CHAPTER 5 Technical Analysis and Weak Form Market Efficiency
Total Page：16
File Type：pdf, Size：1020Kb
CHAPTER 5 Technical Analysis And Weak Form Market Efficiency A. Technical Analysis for Stock Technical analysis is concerned with the examination of historical market price and volume sequences to evaluate or time securities transactions. Technical analysis is based on the concept that all information regarding securities, including earnings, risk, products, etc. is reflected in market behavior. Market price sequences are of primary importance to the buy or sell decision; many technical analysts focus on charting historical market prices of securities. In his best-selling book on technical analysis, Edwards and Magee [1997] argue “The market price reflects not only the differing fears and guesses and moods, rational and irrational, of hundreds of potential buyers and sellers, but it also reflects their needs and resources – in total, factors which defy analysis and for which no statistics are available.” The market price and its behavior over time provide meaningful information. Hence, the current price may not be the best indicator of the intrinsic value of a stock; in fact, it may well be futile to attempt to determine this intrinsic value. In addition to price histories, which indicate the psychology of the market better than firm fundamental factors, market volume and information regarding other participants in markets will probably be important to most technical analysts. The theoretical foundation for technical analysis is derived from the following set of assumptions: 1. Market value is determined by the interaction of supply and demand, which are functions of a variety of factors, both rational and irrational. 2. Security prices tend to move in trends that persist for an appreciable length of time, despite minor fluctuations in the market. Many of these trends will repeat over time in a rather consistent manner. 3. Changes in a trend are caused by the shifts in supply and demand. 4. Shifts in supply and demand, no matter why they occur, can be detected sooner or later in charts or sequences of market transactions. Many technical analysts (chartists) assume that security prices and market behavior are based on the "psychology" of the market. This psychology is revealed through historical price sequences and charts. A given sequence or pattern may be associated with a given market psychology, which will result in the same future price outcome as did previous identical sequences or patterns. Thus, the market reacts identically each time it encounters the same psychology as revealed by the price sequence. Many academic observers of charting are skeptical of the validity and effectiveness of most of the charting systems. However, as will be discussed later in the section regarding weak form market efficiency, we will discuss some exceptions in the academic literature. Increasing numbers of studies have been supportive of certain technical tools in the more recent literature. In any case, some of the better known charting systems or theories are reviewed below. 1 The Dow Theory The Dow Theory, first suggested by Charles Dow in the late 1800's, examines trends in the market and classifies them into three basic types: 1. Primary Trends: Commonly called bear or bull markets, these trends represent the main component of the Dow Theory. They are long term, typically around 4 years in duration. 2. Secondary Movements: Referred to as corrections, these movements last only a few months. Typically, a secondary downward movement in a bull market is referred to as a correction and a secondary upward movement in a bear market is referred to as a bear trap. 3. Tertiary Moves: Daily fluctuations that are considered random variations. Although these movements are not essential to the theory, they are plotted to delineate primary and secondary trends. A line chart may be plotted using each day's closing (or opening, or high, or low) price, and connecting them with a line. Short-term trends may only represent a secondary movement, however a long-term trend, with each secondary trend failing to reach a new bottom may be considered a bull market. A key aspect to the Dow Theory is the combination of both the DJ Industrials Average and the DJ Transportations Index. The theory holds that the DHIA indicator is more meaningful when it is consistent with the Transportation Index. Presumably, the DJIA indicates productivity while the Transportation Index indicates demand reflected by goods in the order and transportation process. The more recent Elliott Wave Principle is based on five "waves" which are analogous to movements in the Dow theory. The Elliott Wave The Elliott Wave Theory, developed by a retired railroad engineer by the name of Ralph Nelson Elliott in the 1930's, was popularized by Robert Prechter in the early 1980's. It seemed that Prechter had used this obscure theory to correctly predict the bull market of the early and mid 1980's, and more interestingly, predicted the October 1987 crash two weeks before its occurrence. The theory lost credibility when, after the crash, Prechter predicted that the market would crash again, reducing the Dow to around 400. Nonetheless, the theory still maintains a following. The Elliott Wave Theory holds that the market moves in cycles composed of five waves. Three of the five waves are termed impulse waves and indicate the overall trend of the market while the other two are termed corrective waves. One is able to determine the future direction of the market by determining which are the impulse waves and which are the corrective waves. Bar Charts Bar Charts are frequently used to analyze individual securities. Vertical bars represent each day's price range, from highest to lowest. Price bar charts are frequently accompanied by bar graphs along the bottom indicating volume of shares traded. A 2 chartist will plot prices over time for a security to locate relevant or recurring patterns. Such patterns may include the "head and shoulders", "triangle" or the "flag" figures. Practitioners and observers of charting generally regard the practice as an art rather than as a science. Figure 1 provides an example of a bar chart taken from 10-minute intervals over the period May 24-25, 2007. This chart depicts high and low values realized for the S&P 500, with left and right notches indicating open and close values. Figure 1: Sample Bar Chart from Barchart.com Moving Averages Moving averages are frequently used as a reference point to gauge or smooth daily fluctuations. Daily prices are compared to a moving average of a specified number of historical prices. For example, one very simple rule holds that if current prices rise above a falling moving average, they are expected to drop back towards the moving average; selling is suggested. Buying is suggested when the moving average flattens out and the stock's price rises above the moving average. There are numerous other moving average rules. Moving averages may be computed for any number of price data points. For example, consider the following sequence of daily closing prices for a given stock over a period of time: 12 14 17 13 14 19 22 17 11 18 16 22 t=1 t=2 t=3 t=4 t=5 t=6 t=7 t=8 t=9 t=10 t=11 t=12 3 The following represents the sequence of three-day moving averages for the above price sequences: NA NA 14.3 14.7 14.7 15.3 18.3 19.3 16.7 15.3 15.0 18.7 t=1 t=2 t=3 t=4 t=5 t=6 t=7 t=8 t=9 t=10 t=11 t=12 The simplest moving rule discussed above would suggest that days 4, 5, 8 and 9 are “buying” days while days 3, 6, 7, 10, 11 and 12 are selling days. Technical analysts make use of simple moving averages, exponential moving averages that weight more recent data more heavily. In addition, many of the moving average – based rules are somewhat more complicated than the simple one described above. Theories Based on Behavior of Certain Groups Other technical analytical systems focus on the behavior of other groups of market participants. For example, Contrary Opinion Theories propose doing the opposite of what some particular group of investors is doing. One Contrary Opinion Theory is the Odd Lot Theory, which assumes small investors are usually wrong; thus, one should follow a strategy contrary to small investors. Odd lot transactions (less than 100 shares) require higher brokerage commissions and are usually placed by individual investors with limited funds. Years ago, odd lot volume data was collected by odd lot traders on the floor of the NYSE, compiled and published in financial sections of many newspapers. A second contrary opinion theory is based on short-sales volume. This Short-sales Contrary Opinion theory assumes that a high level of outstanding short sales is a sign of increased future demand in order to cover outstanding short positions. The theory asserts that this future increase in demand will bid up the prices. Breadth-of Market Statistics are used to study the underlying strength of market advances or declines. For example, before the October 1987 crash, the 30 DJIA blue-chip stocks were rising, but the majority of lesser-known stocks were declining. One easy way to study the breadth of the market is to compare the number of issues in a large market or index, such as the NYSE or Wilshire 5000 that advanced in price to the number that declined in price. Subtracting the issues whose prices declined from the number whose price advanced gives the daily net advances or declines. These daily net advances or declines are cumulated to obtain the breadth of market statistic.