Technically Speaking, July 2010

Letter from the Editor

Little has been written about Ichimoku Clouds, which were first used in the 1930s. They are visually compelling, yet little used in the world of technical analysis. In recent months, two books have been published exploring this topic. We have reviews of both in this month’s issue of Technically Speaking. Prior to the publication of these books, one of the most authoritative pieces on Ichimoku Kinko Hyo may be an article written by Véronique Lashinski, CMT, and published in the Journal of Technical Analysis (http://www.mta.org/eweb/dynamicpage.aspx?webcode=journal2008#section05). MTA members have always produced groundbreaking researching.

Lashinski’s paper is just one example of the type of work that our members produce. In the newsletter this month, we offer another example of cutting edge technical analysis with David Waggoner’s article exploring the May Flash Crash. While regulators are still looking at what happened and how to prevent, Waggoner offers a practical insight into the crash.

Finally, High Growth Stock Investor recently released a new version of their software. They did this almost at the same time we published a review of the older version last month. We are fortunate to be able to offer details on their product. This company is a long-time supporter of the MTA. They offer a 60 day trial to High Growth Stock Investor for free. This includes the software and daily EOD updates to a database of over 8,000 (NYSE,NASDAQ,AMEX) securities, major market indexes, mutual funds and commodities. After the trial period, they will offer a discount from our $59/month rate to $49.00/month for the first 12 months plus a 6 month free subscription to the Woodward and Brown Newsletter and Video, normally a $200.00 annual subscription. For the 60 day free trial, go to www.highgrowthstock.com/MTA.

Many other companies support our organization. Please take a moment to look at them by visiting http://www.mta.org/eweb/dynamicpage.aspx?webcode=membership-discounts

Sincerely,
Mike Carr, CMT

What's Inside...

Technical Analysis as a Forensic Tool in the Investigation of the Flash Crash

David Waggoner, CMT

I am fascinated by the rapid decline and complete recovery that took place in less than 15 minutes exactly one...

Analyzing Markets with Ichimoku Clouds

Manesh Patel, CMT, CFTe

The following example demonstrates how to apply this technique in real time, prepared by Manesh Patel, CTA. It was originally...

"Cloud Charts: Trading Success with the Ichimoku Technique" by David Linton

David Linton, MFTA

Michael Carr, CMT

Japanese Candlesticks are well known, and widely used. This technique traces its origins...

"Trading with Ichimoku Clouds: The Essential Guide to Ichimoku Kinko Hyo Technical Analysis" by Manesh Patel, CTA

Manesh Patel, CMT, CFTe

Michael Carr, CMT

Manesh Patel uses his book to bring you next to him at...

High Growth stock Investor, Version 7

David Steckler

In the June 2010 issue of Technically Speaking I reviewed Version 6 of High Growth Stock Investor (HGSI) software. Industry...

Trade: A Platform Independent Language for Traders

John Bollinger, CMT, CFA

In my presentation at the MTA symposium — kudos to Jeff Lay and Jeremy Berkovitz for a job really well...

Call for Nominations

As Chairman of the MTA Awards Committee, I solicit your nomination(s) for consideration in the two categories — MTA Annual...

MTA Announcements

MTA Office Announcement

In observance of Independence Day (US), please note that Friday, July 2nd the MTA Office...

Technical Analysis as a Forensic Tool in the Investigation of the Flash Crash

I am fascinated by the rapid decline and complete recovery that took place in less than 15 minutes exactly one month ago today on May 6, 2010 coined the “flash crash”. Even with the gloomy global economic back drop since then, it has taken the S&P 500 a full month to close lower than the downward spike of that event which originally occurred in two to three minutes. In over ten years of studying the markets on a daily basis I have never seen anything like it. I have spent the last few weeks studying the flash crash for evidence that could lead to an explanation of how it happened.

I started my research after reading the Preliminary Findings Regarding the Events of May 6, 2010by the SECCFTC Joint Regulatory Committee. The report is 80 pages long with another 100 pages of appendices. The report includes excellent research and is chock full of interesting facts and clues about the “flash crash”.

The report concluded that a confluence of economic events, market forces, and trading system functionality led to a significant dislocation of liquidity as measured by broken trades, bid/offer spreads, self-help declarations, and outsized ETF factors. Furthermore, due to the complexity and extremely tight linkage between the various market products, a detailed market reconstruction of hundreds of millions records, from dozens of different sources, comprising five to ten terabytes of data, consuming a significant amount of staff resources, was required to sequence the events of the flash crash.

