Python is an open-source language, meaning its source code is freely available to the public, and developers can contribute to the development of the language. Its popularity has grown rapidly in recent years, making it one of the most widely used programming languages in the world.

Python is used in investment management for a variety of tasks, such as data analysis, portfolio optimisation, risk management, and algorithmic trading. Here are some examples:

• Data Analysis: Python has several powerful libraries for data analysis, such as Pandas, NumPy, and SciPy, which allow investment managers to easily manipulate and analyse financial data. These libraries can be used to clean, pre-process, and transform large amounts of data into actionable insights.
• Portfolio Optimisation: Python can be used to optimise investment portfolios by finding the optimal combination of assets that maximises return while minimising risk. Libraries such as PyPortfolioOpt and CVXPY provide tools for portfolio optimisation using various techniques, such as mean-variance optimisation, risk parity, and Black-Litterman.
• Risk Management: Python can be used for risk management in investment management by calculating various risk metrics, such as Value at Risk (VaR), Conditional Value at Risk (CVaR), and stress tests. Libraries such as Riskfolio-Lib and PyRiskMetrics provide tools for calculating these metrics and analysing risk exposures.
• Algorithmic Trading: Python is commonly used for algorithmic trading in investment management, where trading decisions are made by computer algorithms based on pre-defined rules. Python's flexibility and ease of use make it an ideal language for developing and back testing trading algorithms. Libraries such as Backtrader, Zipline, and PyAlgoTrade provide tools for developing and testing trading strategies.

Python has become an essential tool in investment management, allowing investment managers to analyse data, optimise portfolios, manage risk, and execute trades efficiently. Its popularity in the industry continues to grow, as more investment managers adopt Python for their investment analysis.

Teach yourself

There are loads of online courses and tutorials you can take to learn Python from scratch. Here are a few of them:

Python and statistics for investment analysis

Python Tutorial

Udemy