ohlcvish
ohlcvish takes OHLCV data, generate multiple technical indicators on it and then gives you all existing Buy-Hold-Sell combinations in the dataset. Mean, median, min and max are the clustered results of the respective signal combination.
How to use
To use ohlcvish you need your OHLCV data to be in a pandas.DataFrame like this:
import pandas as pd
eth = pd.read_csv("data/ETH.csv", index_col="datetime", parse_dates=True)
eth.head()
close high low open volume
datetime
2015-08-07 3.00 3.0 0.6747 0.6747 123.93
2015-08-08 1.20 3.0 0.1500 3.0000 2119.43
2015-08-09 1.20 1.2 1.2000 1.2000 0.00
2015-08-10 1.20 1.2 1.2000 1.2000 0.00
2015-08-11 0.99 1.2 0.6504 1.2000 9486.09
Use ohlcvish() function to get all signals:
from ohlcvish import ohlcvish
signals = ohlcvish(eth)
signals.head()
macd rsi stoch adx aroon bbands sar ma amount forecast_mean forecast_median forecast_min forecast_max
0 -1 -1 0 0 0 0 -1 0 1 59.947906 59.947906 59.947906 59.947906
1 -1 0 0 -1 -1 0 0 0 1 -2.904930 -2.904930 -2.904930 -2.904930
2 -1 0 0 -1 0 0 -1 0 3 -7.415414 -6.642701 -11.645688 -3.957853
3 -1 0 0 -1 0 0 0 0 1 298.919554 298.919554 298.919554 298.919554
4 -1 0 0 0 -1 1 -1 -1 1 -54.082750 -54.082750 -54.082750 -54.082750
Define forecast_period to change forecast for mean, median, min and max.
signals = ohlcvish(eth, forecast_period=10)
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Metadata
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Release files for ohlcvish 0.0.1
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