Update README.md

Author: tejaslinge

README.md

@@ -1,15 +1,15 @@
-# Technical Analysis and backtesting using Python
+# Technical Analysis and back-testing using Python
 
 Technical indicators are heuristic or pattern-based signals produced by the price, volume, and/or open interest of a security or contract used by traders who follow technical analysis. (<i>src: https://www.investopedia.com/terms/t/technicalindicator.asp#:~:text=Technical%20indicators%20are%20heuristic%20or,to%20predict%20future%20price%20movements.</i>)
 
-In this project, I've demonstrated how to use these technical indicators to trade in the stock markets and backtested the results using Python. Technical indicators used for analysis in this project are: 
+In this project, I've demonstrated how to use these technical indicators to trade in the stock markets and back-tested the results using Python. Technical indicators used for analysis in this project are: 
 
 1. Simple Moving Average (SMA)
 2. Exponential Moving Average (EMA)
 3. Bollinger Bands 
 4. Moving Average Convergence Divergence (MACD)
 
-There are many other technical indicators such as RSI, Stochastics, Money Flow Index, etc. but for the purpose of explaining how to implement and backtest technical trading strategies in Python, I've used some of the most popular ones. We can learn how buy/sell signals are generated using these strategies and how long to implement them.
+There are many other technical indicators such as RSI, Stochastics, Money Flow Index, etc. but for the purpose of explaining how to implement and back-test technical trading strategies in Python, I've used some of the most popular ones. We can learn how buy/sell signals are generated using these strategies and how long to implement them.
 
 We can also pair technical indicators with other external factors (qualitative factors such as EBIDTA, revenue, future prospects, management, etc) to improve our trading strategy and get better results.