Technical Indicators Strategies in Python

A basic understanding of Python and Python libraries, such as Pandas and working with pandas dataframe

Basic knowledge of the financial markets

Analyse the trades by computing profit factor, win percentage and profit per trade

Apply technical indicators such as moving average, RSI, MACD, Chaikin Oscillator, etc. and analyse price charts

Combine two or more technical indicators to create a trading strategy

Create a screener of trending stocks and a technical analysis dashboard to see the values of different technical indicators

Create a trading strategy using moving averages, triple crossovers, RSI, rate of change, MACD, Chaikin Oscillator, TRIN indicator, etc

Describe the working of volume indicators such as On Balance Volume and Chaikin Oscillator

Differentiate between different moving averages and determine the suitable lookback period for moving averages

Evaluate the performance of a strategy by using metrics such as the Sharpe ratio and maximum drawdown

Explain the importance of market breadth indicators and describe the McClellan Oscillator as well as the TRIN indicator

Generate entry and exit signals. Manage your risk by adding stop loss and take profit levels to a strategy

Identify price trends using simple moving average, exponential moving average, and weighted moving average

List the top 5 secrets of successful technical traders

Paper trade and live trade the strategy

Perform analysis on multiple timeframes such as 15 minutes, 1 hour and 1 day

The real-world data and examples used in the course belong to the stocks from US markets. These stocks are traded on Nasdaq or NYSE. However, the concepts can be applied to any financial assets traded on any exchange