def strategy(data):
close = data['futures'].sel(field='close')
close_prev = data['futures'].sel(field='close').shift(time=1)
close_change = (close - close_prev)/close_prev
close_crypto = data['crypto'].sel(field='close')
close_crypto_prev = data['crypto'].sel(field='close').shift(time=1)
close_change_crypto = (close_crypto - close_crypto_prev)/close_crypto_prev
sma200 = qnta.sma(close_change, 20).fillna(0).mean('asset').isel(time=-1)
sma200_crypto = qnta.sma(close_change_crypto, 20).isel(time=-1)
return xr.where(sma200 < sma200_crypto, 1, -1)
def get_features(data):
trend = qnta.roc(qnta.lwma(data.sel(field="close"), 90), 1)
k, d = qnta.stochastic(data.sel(field="high"), data.sel(field="low"),
data.sel(field="close"), 21)
volatility = qnta.tr(data.sel(field="high"), data.sel(field="low"),
data.sel(field="close"))
volatility = volatility / data.sel(field="close")
volatility = qnta.lwma(volatility, 21)
volume = data.sel(field="vol")
volume = qnta.sma(volume, 7) / qnta.sma(volume, 80)
volume = volume.where(np.isfinite(volume), 0)
# combine features to one array
result = xr.concat([trend, d, volatility, volume],
pd.Index(
['trend', 'stochastic_d', 'volatility', 'volume'],
name='field'))
return result.transpose('time', 'field', 'asset')
def strategy(data):
close = data.sel(field='close')
sma200 = qnta.sma(close, 200).isel(time=-1)
sma20 = qnta.sma(close, 20).isel(time=-1)
return xr.where(sma200 < sma20, 1, -1)
# os.environ['API_KEY'] = "{your_api_key_here}" # you may need it for local development
import qnt.ta as qnta
import qnt.data as qndata
data_all = qndata.futures.load_data(tail=120)
close_all = data_all.sel(field='close')
data = qndata.futures.load_data(assets=['F_GC', 'F_DX'], tail=120)
high = data.sel(field='close')
low = data.sel(field='low')
close = data.sel(field='close')
volume = data.sel(field='vol')
print("Moving averages:")
sma = qnta.sma(close, 20)
ema = qnta.ema(close, 20)
lwma = qnta.lwma(close, 20)
wma = qnta.wma(close, [3, 2, 1])
wi_ma = qnta.wilder_ma(close, 20)
vwma = qnta.vwma(close, volume, 20)
print("SMA(20)")
print(sma.to_pandas().tail().T)
print("---")
print("Oscillators:")
stoch_k = qnta.stochastic_k(high, low, close, 14)
stoch_fast_k, stoch_fast_d = qnta.stochastic(high, low, close, 14)
stoch_slow_k, stoch_slow_d = qnta.stochastic(high, low, close, 14)
rsi = qnta.rsi(close, 14)