nlp-project 0.0.1

A package for predicting buy and sell signals

Evx regpredict mlbot

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 whitepaper here

Installation

Install regpredict with python3 -m pip install regpredict

Usage

In your python script simply import the module and use as follows:

from regpredict.regbot import signal
print(signal(20,65,85,78,45,0.7))

The above methods take an assets a,b,macd,macdsignal,grad_histogram,close_gradient,close_gradient_neg based on the time interval you have chosen. 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 regbot import signal
#from regpredict.regbot import signal
df = pd.read_csv('../path/to/your_validation.csv')

y_pred = []
def getSignal(a,b,macd,macdsignal,grad_histogram,close_gradient,close_gradient_neg):
    return signal(a,b,macd,macdsignal,grad_histogram,close_gradient,close_gradient_neg)

Where thr is a user defined threshold.


df = df[df['enter_long'] == 1]
print(df.head())

df['result'] = df.apply(lambda row: getSignal(row['a'],row['b'],row['macd'],row['macdsignal'],row['grad-histogram'],row['close-gradient']row['close-gradient-neg']), axis=1)

print(df.head())

print(len(df[df['result'] == df['enter_long']]), len(df))

Your original data must already have some presumed 'buy' signal.

Warning

This is not financial advise. Regpredict is entirely on its preliminary stages. Use it at your own risk.