The last part captured my attention. The idea occurred to me that technical analysis, specifically, ratio analysis, could provide a short cut to a high probability answer of where the flash crash originated.

Ratio analysis in charting is most often used to determine relative strength between two markets or two securities. It is commonly used to show a specific stock’s relative strength compared to the index in which it is a constituent. My idea was that if I applied it to one minute charts leading up to and during the flash crash, I might be able to identify the relative strength of the market linkage between futures, stocks, and ETFs during the crash. If this worked, then I would further be able to determine the likely sequence of events, and even isolate the weakest link in the flash crash.

Chart 1 shows the moments leading up to, and during, the flash crash at 2:45pm on May 6, 2010, and in my opinion paints a clear picture of the order of events between the major indexes and those indexes and their respective futures markets:

At 2:43pm the Nasdaq100 Cash index diverged lower on a relative strength basis to the Nasdaq100 EMinis. The Nasdaq100 E-minis remained stronger than the S&P500 E-Minis, and the S&P500 cash index remained stronger than the S&P500 E-Minis.
At 2:44pm the Nasdaq100 Cash index spiked down hard relative to the Nasdaq100 E-minis, the S&P500 E-minis turned down relative to the S&P500 cash, and the Nasdaq100 E-minis turned down relative to the S&P500 E-Minis.

CHART 1

At 2:45pm the Nasdaq100 cash index relative to the Nasdaq100 E-Minis that had fallen hard for two minutes stopped and reversed, The S&P500 cash index spiked lower relative to the S&P500 E-Minis while the Nasdaq100 E-minis remained weaker than the S&P500 E-minis.
From 2:46-2:48 the Nasdaq100 cash and Nasdaq100 E-minis ratio balances out and the Nasdaq100 EMinis diverge sharply higher relative to the S&p500 E-minis that are still suffering from the S&P 500 Cash index sell off. At 2:46 the S&P cash index stops and reverses relative to the E-minis.

Chart 1 indicates that the cash markets were weaker than the futures markets during the moments of the flash crash and the Nasdaq-100 futures were weaker than the S&P futures. Chart 2 below highlights just the ratio between the Nasdaq-100 cash index and the S&P500 cash index during the price decline. It highlights that the Nasdaq-100 cash index spiked dramatically weaker than the S&P500 cash index at minute 2:43 and remained weaker until minute 2:46pm when it reversed just as dramatically.

CHART 2So far, I have presented good evidence that the Nasdaq100 Cash was the weakest link in the chain of events that lasted only a few minutes on May 6, 2010 and is now called the “Flash Crash”.

The only remaining comparison is against ETFs and Chart 3 depicts the relationship of IWM, the #1 broken ETF during the Flash Crash (by trades and volume), to the NASDAQ-100 on a relative strength basis. During the same pivotal moment of the crash, IWM spikes higher, confirming that the NASDAQ-100 on a relative basis spikes lower at that moment.

CHART 3

Using ratio analysis as a forensic tool, I was able to determine that the Nasdaq-100 cash index was the weakest link during the flash crash.

Coincidently, the joint SEC-CFTC report identifies several crash facts about the NASDAQ (dispersed throughout the report) that are consistent with this thesis.

While ETFs are highlighted as a key factor in the report representing the largest number of securities with broken trades, NASDAQ-listed stocks have more than twice as many actual broken trades (12,306) as ETFs (4,903) and are not highlighted as a key factor.
May 6th volume on NASDAQ-listed stocks was the highest ever on record
The NASDAQ was the only exchange to declare self-help and did so several moments before the crash

Believing that I was onto something significant, I focused my lens even more on the NASDAQ-listed stocks. I recalled something that I originally read it in the SEC-CFTC report that didn’t immediately register to me as significant. Now it did.

APPLE was the #1 top broken stock by trading volume during the Flash Crash. To truly appreciate the significance of this you need to reflect on market capitalization. As market caps go, Apple is a titan among the minnows. In fact, the NASDAQ lists it as one of only two mega-cap members (the other is MSFT). Apple has the second largest market cap of any US listed security. Only Exxon Mobile is larger, and not by much.

