Win Investing

Technical Analysis does have its critics – those economists who say it is nothing more than a pseudoscience, one that has no basis in fact. Investors such as Warren Buffett and Peter Lynch say that there is precious little evidence that Technical Analysis works. However, various academic studies have shown that technical analysis, particularly when carried out by neural networks, can produce statistically significant returns, and many investors have made fortunes through the application of its principles. It is therefore unfair to dismiss it as mere nonsense, and one ignores it at one’s peril!

One of the tenets of Technical Analysis is that prices follow trends, either upwards, downwards or sideways (when the price is generally holding steady – a “flat” price). If investors spot an upward trend in a share, they may well try to jump on the band-wagon and buy that share, hoping to benefit from its rise, and thereby driving its price up further. Similarly, a downward trend may cause investors to dump shares on the market, causing a further fall in the price. This can cause the price to “zig-zag” – rise and fall several times in line with investor confidence.

Technical analysis is often compared to Fundamental Analysis, which also tries to predict share price but on the basis of company assets, the general health of the company and other factors such as the amount of competition in the market that a company faces. Technical analysis, on the other hand, is concerned only with the behaviour of the market: The market’s opinion of a particular company is more important than that company’s underlying worth. The theory is that all the information about the company that you need to predict its share price is already encoded in that price in some way.

Technical analysis covers two areas of the stock market, its sentiment (sometimes termed its “psych”) and the analysis of supply and demand. The sentiment of the market is the general feeling of investors. This is rather intangible, but does show itself in overall share movements. For instance, if investors are feeling generally optimistic (as in a bull market), share prices will tend to rise. The supply and demand aspect of the stock market is a measure of how much money there is available to invest in shares: If an investor has little spare money, for example, this restricts his or her ability to invest in shares and drive the market higher.

Any stock market produces vast amounts of data on a daily basis, far too much for anyone to cope with in its raw form. You only have to look at the share price pages in the Financial Times to get some idea of the quantities of figures that make up just one day’s trading. To make any sense of this deluge, we must apply various statistical measures that turn the raw data into meaningful information. There are several measures in common use, and different technical analysts tend to prefer different measures. These measures all have one thing in common – they reduce the amount of noise present on the data and help to reveal any underlying pattern.

Inevitably, the ultimate aim of Technical Analysis is to make money. The secret of successful share trading, boiled down to one sentence, is to buy when the share price is low and to sell when it is high. As the share prices rise and fall, there will be times when one makes the correct judgement and makes a profit, and times when one gets it wrong and makes a loss. With successful technical analysis, the accumulated profits will outweigh the total losses.

Technical analysis is the science (some might say art) of predicting the prices of share commodities based on their current price and past performance. Share prices wander up and down, changing many times every day. If you plotted the price of a share during the course of a particular time period (day, month or year), you would get a line that moves up and down sharply, like some demented saw blade. You might, however, be able to spot a general pattern underneath all that variation. The random variation is termed “noise” and the purpose of technical analysis is to remove that noise as far as possible.