Learning Objective Statements

“A chart is like a cat’s whiskers. A cat’s whiskers tell the cat which way the mouse will turn and thus which way to pounce. The mouse doesn’t think about which way it will turn but the cat must anticipate that direction. Likewise, the market doesn’t know which way it will turn, but the speculator must anticipate that turn regardless. He uses a chart as his whiskers.”

 (Sieki Shimizu, 1986)

• What type of scale should be used?

Price units are generally plotted on the vertical axis of stock charts. The analyst must determine the scale, or the distance between these price units, to use. Generally, two types of scales are used: an arithmetic scale and a semi- logarithmic scale.

Arithmetic scale 

For all the charts we have examined so far, along with most technical analysts, we have used arithmetic (or linear) scales. A plot with an arithmetic scale shows the price units along the vertical scale at the same price intervals. For example, the vertical plot distance of a change of Rs.1 to Rs.2 would be the same plot distance from 10 to 11 or 100 to 101. In other words, using regular evenly divided grid paper, we plot each box vertically as the same dollar amount.

Semi- Logarithmic Scale

Although the arithmetic scale is the scale most often used, sometimes adjustments need to be made, especially when observing long- term price movements. 

On the logarithmic scale, the vertical distance represents the same percentage change in price. In logarithmically scaled graph, the vertical distance between Rs.50 and Rs.60 is larger than that between Rs.100 and Rs.110. This vertical distance between Rs.100 and Rs.110 always represents a 10% increase in price rather than a particular dollar amount increase in price. The rule of thumb for when to use an arithmetic or logarithmic scale is that when the security’s price range over the period being investigated is greater than 20%, a logarithmic scale is more accurate and useful. As a rule, the truly long- term charts (more than a few years) should always be plotted on logarithmic scales.

1. From a tactical standpoint, the technical investor must decide two things:
   • First the investor or trader must choose when to enter a position.
   • And second, he must choose when to exit a position.
2. Choosing when to exit a position is composed of two decisions:
   • The investor/trader must choose when to exit the position to capture a profit when price moves in the expected direction
   • The investor/trader must also choose when to exit the position at a loss when price moves in the opposite direction from what was expected.

“The wise investor is aware of the risk that the trend might differ from what he expected. Making decisions on what price level to sell and cut losses before even entering into a position is a way in which the investor protects against large losses.”

“One of the great advantages in technical analysis, because it studies prices, is that a price point can be established at which the investor knows that something is wrong either with the analysis or the financial assets price behaviour. Rise of loss can therefore be determined and quantified right at the beginning of the investment. This ability is not available to other methods of investment”

“Finally, because actual rise can be determined, money management principles can be applied that will loosen the chance of loss and the risk of what is called RUIN”

In sum, the basic strategy of making money using technical methods include:

• “The trend is your friend”-play the trend
• Don’t lose- control risk of capital case
• Manage your money – Avoid ruin

“Technical analysis is used to determine the trend when it is changing when it has changed, when to enter a position, when to exit a position, and when the analysis is wrong and the position must be closed.”

It’s as simple as that.

# Trend:

From a technical analyst’s perspective, “a trend is a directional movement of prices that remains in effect long enough to be identified and still be profitable.”

A trend must be recognized early and be long enough for the technician to profit.

# How are trends identified?

These are a number of ways to identify trends:

1. One way to determine a trend in a data set is to run a linear least-square regression.
   (Disadvantage:-The regression method depends on a sizable amount of past price data for accurate results. By the time enough historical data accumulates, the trend is likely changing direction”
2. Many analysts use moving averages to smooth out and reduce the effect of smaller trends with longer trends
3. Trend lines – can define limits to price action, which if broken can warn that the trend might be changing.

# Trends develop from supply and demand:

• As in all markets, the economic principle of interaction between supply and demand determined prices in trading markets.
• Thus, the technical analyst believes it is futile to analyse the components of supply and demand except through the prices it creates.

# For identification purposes, technical analysts have divided trends into several broad, arbitrary categories.
These are:

1. Primary trend(measured in months or years)
2. Secondary trend (measured in weeks or months)
3. Minor trend(measured in days)
4. Intraday trend (Measured in minutes or hours)

# Assumptions of Technical Analysts:

1. Technical analysts assume that price is determined by the interaction of supply and demand.
2. Technical analysts assume that “Price discounted everything” This sounds a little like Eugene Fama’s (1970) famous statement related to the efficient markets Hypothesis(EMH) that “prices fully reflect all available information”
3. Technical analysts believe that “prices are non- random”
4. Technical analysts assumes that history in principle, will repeat itself (or as Mark Twain said, “History rhymes: it does not repeat”).and that “humans will behave similarly to the way they have in the past in similar circumstances.
5. Technical analysts believe that, like trend lines, these patterns are fractal. Thus, an analyst who is watching five- minute bar charts will observe the lame patterns that an analyst watching monthly bar charts will see.
6. Technical analysis is also based on the notion that “emotions are affected by earlier emotions through emotional feedback”
7. If I buy a stock today and its prices rises, I am happy and tell others to by the stock or others see its price rising and also buy it, thus causing the price to rise further.
8. Excessive feedback can cause “bubbles” when price behaviours rises far out of proportion to value and car cause panic when price behaviour declined sharply.

Technical analysis presumes that prices will expand beyond equilibrium for emotional reasons, eventually will revert to the mean, and then expand beyond the mean in the opposite direction (constantly oscillating back and forth with excessive investor sentiment.

Conclusion:

• The interaction of supply and demand determine price.
• Supply and demand are affected by investors’ emotions and biases, particularly fear and greed.
• Price discounts everything
• Prices trend
• Recognizable patterns form within trends
• Patterns are fractal