Learn Trading Strategies in Python

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Searching here for the options we have on the web to learn trading strategies using Python. As someone who loves learning about finance and tech, we have a lack of internet resources to assist us on this journey.

In fact, what is the technology we have to learn in order to be better investors. When thinking of this, I have seen many websites showing different ways of becoming wealthy, but actually, the biggest players on the market are using certain technological tools for this today. 

learn-trading-strategies-in-python

The best known investor, Warren Buffett, is for instance, an advocate for value investing, but in a world of thousands of companies, swimming through a market with no tech knowledge possible? I am not so sure that is possible!

Let me make it very clear, when I said that tech is not about using the site or software on the computer, it is understanding the workings of the code and logic that is at work, from my own research, there is a very limited amount of knowledge on this on the market.

To begin that journey, we do need certain skills like coding languages and logic. There is plenty of information on the web to help. 

From my experience, the best language to start is python, for some reasons:

Python has several libraries that are ready for you already even to financial markets which help to save your time. Free to use and Open Source. I could put many more reasons here, too, but one of the things that I hate is finding blogs or news stories that say lots of things, and say nothing.

What is the best course to help us to learn trading strategies in python?

This DataCamp course helps you learn how to implement customized trading strategies in Python, backtest them, and assess their performance!.

What else do you need to get started?. Are you fascinated with financial markets and are interested in trading money?

This course helps you to understand why people trade, what are different trading styles, and how to use Python to implement and test your own trading strategies.

Start your trading adventures with a primer on technical analysis, indicators, and signals. 

learn-trading-strategies-in-python

Financial Trading in Python from DataCamp

learn-trading-strategies-in-python

Course Description

Are you fascinated by the financial markets and interested in financial trading? This course will help you to understand why people trade, what the different trading styles are, and how to use Python to implement and test your trading strategies. Start your trading adventure with an introduction to technical analysis, indicators, and signals. You’ll learn to build trading strategies by working with real-world financial data such as stocks, foreign exchange, and cryptocurrencies. By the end of this course, you’ll be able to implement custom trading strategies in Python, backtest them, and evaluate their performance.
  • 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.

  • 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.

  • 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.

  • 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.

I took some courses on DataCamp, mostly on Data Analysis, so I actually like their content, since each lecture has a short video (I hate courses that are lengthy videos) and right after each lecture, you really get hands-on experience, for instance, by solving problems by writing code in Python.

For me, some of the best courses on the market are hosted by DataCamp. 

Final Thoughts: Are you ready to learn trading strategies in Python?

Hopefully, this content will be as helpful for you as it was for me. 

Take care 🙂

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