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  • IFTA Speaker

Mathew Verdouw, CMT, CFTe, has taken a different path to Technical Analysis than most. A year out from university in 1996, he started the software development company that would be named Market Analyst Software in Brisbane, Australia. Over 20 years Mathew has dedicated himself to learning all the different facets of financial analysis and he has travelled the world meeting with some of the thought leaders in the field. From educators and private traders to the analysts of trillion dollar funds on Wall St, they each have influenced Mathew as he continued to build products to help them. Today, Market Analyst Software has morphed into Optuma Financial Solutions, and while they still provide advanced software, their services have also expanded to offer education to both beginner and advanced students.Over recent years, Mathew has seen first-hand how many Technical Analysts are required to become more quantitative in their approach, with an understanding of Risk and Reward and statistics. Even seasoned Technical Analysts find it difficult to secure funds for a new technical idea without being able to define historical performance. As an Engineer, Mathew has been focused on finding solutions that will allow Technical Analysts to easily become more quantitative in their process.  

Swing Charts and Quant Analysis

Posted: 13 February, 2019 Subjects: Quant_Analysis&Trading
Source: C2019 MEL Available to: Members

Nearly 100 years ago, W.D. Gann called his 3 Day chart his Master Trend Indicator. It still stands the test of time and as one of Gann's most objective methods, it has a place in quantitative modeling. In this session Mathew will be presenting the reasons why we should be considering swing charts as a way to filter out market noise and signal generation. He will go on to explain the construction of different types of swing calculations like Point, Percent, Gann (what he called a 3 Day chart), Point & Figure, Kagi & Volatility. All of which have their pros and cons. Finally, Mathew will explain the various methods that are used to identify signals which can be derived from any swing trading method.

All too often a Technician's first foray into being quantitative is performing a back test. Statistically, this is one of the worst places to start a quantitative process. A back test that is performed too early is based on many false assumptions and compounds many errors into the process. The result is that the back-test returns are rarely repeatable in real life. In this presentation, Mathew will be explaining what these errors are, how we can avoid them (regardless of what tools you use) and reveal a new Monte Carlo method he developed which allows us to review a valid p-score for our models no matter if they are long term trend following or short term mean reversion strategies. Mathew will go on to explain how as Technicians there is a process that we can follow to rigorously test quantitative ideas. Mathew will use these methods to do a review of the various Swing Chart methods that he introduced in Session 1. He'll also show a method which mixes mean reverting signals and swing charts for some very interesting results. For any Analyst who wants to research new ideas or be able to present ideas that can stand up to rigorous quantitative scrutiny, this presentation will help you to see that not only is a quantitative approach is achievable, but as Technical Analysts, we are in the best position to drive advanced quantitative models.

Quantitative Technical Analysis Testing

Posted: 23 October, 2016 Subjects: Quant_Analysis&Trading
Source: C2016 IFTA Available to: Delegates 2016

Investment Professionals are under pressure to be more quantitative in their process. Many Analysts and PMs are continually asked to validate their signals, strategies, and money management practice. Very few have the time to learn coding languages, or the time and resources to hire and manage a programmer, but they still have an urgent need to test and benchmark new ideas on a continuous basis. In this presentation, Mathew Verdouw, CMT, CFTe will explore some of the issues above and illustrate a simple quantitative approach to validate different technical ideas and generate consistent reports that benchmark strategies without introducing the biases of traditional back-testing. Mathew will explain the most important statistical measures every technical analyst needs to know and what they really mean. Finally, he will show how to measure the true impact of Stops and Targets.

Cycle Identification, Inter-Market Principles and Relative Strength

Posted: 17 May, 2015 Subjects: Cycles Relative_Strength
Source: C2015 Available to: Members

No market should be viewed in isolation. Just as a single stock is affected by the stock market, so is the stock market by every other asset class. In this presentation, Mathew will explain some of the key things that we need to watch from an Inter-Market perspective and reveal how Relative Strength can be used to help in the identification of where we are in the cycle. Finally, Mathew will bring it all back to a portfolio level to show how professionals in Wall Street are using these types of techniques and the lessons that every private trader can take away.

Active Portfolio Construction using RRG's

Posted: 1 August, 2014 Subjects: Indicators
Source: P2014 Available to: Members

In this presentation, Mathew Verdouw will give a brief introduction to Relative Rotation Graphs (RRG) as a simple and clear way to view any group of securities in relation to a Benchmark in a single chart. He will then provide examples of how Portfolio Managers and Private Investors are using this technique in top down analysis and active Portfolio management. Regardless of the final analytical approach taken in security selection, RRGs are a simple way of identifying the securities that most require attention.