Excerpt
Table of content
1. Introduction
1.1. Basic conditions
1.2. Problems
1.3. Objective
1.4. Procedure
2. Analysis methods
2.1. Fundamental Analysis
2.2. Alternative analysis methods
2.2.1. Technical Analysis
2.2.1.1. Premises of Technical Analysis
2.2.1.2. Distinction between Chart Analysis and Technical Indicators
2.2.1.2.1. Chart Analysis
2.2.1.2.1.1. Techniques of chart representation
2.2.1.2.1.2. Trend analysis
2.2.1.2.1.2.1. Support and Resistance
2.2.1.2.1.2.2. Trend lines and Trend Channels
2.2.1.2.1.2.3. Continuation patterns
2.2.1.2.1.2.4. Reversal patterns
2.2.1.2.2. Technical Indicators
2.2.1.2.2.1. Trend-following Indicators
2.2.1.2.2.2. Oscillators
2.2.2. Behavioral Finance
2.2.2.1. Premises of Behavioral Finance
2.2.2.2. Distinction between Behavioral Finance and Sentiment Analysis
2.2.2.2.1. Individual psychological aspects
2.2.2.2.1.1. Motives and needs of market participants
2.2.2.2.1.2. Behavior of market participants
2.2.2.2.1.2.1. Rationality failures during information apperception
2.2.2.2.1.2.1.1. Simplification of circumstances
2.2.2.2.1.2.1.2. Selective apperception
2.2.2.2.1.2.1.3. Relative Evaluation
2.2.2.2.1.2.2. Rationality failures concerning the behavior
2.2.2.2.1.2.2.1. Heuristics
2.2.2.2.1.2.2.2. Herding
2.2.2.2.2. Sentiment Analysis
2.2.2.2.2.1. Premises of Sentiment Analysis
2.2.2.2.2.2. Sentiment indicators based on market data
2.2.2.2.2.3 Sentiment indicators based on public opinion polls
3. Synthesis capabilities
3.1. Proposal of a synthesis concept
3.2. Synthesis concept applied to BASF AG
4. Conclusion
II. List of figures
Figure 1: Primary, intermediate and short-term trend as well as upward trend, downward trend and sideways shown by the example of Daimler Chrysler AG, period: 2006/06/01 – 2007/12/31
Figure 2: Support and Resistance areas applied by the example of BASF AG, period: 2007/01/01 – 2007/12/31
Figure 3: Trend lines and Trend Channels shown by the example of the DAX Performance Index, period: 2007/01/01 – 2007/08/31
Figure 4: Flags and pennants illustrated by the example of the Daimler Chrysler AG, period: 2005/01/01 – 2005/12/31
Figure 5: Double bottom and double / triple top as well as an inverse head and shoulder formation applied on the example of the DAX Performance Index, period: 2007/01/01 – 2007/12/31
Figure 6: V bottom and rounding bottom shown by the example of the Versatel AG, period: 2007/04/30 – 2007/12/31
Figure 7: Moving average of 38 and 200 days, and the MACD-Indicator applied to the example of DAX-Performance Index, period: 2007/01/01 – 2007/12/31
Figure 8: Momentum and Relative Strength Index applied to the example of DAX Performance Index, period: 2007/01/01 – 2007/12/31
Figure 9: Simplification of circumstances illustrated by the example of Vivacon AG, 2007/01/01 – 2007/12/31
Figure 10: Relative Evaluation illustrated by the example of Daimler Chrysler AG, period: 2005/01/01 – 2005/12/31
Figure 11: Heuristics illustrated by the example of BASF AG, period 2007/01/01 – 2007/12/31
Figure 12: Herding shown by the example of Versatel AG, period 2007/04/30 – 2007/12/31
Figure 13: Sentix – DAX development versus DAX sentiment, period: 2007/01/26 – 2007/12/31
Figure 14: AnimusX – news-barometer stocks, period: 2007/01/29 – 2007/12/31 .
Figure 15: AnimusX – Sentiment for the 30 stocks within the DAX, periods: 2007/05/14 – 2007/05/20 and 2007/08/06 – 2007/08/12
Figure 16: Synthesis capabilities of the Fundamental Analysis approach with the two alternative concepts of Technical Analysis and Behavioral Finance illustrated by the example of BASF AG – Sentiment Analysis BASF, period: 2007/04/08 – 2007/12/31
Figure 17: Synthesis capabilities of the Fundamental Analysis approach with the two alternative concepts of Technical Analysis and Behavioral Finance illustrated by the example of BASF AG – Fundamental and Technical Analysis, period: 2007/01/01 – 2007/12/31
III. List of Abbreviations
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1. Introduction
1.1. Basic conditions
At all times stock investors have been trying to develop analysis methods which should enable them to receive an above-average return to outperform the broad stock market (Klein 1999). Due to this attempt, a vast number of various analysis methods have been developed to predict the stock prices in the future.
