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Introduction
Algorithmic trading is a type of trading that uses computer programs to make trading decisions. These programs use algorithms, or sets of rules, to identify trading opportunities and execute trades.
One advantage of algorithmic trading is that it can take advantage of opportunities that may be too difficult for humans to identify or too fast for humans to react to. For example, an algorithm might be able to identify a pattern in the market that signals a trading opportunity. Or, an algorithm might be able to execute a trade in a fraction of a second, before a human trader could even place an order.
Algorithmic trading is not without risks. For example, an algorithm might make a series of trades that turn out to be losses. Or, an algorithm might experience a technical glitch that causes it to make trades that are not in the best interests of the trader.
In recent years, a number of open-source algorithmic trading libraries have been developed in Python. In this article, we will take a look at some of the top Python libraries for algorithmic trading in 2022.
TA-Lib
TA-Lib is a free, open-source technical analysis library in Python that provides a wide range of statistical indicators and charting tools.
The library is used by traders, investors, and analysts to identify trends, make decisions, and execute trades. TA-Lib covers a wide range of technical analysis indicators, including moving averages, oscillators, momentum indicators, and volumetric indicators.
The library also provides a wide range of charting tools, such as candlestick charts, bar charts, and line charts.
Some of the features of TA-Lib include:
- Over 100 technical indicators
- Candlestick pattern recognition
- Open-source API for use in programming languages like C, C++, Java, Perl, Python, and R — Support for Windows, Linux, and macOS
- Ability to handle intraday, daily, weekly, and monthly data