Market capitalization is so significant it is the basis for most market indexes. The premise of a market capitalization index is that the stocks with the largest market capitalization (and shares outstanding) are more stable and therefore given more weight than the smaller stocks with fewer shares outstanding.

In a market capitalization weighted index, each stock is weighted by its market value. Most market indexes including the NYSE, S&P500, NASDAQ Composite, NASDAQ-100, and all Russell Indexes are market capitalization weighted. As stocks come and go and market caps rise and fall, indexes are rebalanced to reflect the changes. When a stock’s market cap grows continually for an extended period of time its percent value of the index grows proportionally. For this reason index owners have rules for rebalancing their indexes.

The NASDAQ-100 is not rebalanced very often. In fact, the last rebalancing of the NASDAQ-100 was in 1998 when Microsoft grew too big too fast. What is too big? The following excerpt is taken from the NASDAQ-100 Index Methodology document on the NASDAQ website:

“On a quarterly basis coinciding with the quarterly scheduled Index Share adjustment procedures, the Index will be rebalanced if it is determined that: (1) the current weight of the single largest market capitalization Index Security is greater than 24.0% and (2) the “collective weight” of those Index Securities whose individual current weights are in excess of 4.5%, when added together, exceed 48.0% of the Index. In addition, a special rebalancing of the Index may be conducted at any time if it is determined necessary to maintain the integrity of the Index.”

When Microsoft’s hefty weighting was redistributed in 1998, AAPL and other smaller corporations received fractional percentage points from Microsoft’s rebalancing. Since then, Apple’s market cap has grown significantly and its weighted percentage of the NASDAQ-100 index has grown along with it. However, because the rebalance conditions have not been met, the index has not been rebalanced.

The following table shows the top ten weighted stocks of the NASDAQ-100 index. The weightings (Market Percent) are the actual weightings given to each stock in the NASDAQ100 for month end May, 2010. May 6th market values were probably higher for many stocks in the index, but Apple, which is the point of my discussion, was about the same.

Look at market percent of AAPL. Apple stock weighs in at 19% of the NASDAQ-100 index. This is not an error. Now look at how much Apple dropped on May 6th. I show the calculated impact that AAPL alone had on the NASDAQ-100 that day. This is more than a red flag; this is a smoking gun. It could likely be the spark that ignited the fire that brought down the house.

I still needed to test the relative strength of AAPL to the Nasdaq-100 during the flash crash to complete my analysis. Chart 4 shows the NASDAQ-100 index, AAPL, and the relative strength (ratio analysis) of Apple to the NASDAQ-100 on a one minute chart in the moments leading up to, and during, the Flash Crash. What ratio analysis shows is that at 2:44 pm on May 6th, 2010, AAPL spiked down hard relative to the index itself. In other words, Apple was MUCH WEAKER than the index during the Flash Crash, or conversely, much stronger to the downside than the index.

CHART 4

In summary, using ratio analysis on one minute charts I have shown with a high level of probability that the NASDAQ-100 was the weakest link during the Flash Crash. Apple represents almost 20% of the weighting of the NASDAQ-100 and was significantly weaker than the index during the key moments of the crash. It is logical to interpret that Apple pulled the index down with it, rather than vice versa and should be the focus of further study.

Relative strength measured by ratio analysis on one minute charts provides a surprising level of detail about the Flash Crash that cannot otherwise be interpreted. I believe that this innovative use of ratio analysis is critical to understanding the compressed events of the Flash Crash.

David Waggoner is a Chartered Market Technician (CMT) and member of the Market Technicians Association. He is the founder of TheMarketDetective.com and a frequent contributor to Minyanville.com.

This paper is a compilation of articles that were originally published at Minyanville.com and posts to David’s blog at http://blog.themarketdetective.com

Contributor(s)

David Waggoner, CMT

David Waggoner, CMT, is the founder of TheMarketDetective.com and uses the Elliott wave principle and Fibonacci ratio analysis to uncover clues about the direction of the market. He then uses other forms of technical analysis to corroborate his findings in such a...

Analyzing Markets with Ichimoku Clouds

The following example demonstrates how to apply this technique in real time, prepared by Manesh Patel, CTA. It was originally published at http://www.ichimokutrade.com/?p=727 on June 10, 2010.

Ichimoku Currency GBPCAD Forex Trade Setup: 6-10-10

GBPCAD consolidating and has a chance to break either way. The trend is bearish but can move into a pullback mode off the consolidation pattern. As a result, we are going to setup two trades. One a counter trend trade with very little risk and another for a continuation trend trade.

