EMA Crossover Strategy

This Python code implements an EMA (Exponential Moving Average) crossover strategy for generating buy and sell signals based on the crossover of short-term and long-term EMAs.

Dependencies

The code relies on the following dependencies:

pandas

numpy

matplotlib

You can install these dependencies using the following command:

pip install pandas numpy matplotlib

#Screenshots

Usage

1.Prepare the data file:

->Replace 'BN.csv' with the appropriate file path to your own dataset in the code.

->Make sure the data file contains a column named 'Close' that represents the closing prices of the asset.

2.Set the input variables:

->emaShortLength: The length (period) of the short-term EMA.

->emaLongLength: The length (period) of the long-term EMA.

->reward_ratio: The desired risk-reward ratio for setting target and stop-loss prices.

3.Run the code:

->Execute the Python script to run the EMA crossover strategy.

->The script will plot the closing prices, the short-term and long-term EMAs, and indicate the buy and sell signals on the chart.

->The generated buy and sell signals will be printed in the console, along with the corresponding entry, target, and stop-loss prices.

Example

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

Define the input variables

emaShortLength = 5

emaLongLength = 20

reward_ratio = 2 # Risk-reward ratio

Read the data into a DataFrame (replace with your own data)

data = pd.read_csv('BN.csv')

Close = data['Close']

Rest of the code... ...

This project is licensed under the MIT License.

Pin Script Version

The pin Script of the same code version is mentioned in the below github feel free to checkout and implement in Tradingview.

https://github.com/Tharunn25/5-20-Ema-corssover-strategy