Editor’s note: this was originally published in the March 2001 issue of Technically Speaking.

With the proliferation of microcomputers and trading software over the past two decades, there has been a surge of interest by futures and equities traders in applying technical analysis to their trading decisions. Concurrently, a transformation has been underway, due in part to advancements in global telecommunications and information technologies, in which the financial markets have become increasingly globally interconnected and interdependent.

Despite the globalization of the financial markets, technical analysis is still directed primarily at analyzing each individual market by itself. This is done utilizing various technical indicators, many of which have undergone little, if any, change in their construction since first being applied by technicians decades ago. These include subjective charting analysis techniques such as head and shoulders, flags, pennants, and triangles, which attempt to find repetitive patterns in singlemarket data thought to be useful for

Editor’s note: This was originally posted at the New York Federal Reserve’s Liberty Street Economics, a site that “features insight and analysis from economists working at the intersection of research and Fed policymaking.”

Volatility, a measure of how much financial markets are fluctuating, has been near its record low in many asset classes.  Over the last few decades, there have been only two other periods of similarly low volatility: in May 2013, and prior to the financial crisis in 2007. Is there anything we can learn from the recent period of low volatility versus what occurred slightly more than one year ago and seven years ago? Probably; the current volatility environment appears quite similar to the one in May 2013, but it’s substantially different from what happened prior to the financial crisis.

For the three periods we consider, the chart below compares how low volatilities are across the following asset classes: two-year

The MTA Singapore Chapter Meeting was honored to host Alex Siew, Dr Sun, and Caner Seren Varol, CMT, CFA, ERP at the September 30th, 2014. There were over 110 market professionals and investors who attended the presentation making it a great success for this young and growing chapter.

Jamie Coutts, CMT, CFTe is the incoming Singapore Chapter Chair, taking over for newly elected MTA board member, James Brodie, CMT. Jamie opened the event with a welcome address that introduced the MTA and provided a brief overview of the CMT
Program. The guest speakers then took the floor covering a diverse range of investment topics.

Alex Siew, Fund Manager at VCB Capital presented “Detecting Reversal Points Using Traditional Indicators, Quantitative Tools and How to Systemize Your Process.” Dr Sun’s presentation was titled “Quantitative Approaches to

Ralph Acampora is an excellent lecturer and it was no surprise that he drew a large crowd to the Chicago chapter meeting last month. He gave us a rich perspective of what Wall Street was like 40 years ago, how he and a close friend and colleague cofounded the Market Technician Association, and most importantly the need of serious recognition for Technical Analysis or, as they were referred to back then, “chartists”. Ralph gave the audience a vibrant perspective of the history on the development of the MTA and TAN designation. He highlighted key events, important dates, and how the TAN Program became recognized as the premier designation for technical analysts worldwide.

Ralph then went on to share a presentation he will be giving in Kuwait later this month for Altaira Ltd, where he serves as the Director of Technical Analysis. The

Editor’s note: This was originally published on September 29, 2014 at WWW.JBECKINVESTMENTS.COM and is reprinted with permission.

ETF selection has been based upon a traditional approach to ETF research to incorporate the best suited benchmark domestic sector ETFs in a portfolio designed to outperform the overall US equities market. The analysis therein uses a classical technical approach to uncover trends, patterns, relative strength leaders, et al., in order to reveal the leading/lagging US equity sectors.

This unique dual approach to ETF research not only seeks to outperform but also to managed risk in your U.S. equity portfolio, while staying invested in a very challenging market.

Our methodology

A rigorous ranking methodology was used to select among broad based benchmark US sector ETFs. For the purposes of this asset allocation portfolio, ETFs tracking a strategy index methodology designed to “beat the market” or “become a market” were excluded from our selection process. Only

Other Winans Indexes include the Winans Real Estate Index™ (WIREI) and the Winans Preferred Stock Index® (WIPSI). The data is available through Global Financial Data, Metastock or Stockcharts.

The WIREI (Patent Pending 11/670,914) tracks new U.S. home prices since 1830. It’s unique approach rescaled and combined several well know government studies of U.S. new home prices into a continuous data set without the “gapping” and time lag problems found in other studies. The WIREI has several sub-indices: 1. Sales since 1962, 2. Inflation since 1932, 3. Home sizes (i.e., average square feet) since 1973 and 4. Geographic regions (Northeast, Midwest, South, West) since 1975. The WIREI is shown on the left.

The WIPSI was the first modern index to track these cornerstone securities. It is an evenweighted index that consists of 85