algorithmic trading using python full course

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algorithmic trading is the process of using computer algorithms to automate the execution of trading strategies. python is a popular programming language for algorithmic trading due to its simplicity, flexibility, and extensive libraries for data analysis and machine learning. in this tutorial, we'll cover the fundamentals of algorithmic trading using python, including data handling, strategy development, backtesting, and live trading.
algorithmic trading involves using predefined rules to automatically execute trades in financial markets. these rules can be based on various factors such as price movements, technical indicators, or fundamental data. algorithmic trading can help traders execute trades more efficiently and quickly than manual trading.
before we start coding, we need to set up our development environment. we'll need python installed on our system along with some essential libraries such as pandas, numpy, matplotlib, and scikit-learn. you can install these libraries using pip:
we'll also need an integrated development environment (ide) such as jupyter notebook or visual studio code for writing and executing our python code.
data handling and analysis are crucial for algorithmic trading. we'll need historical price data to develop and backtest our trading strategies. you can obtain historical price data from various sources such as yahoo finance or quandl.
let's start by importing necessary libraries and loading historical price data:
once we have loaded the data, we can perform various data analysis tasks such as calculating moving averages, identifying trends, and calculating technical indicators.
strategy development involves defining the rules that govern when to buy or sell assets. strategies can be based on technical indicators, statistical models, machine learning algorithms, or a combination of these. let's implement a simple moving average crossover strategy as an example:
backtesting involves testing our trading strategy on historical data to e ...

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