Update README.md

README.md

@@ -5,24 +5,22 @@
 [![PyPI version](https://badge.fury.io/py/stratestic.svg)](https://badge.fury.io/py/stratestic)
 
 
-The `stratestic` module is a Python package that provides a framework for backtesting trading
-strategies. It contains a collection of pre-implemented trading strategies, as well as
-tools for analyzing and visualizing the performance of these strategies.
+The `stratestic` module is a Python package for backtesting trading strategies. 
+It includes pre-implemented strategies and tools for analysis and visualization. 
 
-To use this module, users can simply import the package and select one of the pre-implemented
-strategies to backtest. Alternatively, users can create their own custom strategies by extending
-the existing classes and implementing their own methods.
+Users can import the backtesting classes, select a strategy, or create custom ones by extending the base class.
+It offers a convenient way to explore and experiment with different strategies, evaluating the
+performance under different conditions. 
 
-This module provides a convenient and flexible way for users to explore and experiment
-with different trading strategies, and to evaluate their performance under different market
-conditions. By providing a standardized interface for defining and testing trading strategies,
-the `stratestic` library makes it easy for users to compare and evaluate different approaches to trading,
-and to gain insights into the factors that contribute to successful trading.
+With a standardized interface, `stratestic` makes 
+it easy to compare and evaluate different trading approaches, aiding in the development, 
+testing, and refinement of strategies for both personal and professional use. 📈🛠️💪
 
-Overall, `stratestic` is a powerful tool for anyone interested in developing, testing,
-and refining trading strategies, whether for personal use or for professional trading applications.
+## Installation
 
-## Backtesting
+    $ pip install stratestic
+
+## Usage
 
 This module offers 2 types of Backtesting - Vectorized and Iterative. Below they are described in more detail
 and examples are given. It is also shown how to use the optimization API in order to fine tune the strategies and