Here is the counter trend trade setup. It is a bullish trade off the 30 minute timeframe. It keeps our risk very low. Notice, we are not trying to get huge profits because this is a pullback off the major trend.

Here is the continuation trend trade. We are going to setup everything off a 120 minute chart to try to keep our risk low since we are in a minor consolidation pattern.

For EDUCATIONAL USE. Commodity Futures Trading Comission, Forex, Futures, Equity and options trading has large potential rewards, but also large potential risk and may not be suitable for everyone. You must be aware of the risks and be willing to accept them in order to invest in these markets. Do not trade with money you can not afford to lose. This is neither a solicitation nor an offer to Buy/Sell. No representation is being made that any account will or is likely to achieve profits or losses similar to those discussed on this document. The past performance of any trading system or methodology is not necessarily indicative of future results. All information provide d on the Blog is for educational purpose.

Manesh Patel, CTA will be hosting a presentation on this topic as part of the MTA Educational Web Series on September 15, 2010 at 12 Noon EST. To learn more about Analyzing Markets Using Ichimoku Clouds, we encourage you to register for this webcast as soon as it becomes available!

Contributor(s)

Manesh Patel, CMT, CFTe

Manesh Patel, who holds a Chartered Market Technician (CMT) designation, is the President and Co-Founder of IchimokuTrade and a veteran quantitative trader. He is the author of the book Trading with Ichimoku Clouds: The Essential Guide to Ichimoku Kinko Hyo Technical Analysis,...

"Cloud Charts: Trading Success with the Ichimoku Technique" by David Linton

Japanese Candlesticks are well known, and widely used. This technique traces its origins back several hundred years, and became popular in the United States in the 1990s, based upon the work of Steve Nison, CMT. Linton follows in the footsteps of Nison and is presenting Ichimoku Clouds based upon the original Japanese texts, which date back into the 1930s.

The first part of the book is a review of basic technical analysis concepts, approximately one hundred pages that offer an overview of some of the most important concepts. These summaries are found in many books, and I always find them valuable and think they make good reading for CMT candidates. Linton’s review goes a little beyond the ordinary and includes short discussions on important and advanced ideas like correlation and spread charts. He also explains how to add a moving average to a point-and-figure chart. If the reader stopped here, there would still be enough new ideas for even the most experienced technician to spend weeks testing and implementing some novel insights.

In the second part of the book, Linton explains what a Cloud chart looks like, how to construct the charts, and how they can be interpreted. In his words:

“The construction of the Could Chart is summarized as follows:

Turning Line – midpoint of the high and low of the last 9 sessions.
Standard Line – midpoint of the high and low of the last 26 sessions.
Cloud Span A – midpoint of turning line and standard line shifted forward 26 bars forward.
Cloud Span B – midpoint of the high and low of last 52 sessions shifted 26 bars forward.
The Lagging Line – the price line (close) shifted back 26 bars.”

An example of the Cloud, taken from the author’s website (www.cloudcharts.com) is shown below.

While there appears to be a lot of lines in the chart, the interpretation of the Clouds is actually fairly straightforward. Again quoting from the author:

Prices above the cloud means a bullish picture.
Prices below the cloud means a bearish picture.
Prices in the cloud are bullish if they came from the bullish zone.
Prices in the cloud are bearish if the came from the bearish zone.
Historically thick clouds after a run in prices might signal an imminent trend change.
The lagging line crossing the cloud is the main signal of a trend change.

Of course there are more detailed interpretations that he explains in the book. While presenting the ideas in a simple and straightforward manner, Linton makes sure each topic is fully explained. He focuses on the practical application of Clouds and his book is a study manual for those seeking mastery of the techniques.

The third and final part of the book addresses how to implement Ichimoku Clouds, building on many of the concepts introduced in the first part. They can be integrated into a trading strategy, and he offers some backtested results to help boost the confidence of the reader in Clouds.

Linton introduces a subject that many technicians are unfamiliar with, but by the end of the book has delivered enough information to allow traders to immediately add the technique to their toolbox. Clouds are a tool that allows the trader to confirm a significant trend change fairly quickly after the top or bottom has formed.

Contributor(s)

David Linton, MFTA

David Linton is the founder and Chief Executive Officer of Updata, an analytical service that aims to deliver the best technical analysis software running on as many data sources as possible. Professional traders and analysts now use Updata’s services in over forty...