The price movements of stocks are the result of complex interdependencies due to a vast number of influencing factors – such as fundamental and psychological factors – are expressed in the expectations and the behavior of the stock market participants (Klein 1999). To cope with this complexity and to derive an applicable asset strategy, analysts distinguish particularly between two dominant analysis methods in practice – the Fundamental and the Technical Analysis – which have recently been supplemented by the approach of Behavioral Finance (Cesar 1996).
1.2. Problems
With reference to a strict interpretation of the theoretical assumptions of the Fundamental as well as the Technical Analysis these two concepts are mutually exclusive (Edwards et al. 2007).
As a result of this there are a vast number of analysts who either acknowledge the Fundamental Analysis while denying the Technical Analysis and vice versa (Cesar 1996).
The Fundamentals criticize that the technical approach has a lack in academic foundation and is, therefore similar to a kind of reading tea leaves, whereas the Technicals are convinced that the Fundamental Analysis is not able to generate an advantage by analyzing the fundamental value drivers of a stock, because those are already reflected by the current market prices (Murphy 1999).
In practice the Fundamental Analysis seems to have its weaknesses particularly during extreme market phases – e.g. during the New Economy bubble at the end of the nineties – in which the psychology of the market participants gains in impact. At the same time the fundamental aspects are seemingly neglected (Malkiel 1999). Furthermore, the fundamental approach seems to have improvement capabilities particularly in terms of timing (Montassér 2000).
Psychological aspects of the market participants are at least indirectly included within the Technical Analysis, which could be particularly used for timing decisions as well (Murphy 1999). Nevertheless, it has its weaknesses too, e.g. it does not provide clearly defined interpretation rules for its various numbers of chart patterns and technical indicators.
Behavioral Finance seems to have its existence authority in practice as well, due to decisions in stock markets made by human beings, who do not always behave total rationally (Shleifer 2000).
All these aspects lead to the master question if the two alternative analysis methods – Technical Analysis and Behavioral Finance – can deliver any useable supplements towards the Fundamental Analysis in terms of their practical application?
1.3. Objective
The objective of this case study is to illustrate how the alternative analysis concepts of Technical Analysis and Behavioral Finance work in practice, particularly on the German stock market. In addition it should be analyzed, whether or not these two alternative concepts are able to enrich the Fundamental Analysis in practice.
Based on those results it is aimed at a proposal of a synthesis concept, in which the two alternative analysis concepts supplement the fundamental approach by their respective strengths.
1.4. Procedure
At the beginning, the three analysis methods are differentiated by the Fundamental Analysis and its two alternative analysis methods – Technical Analysis and Behavioral Finance. The description of the Fundamental analysis is limited on its most important concept under 2.1., in order to be able to draw a differentiation towards its two alternative analysis concepts described under 2.2..
Afterwards, the two alternative concepts are described separately in detail under 2.2.1. Technical Analysis and 2.2.2. Behavioral Finance.
Due to its extend Technical Analysis is subdivided into Chart Analysis under 2.2.1.2.1. and Technical Indicators under 2.2.1.2.2.
The description of Behavioral Finance is structured by a bottom-up approach which aggregates the analyzed individual behavior of a market participant to an upper level – the Sentiment Analysis – which applies those qualitative results to the broad market by developing quantitative tools (Shefrin 2000).
To be able to analyze the practical use of these two concepts their respective characteristics are illustrated by five practical examples extended over three important German-Indices – DAX, SDAX and TecDAX – as well as over different industry sectors. Consequently, the practical examples are well diversified to reduce the probability of random results as far as possible. In the following, the five examples are enumerated with their respective ISIN-number and Index membership to enable the reader to allocate the examples unambiguously:
- DAX-Performance Index (DE0008469008 / -)
- BASF AG (DE0005151005 / DAX)
- Daimler Chrysler AG (DE0007100000 / DAX)
- Vivacon AG (DE0006048911 / SDAX)
- Versatel AG (DE000A0M2ZK2 / TecDAX)
For best demonstration the considered periods of time differ within the five examples and are of different duration. Each example is to characterize a different aspect of Technical Analysis respectively Behavioral Finance in practice.
In chapter three the synthesis capabilities of the three analysis methods are analyzed in detail to make a proposal of a synthesis concept, in which the two alternative analysis concepts supplement the fundamental approach by their respective strengths.
In chapter four a argumentation is drawn reflecting and evaluating the results of the case study in conclusion.
