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19 Sep 2019

Constructing the Optimal Portfolio with MATLAB and Smart Beta

In this script, we demonstrate the strength of MATLAB’s optimisation capabilities to construct a portfolio driven by smart beta investment techniques. We do not advocate for the use of any particular investment or trading strategy, but rather demonstrate how to import your own data, implement a custom-made optimisation routine, and backtest the strategy: all in one place. We supply the code in the form of this live script for you to get started right away.

17 Sep 2019

Drones: Reaching New Heights in Education

Are you looking to make your classes more relevant and engaging? Drones have increased functionality and have decreased in size, making it easier to bring into classrooms. They do not cost a lot and have significant benefits, making teaching and learning so much more fun and enriching. It is a modern dynamic educational model that […]

23 Aug 2019

AI in Industry 4.0: Neural Networks for Time Series Modelling in MATLAB

An essential aspect of the mining process is the froth flotation process. This removes impurities from minerals, such as silica from iron ore, which ultimately determines the quality of the product. In this article we focus on how neural networks can be applied to the mineral extraction process, ensuring products of a higher quality. The […]

14 Aug 2019

AI in Finance: Using Deep Learning for RegTech

When deep learning and image processing come together, they can solve the huge problem of meeting regulations in the financial services industry. Take a look at this video where vacation work students Monaheng and Grace take you through the RegTech app, developed by previous vacation work students Christiaan and Zanele.

05 Aug 2019

Real-Time Simulation and Testing: Four Part Series

Learn about Real-Time Simulation and Testing with this short 4-part video series created by our Vacation Work students Andrew and James. Here we will explore Real-Time Simulations, Rapid Control Prototyping, Hardware-in-the-Loop and Speedgoat Real-Time Target machines.

31 Jul 2019

AI in Industry 4.0: Reinforcement Learning for control design

Watch our two-part video series created by our Vacation Work Students Daniel and Vicky to find out more about how reinforcement learning works and how to implement a practical controller with a reinforcement learning algorithm in MATLAB.

17 Jul 2019

Optimisation in Finance: Building the Optimal Trading Strategy

In a previous example, it was shown how MATLAB can be used to backtest a simple trading strategy in 8 lines of code, where the trading strategy was developed based on the Relative Strength (RS) index. In this article, I take Kawee’s work a step further and investigate if we can optimise the buy and sell RS index values to maximise our returns. The buy and sell signals are originally chosen at an RS Index of 40 and 70 respectively. Over a six-year period, this gave approximately 18% return-on-equity. Can this be improved?

28 Jun 2019

AI in Industry 4.0: Getting started with Machine Learning

Machine learning has made its mark! From medical diagnostic tools, speech recognition (think Siri and Alexa) to movie recommendations and predictive maintenance; machine learning techniques are being used to make critical business and life decisions.

04 Jun 2019

AI in Industry 4.0: Got Big Data?

Accessing and processing of data can be done entirely within MATLAB, no matter where it might be stored, including SQL/NoSQL databases, Spark™, and/or Hadoop®. Find out how you can tackle Big Data with MATLAB

30 May 2019

AI in Finance: Constructing a Trading Strategy Using Deep Learning

In this article, you will note the ease with which you can train and validate a neural network, and then see how this is applied by means of a trading strategy. By simple manipulations of historical data, we can leverage the flexibility of deep learning in MATLAB to generate future predictions of time series data, with reasonable precision.