Michael Carr, CMT

Mike Carr, who holds a Chartered Market Technician (CMT) designation, is a full-time trader and contributing editor for Banyan Hill Publishing, a leading investment newsletter service. He is an instructor at the New York Institute of Finance and a contributor to various additional...

"Trading with Ichimoku Clouds: The Essential Guide to Ichimoku Kinko Hyo Technical Analysis" by Manesh Patel, CTA

Manesh Patel uses his book to bring you next to him at his trading desk. He begins by describing what a trading system, and then describes the Ichimoku technique before walking through trades, step-by-step. The result is well-written book that offers insight into how to create a checklist for any trading technique and a detailed guide on using Clouds to trade.

A trading plan is actually a simple set of rules to guide you through the markets. Patel identifies four general areas:

What instruments will be traded and when?
Entry rules
Money management
Trade Post Analysis

Each topic requires a great deal of thought, and he presents a process designed to take the trader to a decisive action plan. His last step, Trade Post Analysis, is rarely mentioned in the many books and articles written about trading. Patel emphasizes, :…post analysis of the trades has to be maintained to verify that the system will produce the long-term goals of your business.” This is typical of the type of insight he offers throughout this book – treat trading as a business and follow a disciplined approach to have the best chance at success. The book uses Ichimoku Clouds as an example of how to develop long-term disciplined trading decisions. Readers can adapt the approach to their favorite tools.

Patel presents Clouds using the original Japanese terms, highlighting the culture behind this tool. The Ichimoku Kinko Hyo system is made up of five components (each is shown in the figure below):

Tenkan Sen, shown in red
Kijun Sen, shown as the green line
Chikou Span, the light purple line in the figure
Senkou A
Senkou B

Each component is calculated with a simple formula that can be programmed within moments into any trading platform. The book explains everything that is needed to use Clouds in trading. They can be used as a stand alone strategy, or easily combined with other tools. With little effort, either approach can be programmed and tested. The ability to run a backtest on the concept makes it especially appealing.

This is a very visual approach to trading, but the rules can be distilled into a checklist. An appendix in the book includes a four page checklist that can be used to answer the questions on entry rules in the trading plan. While Patel does an excellent job describing the technique and the general trading rules, the heart of the book are the trading examples he walks through step-by-step. In detail, he explains the logic behind the trade decisions, and this helps the novice trader answer the question of what trading really is. The more experienced technician will see the application of a new technique, and enjoy seeing the thought process of a fellow
technical trader.

Contributor(s)

Manesh Patel, CMT, CFTe

Michael Carr, CMT

High Growth stock Investor, Version 7

In the June 2010 issue of Technically Speaking I reviewed Version 6 of High Growth Stock Investor (HGSI) software. Industry Monitors recently unveiled a major upgrade to the platform. Version 7 of HGSI implements a new system software architecture enabling High Growth Stock Investor to evolve into an Application Trading Platform.

HGSI offers a collection of seamlessly interactive tools designed to simplify the process of selecting candidate stocks to buy and sell. HGSI simplifies the process of finding the “What, Which, When, Why, and So What” that feed your decision-making efforts. Its goal is to create an intelligent user faster.

HGSI is an end-of-day application that screens the universe of stocks to find those most likely to outperform the market. Data is provided by Quotes Plus (QP2). The user can utilize either a top-down or bottom-up approach.

The top-down approach is one which moves from Markets to Sectors to Industry Groups to Stocks in the search for strongest stocks in the strongest industry groups. Groups can be any collection of securities or indexes that have meaning to the user, e.g. baskets, industries, market sectors, portfolios, indices, exchange traded funds, etc. Using ranking tools for acceleration, velocity and relative strength you are able to find groups of stocks that are moving up or down faster than other groups.

The bottom-up approach defines certain characteristics and then filters out any candidates that do not meet those criteria. It does not dwell on groups, sectors or industries, focusing instead on the desired characteristics of each security.

HGS Investor Software Features

The Housekeeping Features

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HGSI offers a detailed help system installed with your software. You can display the Help system from the “Information” icon. You can also click on the Help menu option or Help button on a dialog box. Information also includes links to the Learning Center, HGS Website, a very active HGS Bulletin Board, and Member Services.