2. Analysis methods
2.1. Fundamental Analysis
The Fundamental Analysis has its origin in the year 1934, when Benjamin Graham and David Dodd published a book with the title “Security Analysis”. It treated first of all the fundamental evaluation of a company, such as the determination of balance-sheet value and profitability of a company (Cesar 1996).
The Fundamental Analysis assumes that the current price of a stock fluctuates around its intrinsic value. The intrinsic value is defined as the fair value at a point in time around which the current market price is fluctuating in the variation of time (Cottle et al. 1999). The intrinsic value is being determined by analyzing and interpreting micro- and macroeconomic factors, such as monetary, sectoral and company-related developments (Sippelfrick 2007).
The buying decision is to be derived from a comparison between the identified intrinsic value and the current market price of the stock. If the identified intrinsic value exceeds the current market price the stock is undervalued and, thus, worth to buy due to a higher real value. If the identified intrinsic value is lower than the current market price the described rule has to be applied vice versa.
Thus, the Fundamental analysis is able to judge if a stock is under- or overvalued and therefore should basically be bought or sold (Cottle at al. 1999).
Nevertheless, it has its weaknesses due to the lack of advice at which point of time an over- or undervalued stock should exactly be bought or sold (Montassér 2000). In a fundamental examination of the US-stock market in 1979 Modigliani and Cohan came to the result, that the US-stock market was undervalued 50 Percent within a period of ten years (Cesar 1996).
This result shows that the fundamental approach could be improved in terms of timing decisions as well as the consideration of psychological factors.
However, there are market phases during which psychological aspects of the participants seem to have major impact on the stock prices.
There are even analysts, who estimate that the impact of new information on the stocks prices does not exceed a number of 50 Percent (Cutler et al. 1993). The remaining 50 Percent are assumed to be influenced by anomalies and psychological aspects. Therefore, alternative analysis methods – such as Technical Analysis and Behavioral Finance – try to take those psychological aspects into account indirectly or even directly (Cesar 1996).
2.2. Alternative analysis methods
Basically, there are two further methods to analyze the stock market in addition to the Fundamental Analysis. Those are the Technical Analysis – which is subdivided into Chart Analysis and Technical Indicators – and the approach of Behavioral Finance (Cesar 1996).
2.2.1. Technical Analysis
The Technical Analysis is based on the Dow Theory developed by Charles Dow and his partner Edward Jones around the turn to the 19th century (Pring 2002). According to Murphy “Technical analysis is the study of market action, primarily through the use of charts, for the purpose of forecasting future price trends.” The term “market action” includes the three principal sources of information available and necessary for the approach of technical analysis – price, volume and open interest – on which all further tools of technical analysis consist of (1999).
2.2.1.1. Premises of Technical Analysis
The Approach of technical analysis is based on three principal premises, which represent its foundation (Murphy 1999):
- Market action discounts everything
- Prices move in trends
- History repeats itself
The first premise about the market action discounting everything, is the cornerstone of technical analysis. It assumes that everything which could have influence on the market price – no matter if it is of fundamental, technical or psychological origin – is included and reflected by the price of that market (Edwards et al. 2007).
Thus, unlike to the fundamental approach Technical Analysis does not try to determine the intrinsic value of a stock.
Technicians are convinced that an intrinsic value of a stock does not exist, because all necessary information to evaluate the stock – as well as the fundamental information – is already contained and reflected by the current market price (Pring 2002).
Thus, Technical Analysis examines the movement of markets. In contrast the Fundamental approach analyzes why the markets move (Murphy 1999).
Technical Analysis assumes that if everything that affects market price is contained and thus reflected by the market, the studying of the market price enables a technician to draw conclusions of the probable movements of this market in the future (Edwards et al. 2007).
To be able to draw such conclusions on future price movements of markets the two further mentioned premises have to be taken into consideration as well.
Based on Newton’s first law of motion, technical analysis assumes that a trend in motion is more likely to continue than to reverse and will continue in the same direction until it reverses.
The assumption of the existence of trends in stock markets is closely linked to the third premise of a repeating history (Murphy 1999).
Therefore, Technical Analysis denies the Random Walk Theory which assumes that future price movements are random (Montassér 2000).
Technical Analysis assumes that special characteristics of chart patterns and technical indicators “reveal the bullish or bearish psychology of the market. Since theses patterns have worked well in the past, it is assumed that they will continue to work well in the future. They are based on the study of human psychology, which tends not to change” (Murphy 1999).
That means that the approach of technical analysis takes the psychological aspects of the market into consideration indirectly (Edwards et al. 2007).
