
flat_rate=8):
if tickers is None:
tickers = s_and_p_names('2014-1-1', '2015-11-02')
super(BestChangeBuyAndHoldStrategy,
self).__init__(balance,
tickers,
log=log,
commission=commission,
wait=wait,
flat_rate=flat_rate)
self.k = k
self.envelope = envelope