“Preferences” maintains your HGS Account information and enables you to set your Global Index options, including the Index Type (e.g., Average Price or Equal Dollar Weighted), which filter to apply, if any, and the start date for indexing.

“Update” initiates an update of the various HGS Investor databases and includes the QP2 download. You may elect to run these updates manually or schedule them to run automatically at a selected time.

Managing Lists with the Designer

The Designer customizes the groupings of stocks for your own needs and preferences and displays a set of group databases containing three types of groupings:

The HGS Reference Groups item contains the Investors’ Data Repository listing standard industry reference groups, such as AMEX, NASDAQ and so forth. Symbol changes and new stock additions are incorporated into the database via Update. You cannot modify this data in any other way.
The User Groups item allows you to copy the data from the HGS Reference Groups or to create your own personalized groups of stocks, such as watch lists and custom portfolios. This grouping allows you to create, modify and experiment without altering the HGS Reference groups. With new users or “clean” installs, the User Groups item is empty when you first install the software and the views, filters and combo ranks are found in the HGSI Classic and HGSI Applications folders. If the user is upgrading from version 6, the Version 6 filters, views and combo ranks are moved into Version 7 “User” folders.
The SmartGroups are daily lists of top stock selections generated by the Designer HGSI Group Database software. The lists are updated daily and organized into a variety of HGSI Groups.

The Productivity Features

Warehouse, Ranking and Charting are the productivity features within which you perform most of your analysis work. They help you to decide what stocks, groups and industries are the current best performers, which are the strongest, and finally when you should invest.

The “Warehouse” enables you to set your own criteria to determine what stocks, groups or indexes are the best performers. By creating filters based upon your own criteria, you use the Warehouse as a Data Mining Center to draw potential winners from the original reference list of over 8000 candidate stocks in 154 Industry Groups, 10 Sectors in which the industry groups are located, and 3 Markets (NYSE, AMEX, Nasdaq). Using a pre-designed list of fundamental and technical data you build views and filters reflecting the criteria important to you.

“Ranking” indicates where the money is flowing by measuring the internal relative strength of an index or security and computing its rank among similar securities or indexes. Using color-coding, it visually identifies group and sector rotation.

Once you identify what to buy, “Charting” helps you decide when to buy. Charts indicate the “attitude” of traders toward the stock and group using MACD, Candle Charting, Group Strength, Revenue, Earnings Per Share and other important indicators.

Version 7

I described HGSI as having evolved into an Application Trading Platform. “Applications” are defined to mean trading methodologies developed by experts in the investment world or by customers using the platform to develop their own methodology. The chart below depicts the layout of the platform:

p12

The four Choose/Create Windows used in the Warehouse, Charting, Filter and Combo Rank have been redesigned to allow folders. Within each of these four windows there are a standard set of three folders: HGSI Applications, HGSI Classic and User. Each window is described below.

The User Folder: When Version 7 updates a Version 6 copy of HGSI, the Version 6 filters, views and combo ranks are moved into Version 7 “User” folders. Nothing is lost. Notice the consistent look of Version 7 windows in the snippets shown below. When Version 7 is installed new, filters, views and combo ranks appear in the HGSI Applications and HGSI Classic folders.

p13

The HGSI Classic Folder: In the Warehouse, HGSI Classic comes with a variety of basic ready-to-use views that are grouped into areas of interest. Each view is already setup with a HGSI Filter to scan the database and create a list of stocks. Each view also has a Combo Rank that will sort and bring the best choices to the top of the list.

Filters are important tools for data mining because they enable you to weed out all but the stocks that are most important to you. Think of data mining as a means of getting to the gold. Once you create a filtered list inside one module, you can open that filtered list in any other. A primary function of filters is to cut the Warehouse down to size. In order to keep the data simple enough to analyze, use filters to ultimately select a small number of stocks from 8000-plus, and a focus on a few groups from 154.

p14

Combo ranking computes weighted values for each data field selected by the user and then combines all the weighted values. If the user wants to overweight or underweight a particular data field, e.g., overweight EPS for the most recent two quarters, she has the ability to do so. Combo ranking values can then be displayed in two data fields called Combo Ranking and Raw Combo Ranking. Combo Ranking uses the same 1-99 ranking system that is used on other Ranking data fields. The Raw Combo Ranking data field shows you the value from the actual computation for greater accuracy.

