tothemoon evx ML model
This is a simplified version of evxpredictor package used to generate buy and sell signals for crypto and conventional stock markets based on the excess volume indicator(EVX). EVX is a concept where the bid-ask spread is estimated inherently from current market prices.
You can read more about Evx in the free whitepaper here
Installation
Install tothemoon with python3 -m pip install tothemoon
Usage
In your python script simply import the module and use as follows:
from tothemoon.moon import signal
print(signal(20,65,utcdatetime))
The above methods take an assets open, close prices of the asset based on the time interval you have chosen in OHCLV type. A zero classification output would instruct the user to sell, while one output means don't sell or buy if the asset is not already present in the orders.
Testing an entire dataframe
Testing of a dataframe for correct buy, sell signals is as simple as applying the function as follows:
import pandas as pd
from moon import signal, Regbot
df = pd.read_csv('path/toyour/file.csv')
def getSignal(open,close,utcdatetime):
return signal(open,close,utcdatetime)
# select long profitable trades
df2 = df[df['close_profit_abs'] > 0]
df2 = df2[df2['is_short'] == 0]
print(df2.head())
# Run all predictions
df2['enter_long_pred'] = df.apply(lambda row: getSignal(row['open'], row['close'], row['date']), axis=1)
print(len(df2[df2['enter_long_pred'] == df2['is_short']]), len(df) )
print(df2[df2['is_short']==0].head(15))
Your original data must already have some presumed 'buy' signal.
Warning
This is not financial advise. tothemoon is entirely on its preliminary stages. Use it at your own risk.
1 maintainer
Metadata
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Release files for tothemoon 0.1.9
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