def test_load_dataframe():
df = poloniex.load_dataframe('ETH_BTC', 1800, days_history=30)
assert len(df) > 0
assert df.index[0] < df.index[-1]
for val in ['close', 'high', 'low', 'open']:
assert val in df.columns.values
assert df.dtypes[val] == np.dtype('float64')
'date': today['date'],
'price': current_price,
'rsi': rsi[-1],
})
# Data settings
pair = "ETC_BTC" # Use ETH pricing data on the BTC market
period = 300 # Use 1800 second candles
days_history = 30 # From there collect 60 days of data
RSI_OPEN = 55
RSI_DEVIATION = 10
RSI_PERIOD = 14
# Request data from Poloniex
df = px.load_dataframe(pair, period, days_history)
# Algorithm settings
sim_params = {
'capital_base': 1,
'data_frequency': '30T',
'fee': {
'Long': 0.0025,
'Short': 0.0025,
}
}
gemini = Gemini(logic=logic, sim_params=sim_params, analyze=None)
gemini.run(df)
def cmo_trading_strategy(gemini, data):
if len(data) >= CMO_PERIOD:
cmo = cmo_logic(data)
assert -100 <= cmo <= 100
if cmo < OVERSOLD_VALUE:
gemini.account.close_position(position=gemini.account.positions[0],
percent=1,
price=data.iloc[-1]['low'])
elif cmo > OVERBOUGHT_VALUE:
gemini.account.enter_position(
type_="Long",
entry_capital=params['capital_base'] * 0.1,
entry_price=data.iloc[-1]['high'])
else:
raise Exception
if __name__ == '__main__':
data_df = poloniex.load_dataframe(pair=PAIR,
period=PERIOD,
days_history=DAYS_HISTORY)
backtesting_engine = Gemini(logic=cmo_trading_strategy,
sim_params=params,
analyze=analyze.analyze_bokeh)
backtesting_engine.run(data=data_df)
print(data_df)