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analyse trading signals in OHLCV data

Project description

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)

Project details


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Files for ohlcvish, version 0.0.1
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