def run(self):
# Fetch and select timeseries.
self.ts = pf.fetch_timeseries(self.symbol,
use_cache=self.options['use_cache'])
self.ts = pf.select_tradeperiod(self.ts,
self.start,
self.end,
use_adj=self.options['use_adj'])
# Add technical indicator: 200 day sma regime filter.
self.ts['regime'] = pf.CROSSOVER(self.ts,
timeperiod_fast=1,
timeperiod_slow=200)
# Add technical indicators: X day high, and X day low.
self.ts['period_high'] = pd.Series(self.ts.close).rolling(
self.options['period']).max()
self.ts['period_low'] = pd.Series(self.ts.close).rolling(
self.options['period']).min()
# Finalize timeseries.
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
# Create tlog and dbal objects.
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
# Run algo, get logs, and get stats.
self._algo()
self._get_logs()
self._get_stats()
def run(self):
self.ts = pf.fetch_timeseries(self.symbol)
self.ts = pf.select_tradeperiod(self.ts, self.start, self.end, use_adj=True)
# Add technical indicator: 200 sma regime filter
self.ts['regime'] = \
pf.CROSSOVER(self.ts, timeperiod_fast=1, timeperiod_slow=200)
# Add technical indicator: instrument risk, i.e. annual std
self.ts['vola'] = \
pf.VOLATILITY(self.ts, lookback=20, time_frame='yearly')
# Add technical indicator: X day sma
sma = SMA(self.ts, timeperiod=self.sma)
self.ts['sma'] = sma
# Add technical indicator: X day high, and X day low
period_high = pd.Series(self.ts.close).rolling(self.period).max()
period_low = pd.Series(self.ts.close).rolling(self.period).min()
self.ts['period_high'] = period_high
self.ts['period_low'] = period_low
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
self._algo()
def run(self):
self.ts = pf.fetch_timeseries(self.symbol)
self.ts = pf.select_tradeperiod(self.ts, self.start,
self.end, self.use_adj)
# Add technical indicator: day sma regime filter
self.ts['regime'] = \
pf.CROSSOVER(self.ts, timeperiod_fast=1, timeperiod_slow=self.sma_period,
band=self.percent_band)
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
self._algo()
def run(self):
self.ts = pf.fetch_timeseries(self.symbol)
self.ts = pf.select_tradeperiod(self.ts, self.start, self.end)
# add regime filter
self.ts['regime'] = \
pf.CROSSOVER(self.ts,
timeperiod_fast=self.timeperiod_fast,
timeperiod_slow=self.timeperiod_slow,
band=self.percent_band)
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
self._algo()
def run(self):
self._ts = pf.fetch_timeseries(self._symbol)
self._ts = pf.select_tradeperiod(self._ts, self._start,
self._end, self._use_adj)
# Add technical indicator: day sma
sma = SMA(self._ts, timeperiod=self._sma_period)
self._ts['sma'] = sma
self._tlog = pf.TradeLog()
self._dbal = pf.DailyBal()
# add S&P500 200 sma regime filter
ts = pf.fetch_timeseries('^GSPC')
ts = pf.select_tradeperiod(ts, self._start, self._end, False)
self._ts['regime'] = \
pf.CROSSOVER(ts, timeperiod_fast=1, timeperiod_slow=200)
self._algo()
def run(self):
self.portfolio = pf.Portfolio()
self.ts = self.portfolio.fetch_timeseries(
self.symbols,
self.start,
self.end,
use_cache=self.options['use_cache'],
use_adj=self.options['use_adj'])
# Add S&P500 200 sma regime filter
ts = pf.fetch_timeseries('^GSPC')
ts = pf.select_tradeperiod(ts, self.start, self.end, use_adj=False)
self.ts['regime'] = \
pf.CROSSOVER(ts, timeperiod_fast=1, timeperiod_slow=200, band=3.5)
# Add calendar columns
self.ts = self.portfolio.calendar(self.ts)
# Add technical indicator Momenteum for all symbols in portfolio.
def _momentum(ts, ta_param, input_column):
return pf.MOMENTUM(ts,
lookback=ta_param,
time_frame='monthly',
price=input_column,
prevday=False)
lookbacks = range(3, 18 + 1)
for lookback in lookbacks:
self.ts = self.portfolio.add_technical_indicator(
self.ts,
ta_func=_momentum,
ta_param=lookback,
output_column_suffix='mom' + str(lookback),
input_column_suffix='close')
self.ts, self.start = self.portfolio.finalize_timeseries(
self.ts, self.start)
self.portfolio.init_trade_logs(self.ts)
self._algo()
self._get_logs()
self._get_stats()
def run(self):
self.ts = pf.fetch_timeseries(self.symbol)
self.ts = pf.select_tradeperiod(self.ts, self.start, self.end)
# add regime filter
self.ts['regime'] = \
pf.CROSSOVER(self.ts,
timeperiod_fast=self.timeperiod_fast,
timeperiod_slow=self.timeperiod_slow,
band=self.percent_band)
# Add technical indicator: volatility
self.ts['vola'] = pf.VOLATILITY(self.ts)
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
self._algo()
def run(self):
# Fetch and selct timeseries
self.ts = pf.fetch_timeseries(self.symbol,
use_cache=self.options['use_cache'])
self.ts = pf.select_tradeperiod(self.ts, self.start, self.end,
self.options['use_adj'])
# Add technical indicator: day sma regime filter.
self.ts['regime'] = \
pf.CROSSOVER(self.ts, timeperiod_fast=50, timeperiod_slow=200)
# Finalize timeseries
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
self._algo()
self._get_logs()
self._get_stats()
def run(self):
self.ts = pf.fetch_timeseries(self.symbol)
self.ts = pf.select_tradeperiod(self.ts,
self.start,
self.end,
use_adj=False)
# Add technical indicator: 200 sma regime filter
self.ts['regime'] = \
pf.CROSSOVER(self.ts, timeperiod_fast=1, timeperiod_slow=200)
# Add technical indicator: X day high, and X day low
period_high = pd.Series(self.ts.close).rolling(self.period).max()
period_low = pd.Series(self.ts.close).rolling(self.period).min()
self.ts['period_high'] = period_high
self.ts['period_low'] = period_low
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
self._algo()
def run(self):
self.ts = pf.fetch_timeseries(self.symbol,
use_cache=self.options['use_cache'])
self.ts = pf.select_tradeperiod(self.ts, self.start, self.end,
self.options['use_adj'])
# Add technical indicator: day sma
self.ts['sma'] = SMA(self.ts, timeperiod=self.options['sma_period'])
# add S&P500 200 sma regime filter
ts = pf.fetch_timeseries('^GSPC')
ts = pf.select_tradeperiod(ts, self.start, self.end, use_adj=False)
self.ts['regime'] = \
pf.CROSSOVER(ts, timeperiod_fast=1, timeperiod_slow=200)
self.ts, self.start = pf.finalize_timeseries(self.ts, self.start)
self.tlog = pf.TradeLog(self.symbol)
self.dbal = pf.DailyBal()
self._algo()
self._get_logs()
self._get_stats()
def _crossover(ts, ta_param, input_column):
return pf.CROSSOVER(ts,
timeperiod_fast=1,
timeperiod_slow=200,
price=input_column,
prevday=False)