A Code of Ethics is one of the minimum requirements of a profession. Since its founding in 1974, MTA members have been required to adhere to a comprehensive Code of Ethics. The Code consists of a single page that defines the highest standards of ethics. Although it is brief, the Code is comprehensive and has met the needs of the Association.

If there is a shortcoming in the Code, it was that it did not include a large number of examples or provide additional study material For TAN candidates. This made ethics one of the more challenging topics to study for when preparing for the exams. The Code was clear and comprehensive but without examples, candidates for the exams often felt unprepared for the exams.

To address this concern, the Ethics and Standards Committee set out to develop a detailed Body of Knowledge related to ethics. In their research, they realized the

Long-time MTA member James G. Birmingham passed away on April 18, 2015 at the age of 84. Jim has been a member of the MTA since 1974.

Two of the defining characteristics of Jim’s life were his love of his family and the markets. He spent 59 years working in the markets yet his resume can be condensed into just three lines. Jim served in the Navy, worked briefly for a broker and then managed money through a hedge fund. Just three positions over six decades.

Jim was born in Boston on June 30, 1931 and graduated from Boston College in 1952.  From 1953 until 1956, he served as a Lieutenant JG in the United States Navy during the Korean Conflict. After leaving the Navy, Jim started as a broker in Boston with Proctor Cook and Company. As he recalled years later:

“I

Editor’s note: Milton Erzati was one of the presenters at the recent Annual Symposium. His presentation included some of the information in his book which is reviewed here.

Thirty Tomorrows starts with well-known, bearish demographic facts and then demonstrates that the outlook is actually bullish. Milton Erzati is an economist who does an excellent job summarizing the challenges the global economy faces.  Any economic data series can be presented on a chart and as Erzati points out, it can be used to develop a forecast but the right side of the chart (the future) is uncertain and is likely to provide upside surprises. That’s an important point that is often overlooked. Many forecasts consider downside surprises but the upside surprises are often overlooked although they are usually just as likely to occur.

The demographic data Erzati focuses on can be summarized in the dependency ratio, a measure showing the number of dependents

Editor’s note: this was originally posted at Inovancetech.com and is reprinted her with permission. Inovancetech is offering the free use of an algorithmic trading platform to MTA members

Artificial intelligence, machine learning, data mining and big data seem to get thrown around in everything from business intelligence to financial services.

Artificial intelligence is used where machine learning should be and machine learning is often confused with data mining. The goal of this post is to clarify these buzzwords, explore how they apply to trading and then explore an ideal subcategory of data mining for traders.

Clarifying the Buzzwords

Artificial intelligence, a subfield of computer science, has three main subcategories; machine learning, curated knowledge and reverse engineering the brain. Machine learning is a method of developing algorithms for recognizing patterns within data. Data mining, also a subfield of computer science, is the whole information discovery process; from preparing and cleaning data to analyzing to post

We all learn the basics of technical analysts differently. Some of us read the classics and think about how those ideas still apply to the current markets. Some of us find mentors who explain the important concepts to us. Some of us prefer traditional classrooms and other like self-paced video courses. No matter how we learn technical analysis, the next step is to apply the knowledge.

Kase on Technical Analysis is a one-stop training source. Cynthia covers the basics, puts them all together into a coherent trading strategy and then provides tests so you can apply the knowledge without risk in the markets.

The big question is who would benefit from this material. The answer is anyone wanting to learn about technical analysis, anyone studying for the CMT exam and anyone wanting to learn about the Kase suite of indicators or strategies. CMT

Point and Figure (P&F) is one of the oldest tools of technical analysis. It’s been used since at least the 1880s yet the technique works just as well today as it did 130 years ago. The basics of P&F haven’t changed over time but computers and software have allowed skilled analysts to derive more information from the columns of Xs and Os that are found on P&F charts.

In this book, du Plessis demonstrates how to apply 20th century tools like Bollinger Bands®, Donchian channels and Welles Wilder’s parabolic stop and reverse strategy to P&F charts.

Below are examples from the book showing how Donchian channels could be applied to P&F charts. Donchian channels were developed by Richard Donchain in the 1960s. They consisted of two lines on a price chart. One line showed the highest high over a time period, usually 20 days or 4 weeks. The second line showed the

Editor’s note: This was recently published at Alvarez Quant Trading and is reprinted here with permission. A spreadsheet with the complete results of this strategy is available at the web site.

My recent research has been in ETFs which I have not explored in several years. ETF sector rotation has always intrigued me. The idea seems so simple that it should work. Always be in the sector that has been doing the best. I like simple but does it work? If not, can we make it work?

ETF Universe

For these test, we will using the Select Sector SPDR ETFs. They have a long history. The list is

• Consumer Discretionary (XLY)
• Consumer Staples (XLP)
• Energy (XLE)
• Financials (XLF)
• Health Care (XLV)
• Industrials (XLI)
• Materials (XLB)
• Technology (XLK)
• Utilities (XLU)

Testing will be from 2005 to 2014.

Baseline

Our baseline will be buy and hold on the SPY. My typical goal when trading ETFs is to beat CAGR of Buy & Hold by 50% but with

Editor’s note: this was published in late-April and is presented as an example of long-term technical analysis.

Two weeks ago our Market Comment summarized the big picture for the 2009-2015 bull market. We concluded that after a 97% gain over nearly three and a half years, the markets were due for a well deserved rest. While some market analysts expect a big correction or even the end of the bull market after such a strong advance, our view is that the markets can remain bullish and “correct” by marking time within a relatively narrow trading range.

What has happened so far? The S&P 500 has moved sideways for two months. Last Friday’s decline, caused mainly by being both option-expiry day and the end of the 70-day cycle, was contained comfortably above the 1,975 to 2,025 zone that we highlighted last time. On Monday the loss was recovered.

As the S&P 500 moves sideways,

Technical analysis has been used by traders for centuries. But it has only been taught as a for-credit course at universities since 1996. In that year, the MTA Educational Foundation partnered with the University of Richmond to teach “Technical Analysis and the Securities Market” to undergraduates.

Dick Dickson, CMT, was the instructor in 1996. Dick worked with Professor John Earl, who is now Chair of the University’s Finance Department, Ralph Acampora and Martin Pring to introduce the course to the school. With Dr. Earl’s assistance, a presentation to the Dean was completed and the course which focused on the practical application of technical analysis to the markets was immediately approved.

In addition to learning from Dick, students were provided with insights from some of the country’s leading technical analysts. Ralph Acampora, CMT, Steve Nison, CMT, Alan Shaw, CMT, Phil Roth, CMT and Martin Pring presented as guest lecturers.

One of the students in