Dancing with the Trend

Article Summaries 12-2015 to 3-2016

Most blog authors on StockCharts.com are writing about the current markets and do an exceptional job.   I do not write about the current markets as I wanted to share my experiences after 40+ years as a technical analyst.  Not only experiences with trading and investing, but model building and money management.  I also share the details of all the Master’s degrees I have – those expensive learning experiences that hopefully I learned something from.  Since I rarely go back into the archives of other’s blogs that I read, I wondered if that is common or not.  Hence, after talking with Chip, a summary of my past articles might encourage new readers to take a look as most of the material is timeless.  That’s timeless, not worthless!  This is the fifth of the 'article summary' series and starts in December, 2015 and ends in March, 2016.  I’ll try to do future summaries whenever I have a dozen or so articles to include.  You can click on the article name for a link directly to the article.

 

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Candlestick Analysis - Statistics II

Candle patterns are predictable psychological trading pictures (windows) that produce reasonable forecasting results when used in the proper manner.  This article will explain the technique used to determine the various statistics developed to show the success of candle patterns.  Note that no magnitude of success is used, only a relative success and failure.  Keep in mind, though, that success still means that the pattern correctly predicted the market move and failure means that it did not.

Using all of the information about pattern recognition (including trend determination) developed in the previous articles, we will now set out to see just how good candle patterns are.  Because a simple approach is usually best, no elaborate assumptions were used, only the price change over various time intervals into the future.  Those time intervals were measured in days.

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Candlestick Analysis - Statistics I

The candle pattern statistics in Table A below show the amount of data used in this analysis, the type of data used, and various other pertinent statistics.  All common stocks on the New York Stock Exchange, the Nasdaq market, and the American Stock Exchange were used over a 13-year period. Using stock data prior to late 1991 would distort the analysis because most data services did not provide open prices then.  When I wrote the first edition of my book in 1992, I had to use mostly futures data since stock data with open price was rare.  Any discrepancies in the summary statistics are because not all of those stocks traded for the full analysis period.

A total pattern frequency of slightly more than 11% equates to one candle pattern about every nine trading days, 8.69 to be exact.  This represents a good frequency for daily analysis of stocks and futures.  Reversal patterns occur about 40 more times often than continuation patterns.  This too is important, as it indicates the reversal of a trend caused by changed positions in trading.  In this analysis, there were 65 reversal patterns and 23 continuation patterns, which make reversal patterns account for about 74% of all patterns.

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Are Mutual Fund Statistics in the Dark Ages?

Since the dawning of the Internet in the early 1990s, investors now have access to volumes of data and statistics that were only reserved for a select group before.  There are some things you need to know about financial data that is readily available for your use.  There are some problems that don’t seem to be addressed by those who should know better.

Daily vs. Monthly Statistics

Almost all of the financial statistics you see on mutual funds are based upon monthly returns.  Did you ever wonder why some of the big mutual fund sites only show some statistics for funds that have at least 3 years of data?  It is because they are only using 36 months’ worth of data returns to make the calculations.  36 months is barely into the realm of statistical significance, let alone enough data to account for the tremendous uncertainty in free market pricing.  Daily data is and has been readily available for decades.  Why isn’t it used?  Surely the results of using daily data to generate the statistics would be more valuable to the investor, especially an technically oriented investor.

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Candlestick Analysis - Recognition Reliability

Using the pattern identification philosophy developed in the previous article on Pattern Identification, one can now adapt a method of determining just how successful candle patterns are?  The techniques I used are quite analytical and I find they are somewhat difficult to explain, so here goes.

Measures of Success

The following three assumptions were used in measuring the success and/or failure of the many different candle patterns:

1. The pattern must, of course, be identified based upon its open, high, low, and close relationships (see previous article).

2.  For the pattern to be identified, the trend must be determined (see Trend Determination article).  This is interchangeable with the previous assumption; each must exist in the methodology.

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Candlestick Analysis - Pattern Identification

All books on candlesticks offer detailed descriptions of the relationships among the open, high, low, and close.  They also deal with the concepts of trend determination which I did in the previous article; while this article focuses on pattern identification.  In addition, a method of determining long days, short days, doji days, etc., is needed, including the relationship between the body and the shadows.  The latter is essential for proper identification of patterns such as the Hanging Man and Hammer.  The following will show the multitude of methods used to accomplish these and similar tasks.  I wish to note that all of the Japanese books on candlesticks do not delve deeply into this subject; most just show a drawing of how it should look.  However, when you are programming a computer to identify them you must accept some flexibility or no patterns would ever appear.

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Candlestick Analysis - Trend Determination

In the first few minutes of the trading day, a great deal of overnight emotion is captured.  Sometimes special events cause chaos.  For example, on the New York Stock Exchange it may take several minutes for the market maker (used to be a specialist) to open a stock for trading because of a large order imbalance.  However once a stock or commodity does open, a point of reference has been established.  From this reference point, trading decisions are made throughout the day.  The Japanese believed that the period of time from the close of trading in the previous session to the current session’s open is very important.  Many things can happen during that time to affect a trader’s decisions.

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Secular Bulls

This is a complementary article to Secular Bears that I wrote on May 14, 2015.  To be perfectly honest (that is how someone usually leads into telling a lie) I planned on doing this article shortly after the first one and totally forgot.  Secular Bulls and Secular Bears is terminology that I don’t ever recall hearing more than 15-20 years ago.  Now I see the term bandied about all of the time and often it is different in a number of ways.  For full disclosure, my entire education on secular markets comes from Ed Easterling.  Ed wrote two wonderful books that I strongly recommend – “Unexpected Returns” and “Probable Outcomes.”  Ed also maintains a website that is loaded with great articles and charts (even though they are not SharpCharts) at http://www.crestmontresearch.com.  Secular is one of those words that I don’t think is well defined, but the dictionary says it pertains to occurring once in an age.  My version is simply that it doesn’t occur very often.  Even that depends on your viewpoint, but since we are talking about the stock market and it has been around since the late 1800s, we can think of secular as something that happens every couple of decades or so.

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Candlestick Analysis

In 1988 I attended a Market Technician’s Association (MTA) meeting in Phoenix at the Camelback Inn.  There were two wonderful highlights that occurred at that meeting: one was an introduction to Japanese candle pattern analysis/charting, and the other was meeting Ian McAvity who published Deliberations newsletter for over 40 years and remains a great friend.  Ian, you can relax because the remainder of this article will be about Japanese candlestick analysis, even though stories about you would be quite entertaining.

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Blinded by the Noise

I’ve discussed noise a few times in the past but it needs to be brought up again.  Just in the course of a normal week, we are bombarded with information from sources such as the FED, television analysts, brokerage firm analysts, economists’ projections, newspapers, junk mail, neighbors, war reporters, etc.  Making investment decisions without a plan or methodology is truly a gamble.  And to think that there are academic types who advocate that the markets are efficient, which means everyone has all the available information at the same time, and therefore cannot possibly get an advantage over anyone else is preposterous!   Then when you add the “investors are rational” tag, it gets even worse.  What I think is truly sad is that our educational system is tied to this drastically common and challenged line of thinking.  One can get a college degree without a single hour of finance or economics.  While I do not think that is exactly my point, it is the lack of understanding how the credit markets and the capital markets work that is the ultimate problem.

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