In the 1970s there were very few books on technical analysis. Now there a many great books available in the field of technical analysis and finance. However, I’m going to keep these lists short and focused. These lists contains many other wonderful books on technical analysis, finance, and behavioral analysis, but if I had to pick a library of only four books, this is it – Getting Started List.
Early in writing these articles I talked a lot about market internals or market breadth. As a refresher, I’ll review the basics and then offer an opinion on why breadth is so important.
Breadth components are readily available from newspapers, online sources, etc. and consist of daily and weekly statistics. They are: Advances, Declines, Unchanged, Total Issues, Up Volume, Down Volume, Total Volume (V), New Highs, and New Lows. From one day to the next, any issue can advance in price, decline in price, or remain unchanged. Also any issue can make a new high or a new low. Here are more specific definitions:
This is the fourth article dealing with cognitive biases that totally screw up your decision making. The first article, Know Thyself, covered anchoring, confirmation bias, herding, hindsight bias, overconfidence, and recency. The second article, Know Thyself II, covered availability, calendar effects, cognitive dissonance, disposition effect, and loss aversion/risk aversion. The third article, Know Thyself III, covered Communal Reinforcement, Endowment Effect, Halo Effect, Overreaction, Prospect Theory, Self-Attribution, and Self-Deception. Most of my education on behavioral investing came from books by James Montier, Hersh Shefrin, and Thomas Gilovich. Two great websites for this stuff are from Tim Richards and Martin Sewell.
I’m on record in my book, “Investing with the Trend,” and probably in this blog of stating that Financial Academia is nothing more than the marketing department for Wall Street. When I do presentations about technical analysis and / or money management, I always begin with this slide:
First of all, I must apologize for my lack of creativity for these article titles. The previous two “Filtering the Noise” and “Filtering the Noise II” were about moving averages and suggesting a better way to use a relationship between two moving averages, similar to the ubiquitous MACD. In this creatively named article I will attempt to explain my process for finding the shorter-term average using detrending. If you recall from the previous articles, once you have the shorter-term average, you then know the longer term one and the signal value. Instead of rewriting it, I’ll just pull if from an article, I wrote over 30 years ago. See the end of this article for more information on Stocks and Commodities magazine – a must read.
The first article of Filtering the Noise dealt with smoothing the data with moving averages. Here I want to discuss a really popular concept popularized by an indicator called Moving Average Convergence Divergence or MACD. MACD is a concept using two exponential averages developed by Gerald Appel. It was originally developed as the difference between the 12 and 26 day exponential averages; the same as a moving average crossover system with the periods of the two averages being 12 and 26. The resulting difference, called the MACD line, is then smoothed with a nine-day exponential average, which is referred to as the signal line. Gerald Appel originally designed this indicator using different parameters for buy and sell signals, but that seems to have faded away and almost everyone now uses the 12–26–9 combination for both buy and sell.
I have mentioned many times I that I basically only work with daily market data. I do not have the personality to deal with intraday data and weekly data is only good for long term use. I do have a few weekly data indicators that I use as overlays to my trend model, but the bulk of then are daily. One of the concepts I think you must deal with when using daily data is to come up with a method that removes the noise. Noise in this instance is very short term fluctuations in price. One of the most popular is the moving average; and it comes in many flavors. There is a significant difference between the simple and exponential moving average.
This is funny. A few articles ago I commented on the foolishness of the media’s focus on Dow 20,000 and now I’m focusing on my 100th blog article. Is that being a hypocrite or what? I have been racking my feeble brain trying to think of an appropriate topic for this milestone. Maybe I'll start with a little history.
The “Wall of Worry” has been used for many decades to identify the period of time in the latter stages of a bullish run in the stock market, when all the naysayers start talking about a top. I have witnessed this often. As the bull ages, many start to think they can “call the top.” The financial media parades expert after expert showing economic or political situations in which they believe is coincident with a market top. First of all, anyone who has ever looked at a chart knows that the topping process, also called distribution (more on that later), is a really long drawn out affair. The topping process leaves lots of dead bodies alongside the road.
Periodically I write an article that reviews the past few months of articles. Why on Earth would I do this? Primarily for two reasons. One is that many new readers are involved and often they do not go back and look at the past articles. Two is that my articles are rarely tied to anything that is happening in the markets. Generally, they are about experiences I have had as a technical analyst for almost 45 years; the good, the bad, and the ugly.