Course
Financial Trading in Python
IntermediateSkill Level
Updated 12/2021PythonApplied Finance4 hr15 videos50 Exercises4,000 XP20,318Statement of Accomplishment
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Prerequisites
Intermediate Python for Finance1
Trading Basics
What is financial trading, why do people trade, and what’s the difference between technical trading and value investing? This chapter answers all these questions and more. You’ll also learn useful tools to explore trading data, generate plots, and how to implement and backtest a simple trading strategy in Python.
2
Technical Indicators
Let's dive into the world of technical indicators—a useful tool for constructing trading signals and building strategies. You’ll get familiar with the three main indicator groups, including moving averages, ADX, RSI, and Bollinger Bands. By the end of this chapter, you’ll be able to calculate, plot, and understand the implications of indicators in Python.
3
Trading Strategies
You’re now ready to construct signals and use them to build trading strategies. You’ll get to know the two main styles of trading strategies: trend following and mean reversion. Working with real-life stock data, you’ll gain hands-on experience in implementing and backtesting these strategies and become more familiar with the concepts of strategy optimization and benchmarking.
4
Performance Evaluation
How is your trading strategy performing? Now it’s time to take a look at the detailed statistics of the strategy backtest result. You’ll gain knowledge of useful performance metrics, such as returns, drawdowns, Calmar ratio, Sharpe ratio, and Sortino ratio. You’ll then tie it all together by learning how to obtain these ratios from the backtest results and evaluate the strategy performance on a risk-adjusted basis.
Financial Trading in Python
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FAQs
What trading strategies will I learn to implement in Python?
You will implement and backtest both trend-following and mean-reversion strategies using real stock data, and learn strategy optimization and benchmarking techniques.
Which technical indicators are covered?
You will learn to calculate and interpret moving averages, ADX, RSI, and Bollinger Bands, and use them to construct trading signals in Python.
What performance metrics are used to evaluate strategies?
You will learn returns, drawdowns, Calmar ratio, Sharpe ratio, and Sortino ratio to evaluate strategy performance on a risk-adjusted basis.
What types of financial data are used in the course?
You will work with real-world data from stocks, foreign exchange markets, and cryptocurrencies throughout the four chapters.
Do I need prior trading or finance experience?
No trading experience is needed. The course starts with trading basics and explains why people trade and the difference between technical trading and value investing.
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