The HGSI Classic Folder: In the SmartGroups, HGSI Classic uses the same Filter and Combo Rank that are used in the Warehouse HGSI Classic Folder. The difference is an index is created for each group and placed in the area of interest folder. With the indexes, you can perform comparative analysis. These SmartGroups lists are also setup to only give you the top 10 stocks. The Warehouse will give you the entire list.

p15

The HGSI Applications Folder: In the Warehouse, HGSI Applications is where you find popular advanced methodologies that have been developed by experts in the industry and implemented on the HGSI Trading Platform. Examples are Woodward and Brown, Larry Connors, and Charles Kirkpatrick. Apps are the growth area for the HGSI Trading Platform. More will be added and announced as they become available.

p16

The HGSI Applications Folder: In the SmartGroups, the HGSI Applications use the same Filter and Combo Rank that are used in the Warehouse HGSI Application Folder. The difference is an index is created for each group and placed in the area of interest folder. With the indexes, you can perform comparative analysis.

p17

Charting and Warehouse Windows: A new Quick Pick View Window that remains open, making all the Charting and Warehouse Views immediately visible for fast selection of different views. Just click on desired view to see it in the Charting or Warehouse Windows. These “floating” view windows are resizable and can be moved anywhere on your desktop.

The image below shows the Quick Pick View Button on the Charting Window and images of the Quick Pick Charting and Warehouse Views. The same button is on the Warehouse Window.

p18

Web-Help: This is a new documentation system for Charting Views, Warehouse Views, Filters and Combo Ranks provided with the platform. Select a specific view, filter or combo and press the web-help button. This will take you to a web page where videos, documents and other information about the filter, view or combo rank you selected will be provided.

p19

Each of the four Choose/Create Windows for Filters, Charting Views, Warehouse Views and Combo Rank has one of these buttons.

p20

Unchanged is the price of HGSI: $599 per year. Also unchanged is the trial which gives you:

Sixty days FREE use of the software;
Sixty days FREE data from Quotes Plus;
Monthly newsletters;
Educational articles by Ian Woodward containing details on HGS Investing;
A series of getting started videos that teach you the basics of using the HGS Investor Software;
Weekly Reports containing market analysis and HGS investing news; and
Access to the HGS Learning Center containing tips and FAQ’s.

One of the best features of HGSI is that all updates/new versions of the software are free once you are a subscriber. A very flexible and powerful application is now even better and more user-friendly with this latest version.

Contributor(s)

David Steckler

David Steckler worked in the financial industry for 24 years, managing investment portfolios for institutional clients and hedge funds. He retired in 2011. His interest in technical analysis began in 1987 when he read William O’Neil’s book, “How to Make Money in...

Trade: A Platform Independent Language for Traders

In my presentation at the MTA symposium — kudos to Jeff Lay and Jeremy Berkovitz for a job really well done — I mentioned Trade and there was quite a lot of interest expressed in the project. Trade is a functional language. At its lowest level it is object oriented and recursive. At higher levels it is much like English or any other natural language, which means that the end user need not be aware of the details. For example, they could say something like:

Low level:
spy = close(spy)
and(spy > average(spy, 10, exp), spy[-1] < average(spy, 10, exp)) * buy(spy, 100, market)

Somewhat higher level:
spy = close(spy)
if

spy > average(spy, 10, exp) and spy[-1] < average(spy, 10, exp)

then

buy(spy, 100, market)

end if

Or, in some thing closer to natural language:

Close = close of spy
If close is greater than average(close,10, exp) and close[-1] is less than average(close,10, exp)[-1] than buy
(spy, 100, market)

Or, ever more intuitive:

If the close of SPY today is greater than its 10-day average and yesterday the close was less than its 10-day average than buy 100 shares at the market.

In any of these cases Trade via its interpreters could prepare language for your trading/analysis platform and/or put it into a standardized form for clear communication.

The point is to allow clear and unambiguous communication of ideas from trader to trader, from trader to machine, from analyst to system developer, in our journals, via our email list and so on.

That touches the surface of what we’d like to do. If you would like to work on Trade, drop me a note at BBands@BollingerBands.com with the word Trade in the subject.

Contributor(s)

John Bollinger, CMT, CFA

John Bollinger is President and Founder of Bollinger Capital Management, Inc., an investment management company that provides technically-driven money management services and develops proprietary research for institutions and individuals. He is probably best known for his Bollinger Bands, which he developed in...

