Dancing with the Trend

Candlestick Analysis - Putting it All Together

Here we are at the end of the Candlestick Analysis series; hopefully a few of you are still with me.  I’m going to show in this article the process I would use to incorporate candle patterns into my trading even though I am no longer a trader; not sure I ever was.  Hey, there are enough non-traders out there offering trading advice, I just wanted to be honest about it.  There are some things that must be met before I would consider a Japanese candle pattern to have any validity.


Of course, this is the most important component to candle pattern analysis; a pattern must be preceding by an appropriate trend.  Reversal patterns are reversing something!  They are reversing the trend that was used to help identify them in the first place.  See Trend Determination article.

Continue reading "Candlestick Analysis - Putting it All Together" »

Candlestick Analysis - Performance

The following tables of data reflect the performance of 14 different technical indicators using the perceived popular parameters for each one (see Table A).  However, each table uses a different setting for analyzing the candle patterns.  The success or failure of a candle pattern is determined by the price relative to the last day of the candle pattern.  For example, in Table B, the success of a candle pattern is measured by the price two (2) days after the pattern.  If the price is lower and it was a bearish reversal pattern or a bearish continuation pattern, then the pattern was deemed successful.  Similarly, if the price was higher for the bearish reversal or bearish continuation pattern, then the pattern was a failure.  Stated a little differently, if the candle pattern was correct after the period being used, it was considered successful.

Continue reading "Candlestick Analysis - Performance" »

Candlestick Analysis - Filtering

Candle pattern filtering offers a method of trading with candlesticks that is complemented by other popular technical tools for analysis.  Filtering is a concept that has been used in many other forms of technical analysis and is now a proven method with candle patterns.

Since any one indicator on its own can have inherent flaws, the synergy created by combining different methods of price movement analysis can result in some very powerful combinations.  When candle patterns are combined with other indicators, the results are superb.

Continue reading "Candlestick Analysis - Filtering" »

Know Thyself II

The first article on Know Thyself generated a lot of interest, so here is the second one.  Welcome to being human!  Do you really know that person you see while shaving or applying makeup?  If you are going to be a successful investor/trader, you better get to know him/her and know them really well – like the back of your hand.  As a human being, you were born with some unusual traits that most of us cannot override or rid ourselves of, such as keeping your eyes open when you sneeze or blinking periodically.  While these have nothing to do with the market, they do serve as a lead into the human frailties known as heuristics.  As an adjective, heuristic pertains to the process of gaining knowledge or some desired result by intelligent guesswork rather than by following some pre-established formula. As a noun, a heuristic is a specific rule-of-thumb or argument derived from experience.

Continue reading "Know Thyself II" »

Candlestick Analysis - Statistics III

Additional information in regard to the determination of the suitability of candle patterns is to look at the Net Profit divided by the Net Loss per Trade.  This would be a measure of the overall profitability of candle patterns based upon the prediction interval.  Table A shows this data with the positive data emboldened.

Trades that do not produce either a profit or loss are included in the Net Profit/Loss per Trade (Table A) calculation.  The Net Profit/Loss per Trade value is simply the average percent gain (or loss) for all trades. Because the Net Profit/Loss per Trade value is the average result for all trades (winning, breakeven, and losing trades), it can be a positive or negative number, or even zero. If the Net Profit/Loss per Trade value is positive, it means the average trade produced a net profit. If the Net Profit/Loss per Trade value is negative, it means the average trade produced a net loss.

Continue reading "Candlestick Analysis - Statistics III" »

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.


Continue reading "Article Summaries 12-2015 to 3-2016" »

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.

Continue reading "Candlestick Analysis - Statistics II" »

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.

Continue reading "Candlestick Analysis - Statistics I" »

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.

Continue reading "Are Mutual Fund Statistics in the Dark Ages?" »

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.

Continue reading "Candlestick Analysis - Recognition Reliability" »