def test_strategy(self, indicator, params=None, data=None):
# DATA
if data is None:
stock = pd.read_csv('../Data/bitcoin_histo.csv', sep=';')
pxlast_csv_str = stock['PX_LAST']
pxlast = pd.to_numeric(pxlast_csv_str)
dates_csv_str = stock['Date']
dates = pd.to_datetime(dates_csv_str, dayfirst=True)
else:
# dates = pd.Series(data[0].values)
pxlast = data # pd.Series(data[1].values)
# COMPUTATIONS
if indicator == 'macd':
ss = params[0]
ls = params[1]
sf = params[2]
macd, macd_ema9 = Indicators.macd(pxlast,
short_span=ss,
long_span=ls,
smoothing_factor=sf)
returns = pxlast.pct_change(1)
invested = Helpers.indicators_to_investment(indicator_name='macd',
data=(macd, macd_ema9))
elif indicator == 'ema':
ema_difference = Indicators.ema_diff(pxlast,
long_span=26,
short_span=12)
returns = pxlast.pct_change(1)
invested = Helpers.indicators_to_investment(
indicator_name='ema_diff', data=ema_difference)
elif indicator == 'macd_rsi':
macd, macd_ema9 = Indicators.macd(pxlast,
long_span=26,
short_span=12,
smoothing_factor=9)
rsi = Indicators.RSI(pxlast, period=14)
invested = Helpers.indicators_to_investment(
indicator_name='macd_rsi', data=(macd, macd_ema9, rsi))
# PROFITABILITY
total_profit, strat_profit = self.profitability(returns, invested)
# return strat_profit.iloc[-1].values[0]
# PLOT
data_plot = pd.concat([total_profit, strat_profit], axis=1)
data_plot.plot()
plt.show()
