The Handbook of Technical Analysis + Test Bank. Lim Mark Andrew

analysts study market action. Market action itself is mainly comprised of the study of:

      • Price action

      • Volume action

      • Open interest action

      • Sentiment

      • Market breadth

      • Flow of funds

      Of all the data that technical analysts employ, price is the most important, followed closely by volume action. Price itself is comprised of an opening, high, low, and closing price, normally referred to as OHLC data. OHLC data normally refers to the daily opening, high, low, and closing prices, but it may be used to denote the OHLC of any bar interval, from 1-minute bars right up to the monthly and yearly bars.

       1.4 Classifying Technical Analysis

Technical analysis may be categorized into four distinct branches, that is, classical, statistical, sentiment, and behavioral analysis. Regardless of which branch is employed, all analysis is eventually interpreted via the various behavioral traits, filters, and biases unique to each analyst. Behavioral traits include both the psychological and emotional elements. See Figure 1.6.

Figure 1.6 The Four Branches of Technical Analysis.

      Classical technical analysis involves the use of the conventional bar, chart, and Japanese candlestick patterns, oscillator and overlay indicators, as well as market breadth, relative strength, and cycle analysis. Statistical analysis is more quantitative, as opposed to the more qualitative nature of classical technical analysis. It studies the dispersion, central tendencies, skewness, volatility, regression analysis, hypothesis testing, correlation, covariance, and so on. Sentiment analysis is concerned with the psychology of market participants, which includes their emotions and level of optimism or pessimism in the markets. It studies professional and public opinion via polls and questionnaires, trading and investment decisions via flow of funds in the markets, as well as the positions taken by large institutions and hedgers. Finally, behavioral analysis studies the way market participants react to news, profit and losses, the actions of other market participants, and with their own psychological and emotional biases, preferences, and expectations.

       Mean Reverting versus Non–Mean Reverting Approach

The type of technical studies employed also depends on the approach taken by traders and analysts with respect to their personal preferences and biases regarding the action of price in the markets. Basically, traders either adopt a contrarian or a momentum-seeking type approach. Being more contrarian in their approach implies that they do not usually expect the price to traverse large distances. In fact they are constantly on the lookout for impending reversals in the markets. In essence, they expect price to be more mean reverting, returning to an average price or balance between supply and demand. Those that adopt the mean-reverting approach prefer to employ technical studies that help pinpoint levels of overbought and oversold activity, which includes divergence analysis, regression analysis, moving average bands, and Bollinger bands. They prefer to trade consolidations rather than trend action. They normally buy at support and short at resistance. Limit entry orders are their preferred mode of order entry. Conversely, being more momentum seeking in their approach implies that they usually expect the price to traverse large distances and for trends to continue to remain intact. They are constantly on the lookout for continuation type breakouts in the markets. In short, they expect price to be more non–mean reverting, where demand creates further demand and supply creates further supply, both driven by a powerful positive-feedback cycle. Those that adopt the non–mean reverting approach prefer to employ technical studies that help pinpoint breakout or trend continuation activity, which includes chart pattern breakouts, moving average breakouts, Darvas Box breakouts, and Donchian channel breakouts. They prefer to trade trends rather than ranging action. They normally short at the breach of support and long at breach of resistance. Stop entry orders are their preferred mode of entry into the markets. See Figure 1.7.

Figure 1.7 Mean Reverting versus Non–Mean Reverting Approaches.

       Advantages and Disadvantages of Technical Analysis

      The advantages of applying technical analysis to the markets are:

      • It is applicable across all markets, instruments, and timeframes, where price patterns, oscillators, and overlay indicators are all treated in exactly the same manner. No new learning is required in order to trade new markets or timeframes, unlike in fundamental analysis where the analyst must be conversant with the specifics of each stock or market.

      • There is no need to study the fundamentals of the markets traded or analyzed in order to apply technical analysis, since technical analysts believe that all information that impacts or potentially may impact the stock or market is already reflected in the price on the charts.

      • Technical analysis provides a clear visual representation of the behavior of the markets, unlike in fundamental analysis where most of the data is in numerical form.

      • It provides timely and precise entry and exit price levels, preceded by technical signals indicating potential bullishness or bearishness. It has the ability to also pinpoint potential time of entry via time projection techniques not available to fundamentalists. Fundamental analysis does not provide the exact price or time of entry.

      • It makes the gauging of market risk much easier to visualize. Volatility is more obvious on the charts than it is in numerical form.

      • The concerted effort of market participants acting on significantly clear and obvious price triggers in the markets helps create the reaction required for a more reliable trade. This is the consequence of the self-fulfilling prophecy.

      The disadvantages of applying technical analysis are:

      • It is subjective in its interpretation. A certain price pattern may be perceived in numerous ways. Since every bullish interpretation has an equal and opposite bearish interpretation, all analysis is susceptible to the possibility of interpretational ambiguity. Unfortunately, all manners of interpretation, regardless of the underlying analysis employed – be it fundamental, statistical, or behavioral – are equally subjective in content and form.

      • A basic assumption of technical analysis is that price behavior tends to repeat, making it possible to forecast potential future price action. Unfortunately this tendency to repeat may be disrupted by unexpected volatility in the markets caused by geopolitical, economic, or other factors. Popular price patterns may also be distorted by new forms of trade execution that may impact market action, like automated, algorithmic, or high-frequency program trading where trades are initiated in the markets based on non-classical patterns. This interferes with the repeatability of classic chart patterns.

      • Charts provide a historical record of price action. It takes practice and experience to be able to identify classical patterns in price. Though this skill can be mastered with enough practice, the art of inferring or forecasting future price action based on past prices is much more difficult to master. The practitioner needs to be intimately familiar with the behavior of price at various timeframes and in different markets. Although classical patterns may be applied equally across all markets and timeframes equally, there is still an element of uniqueness associated with each market action and timeframe.

      • It is argued that all market action is essentially a random walk process, and as such applying technical analysis is pointless as all chart patterns arise out of pure chance and are of no significance in the markets. One must remember that if this is the case, then all forms of analysis are ineffective, whether fundamental, statistical, or behavioral. Since the market is primarily driven by perception, we know that the random-walk process is not a true representation of market action, since market participants react in very specific and predictable ways. Though there is always some element of randomness in the markets caused by the uncoordinated