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This course examines different approaches to building trading strategies across all asset classes. Using Python you will learn how to interact with market data to perform data analysis and find trading signals. We will look at advanced strategies to maximize trade performance and examine the statistics around testing and evaluating trade performance.
The first day of the programme begins with an overview of trading strategies and outlines various approaches used to look for trading opportunities. Through workshops we will implement data analytics using Python standard libraries including Pandas and Scipy.
On day two we investigate how to generate trading signals and analyze some of the dangers of overfitting the data. A workshop will focus on how to implement these trading signals in practice using real data. The afternoon examines methods for evaluating the performance of the trading strategies alongside methods of execution. We finish by exploring more advanced trading strategies and Machine Learning techniques in trading.
Please contact us for more information.
Specific job titles may include but are not limited to:
Applicants should come to the course with a basic understanding of capital markets and securities trading. Some exposure to Python programming would be beneficial.
This course is eligible for CE/CPD credit hours from CFA and GARP Institutes.
Workshop: Python coding framework
Workshop: Data and databases in Python
Workshop: Generating trading signals in practice
Workshop: Trading against a signal
This course is also available in New York Time Zone and Singapore Time Zone
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London Financial Studies are specialists in delivering professional development for finance professionals focusing on capital markets. LFS provide individuals, teams and companies with expert teaching that combines theoretical understanding with practical experience, giving them the knowledge to operate at the...
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