Call for Nominations

As Chairman of the MTA Awards Committee, I solicit your nomination(s) for consideration in the two categories — MTA Annual Award and MTA Service Award.

The Committee carefully evaluates nominee’s credentials, reputation and contributions to market analysis (whether the analyst is living or deceased) in choosing its recommendations to the MTA Board of Directors.

It’s important that your nomination(s) include all the information that should be considered by the Committee.

Please address your submissions to: BBands@BollingerBands.com

Thank you in advance for your participation.

Respectfully,
John Bollinger, CFA, CMT

Contributor(s)

MTA Announcements

MTA Office Announcement

In observance of Independence Day (US), please note that Friday, July 2nd the MTA Office will be closing early around 2 PM EST. In addition, the MTA Office will also be closed Monday, July 5th. Of course the website will still be accessible for CMT and event registration

MTA Regional Seminars/Meetings – Agendas Available!

The MTA is pleased to announce that the agendas for all four events listed below are now
available.

- August 9th – United Kingdom Initial Event (London)
- August 10th – Netherlands Initial Event (Amsterdam)
- September 18th – US West Coast Regional Seminar (San Francisco, CA)
- October 1st – US Mid-West Regional Seminar (Columbus, OH)

Registration is now open. Sign up early! For more information on these events, including
agendas, speakers, and registration instructions, please click here.

MTA Educational Web Series – Next Upcoming Webcast!

Registration is now open for the presentation “Planes, Trains & Automobiles – A Study of Various Market Thrust Measures” featuring Wayne Whaley, CTA on July 7th at 12:00 PM EST. Wayne joined Witter & Lester Inc, a Huntsville, Al. based Commodity Trading Advisor, in 1993 as a research analyst and became a partner in 1999. Wayne trades the company’s assets but the majority of his efforts are in research activities to support trading. Mr. Whaley’s forte is the implementation of his engineering background in the development of pattern recognition techniques, along with the ability to backtest multitudes of combinations of candidate market strategies. Wayne is the recipient of the MTA’s 2010 Charles H. Dow Award. To register for this webcast please click here. To view the entire schedule of upcoming webcasts please visit the Educational Web Series page at mta.org.

MTA Podcast Series – Next Upcoming Podcast!

The MTA is pleased to announce the interview featuring Jeff Cheah, CMT (July 13th) will available through the Podcast Series. Jeff is the Chief Technical Analyst at Thomson Reuters Americas. He joined Reuters in 2006. He presents and teaches Technical Analysis and FX Options courses to Thomson Reuters clients. Jeff brings 20 years of financial market research and trading experience to this role. Prior to joining Reuters, Jeff worked as a Senior Analyst at the Bank of Canada in Ottawa. In that capacity, he served in the Financial Markets Department, the group that is responsible for executing all financial market transactions required to carry out the Bank of Canada mandates. Jeff’s work involved daily briefing as well as background research ahead of G7 and BIS meetings for senior management and Governing Council to help better understand the implications of trends and developments in financial markets. Jeff’s financial markets experience also include being a Market Strategist with Standard & Poor’s in Toronto, a Foreign Exchange Trader at Bank of America in Toronto, a Derivatives and Money Market Trader at the New Zealand Investment Bank in Singapore and an
Economist at the Port of Seattle in the U.S. He is a Chartered Market Technician (CMT) and his research paper, “Risk Reversals Analysis and Evaluation: An Option-Based Sentiment Indicator for the Foreign Exchange (FX) Markets” was published in the Journal of Technical Analysis (issue 63). Visit the MTA Podcast Series page to listen to this podcast and subscribe to our RSS feed, where you’ll receive updates automatically every week.

MTA Speaking Opportunities

With the growing number of MTA Chapters both in US and non-US markets, now over 35, there are more speaking opportunities than ever before. If you are traveling to an area where the MTA has a chapter, and you are interested in a speaking opportunity, please notify Courtney Musarra at courtney@mta.org. She will notify the local chapter chair about your willingness to speak. For a complete listing of MTA Chapters, please click here.

MTA Library – New Additions!

The MTA would like to announce the additions of Integrated Pitchfork Analysis Volumes 1, 2, and 3 by Dr. Mircea Dologa to the MTA Library. We would like to thank Dr. Mircea Dologa for his generous contributions. If you have any suggestions of books that should be included in the Library, please contact Cassandra Townes.