Algorithmic and Quantitative Trading Online Videos - InvestingChannel

Algorithmic and Quantitative Trading Online Videos


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It is really not easy to find online video courses on algorithmic and quantitative trading for newbies, until recently I got an email introducing this website, QuantInsti is Asia premiere Algorithmic Trading Research and Training Institute focused on preparing financial market professionals and equipping them to conquer the contemporary field of Algorithmic and High-Frequency Trading. As an initiative by financial market professionals with stellar academic and professional credentials, the program aims to fulfill the pressing demands for highly specialized skill sets of a potentially lucrative domain of Algorithmic Trading.

Some videos are really useful so I list them below:
Introduction to Machine Learning for Trading
This course will help you in understanding the basics of Machine Learning and give you an opportunity to code an algorithm in Python. You will also learn the different types of Machine Learning Techniques. In this course, you will understand a few research papers on Reinforcement learning and how it works. Finally, you will code a trading strategy using the predictions made by the Machine Learning algorithm.

Trading with Machine Learning: Regression
In this course, you will learn the mathematical concepts behind regression function, such as the gradient descent and cost function optimization. Diving deeper, you will get a thorough overview of the Bias and Variance problems faced by machine learning algorithms. Finally, you will be coding a trading strategy using the predictions made by the algorithm.

Trading using Options Sentiment Indicators
This course will help you to understand the two major emotions that drive the entire market – Fear and Greed and how we can capitalize on them to make profits. We will learn about sentiment indicators, how to interpret them and devise trading strategies using the same. We will develop a trading logic for our algorithm defining our entry and exit points using signals from the sentiment indicators. We will code this strategy using Python programming language and analyze the buy/sell orders of S&P 500 index futures, generated by our strategy in Microsoft Excel using 2 years of historical data for backtesting.

Statistical Arbitrage Trading
This course will help you in gaining an in-depth understanding of Statistical Arbitrage along with the key statistical concepts involved in modeling a Stat Arb strategy. This course will give you an insight into the various types of risks involved in a Stat Arb strategy and ways to mitigate them so that you are empowered to start trading pairs or develop your very own Statistical Arbitrage model. We will take you through a practical implementation of Pairs Trading (Lead – Aluminium Pair) in Excel and explain how to code the same strategy in Python as well.

Python for Trading
The course is designed for anyone who wants to start trading in Python. It covers important concepts from scratch, and also helps to develop and improve Python skills specific to trading. Topics covered include objects, namespaces, classes, data structures, data analysis libraries, coding trading strategy using Moving Averages and a technical Indicator called Relative Strength Index.

Getting Started with Algorithmic Trading
The course will help you appreciate the advantages of algorithmic trading over traditional training techniques. This course also comes with a downloadable e-book (provided in the last section of this course) for your reference.

Trading with Machine Learning: Classification and SVM
This course is a mixture of videos, PDF documents, MCQs, and Interactive Exercises. In this course, you will learn about different types of the Supervised classifier. You will also learn about binary classification, math functions used for classification and their application in Financial Market. Further, you will also understand the difference between Binary and Multiclass Classification and will learn one vs all algorithm, one hot encoding and softmax function for performing multiclass classification.

More videos are following… Enjoy.
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