There is the linkage between the Technical Analysis and the approach of Behavioral Finance, explained under bullet 2.2.2.
2.2.1.2. Distinction between Chart Analysis and Technical Indicators
Technical Analysis has been steadily developing during the following decades, so that it is nowadays divided into two interdependent approaches, which are known as Chart Analysis and Technical Indicators.
The Chart Analysis is focusing the examination of graphical data of a stock in form of charts, whereas the approach of Technical Indicators concentrates on the statistical analysis of the stock data (Murphy 1999).
2.2.1.2.1. Chart Analysis
Chart Analysis represents the classical subset of Technical Analysis and tries to predict future price movements of a market by analyzing its past on the basis of charts (Götz 1990).
A chart is defined as a graphical representation of an array (Cesar 1996). Charts consist of the considered period, the traded volume and the respective price information of the stock. The considered period as well as the traded volume are normally shown on the vertical axis. The price information is normally visualized on the horizontal axis (Murphy 1999).
The practical application of the concept of chart analysis can be divided into two steps (Cesar 1996).
In a first step the array of the stock has to be visualized by a chart. 2.2.1.2.1.1. illustrates the most important techniques of visualization by the practical example of Daimler Chrysler AG.
In a second step the constructed chart is analyzed in terms of its contained chart patterns, which should enable the Chartist to draw conclusions on the future price movements of the stock (Pring 2002).
2.2.1.2.1.1. Techniques of chart representation
There have been developed a vast number of techniques on how to represent charts. They all have the objective to improve the informational basis for the following analysis process (Montassér 2000).
The most important of those are line charts, bar charts, point and figure charts and more recently candlesticks charts (Murphy 1999).
With reference to its wide application in practice (Murphy 1999) the following practical examples within this case study are all represented with bar charts.
A bar chart is visualized by a line that is generated by the high and the low of the considered time period. The left bar represents the opening price whereas the right bar shows the closing price of the stock (Cesar 1996).
2.2.1.2.1.2. Trend analysis
The primary objective of Technical Analysis is to identify a trend reversal at a relatively early stage to follow that trend until evidence shows that the trend will reserve. In order to identify such a reversal, a technician must first know what a trend is (Pring 2002).
“In a general sense, the trend is simply the direction of the market, which way it is moving” (Murphy 1999). More precisely defined “a trend is a time measurement of the direction in price levels covering different time spans” (Pring 2002).
The stock market does not move in a straight line in any direction. The price movements are characterized by a series of zigzags. These zigzags are caused by a series of successive waves with peaks and troughs. From the opinion of Murphy “it is the direction of those peaks and troughs that constitutes market trend” (1999). There are a vast number of trends, but three that are most widely followed in practice. Those are the primary or major trend, the intermediate trend and last but not least the short or near-term trend (Murphy 1999). In practice, the durations of those three trends are not clearly defined. The primary trend is generally defined as a period of at least nine months up to at most two years. The intermediate trend extends over a period of at least six weeks to at most nine months whereas the short trend last to at most six weeks (Pring 2002).
In Addition to its time dimensions trends are also be differentiated by their directions (Cesar 1996). There are three possible directions in which a trend can move – upwards, downwards and sideways. Thus it is distinguished between upward trend, downward trend and sideways. According to Murphy “an upward trend would be defined as a series of successively higher peaks and troughs; a downward trend is just the opposite, a series of declining peaks and troughs; horizontal peaks and troughs would identify a sideways price trend” (1999).
Figure 1 (chart was created by the authors in MetaStocks 9.1) shows the stock price movements of Daimler Chrysler AG during a period of one and a half year in order to prove the existence of the afore described trends in practice.
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Figure 1: Primary, intermediate and short-term trend as well as upward trend, downward trend and sideways shown by the example of Daimler Chrysler AG, period: 2006/06/01 – 2007/12/31
The primary trend is an upward trend and lasts all over the period of one and a half year (blue lines). The primary trend in itself consists of a number of intermediate trends, e.g. an downward trend (green lines) that extends over two months. The intermediate trend includes various short term-trends, e.g. sideways price movements, that last approximately three weeks.
That leads two the conclusion that a primary trend with one trend direction exists of a vast number of intermediate trends, which could have all of the three trend directions. According to intermediate trends it counts analogously the same (Murphy 1999).
2.2.1.2.1.2.1. Support and Resistance
The understanding of support and resistance is essential for further concepts such as continuation and reversal patterns under 2.2.1.2.1.2.3. and 2.2.1.2.1.2.4., because those are based on the acknowledgement of the basic ideas of support and resistance (Pring 2002).
Price movements of stocks are characterized by a series of peaks and troughs which lead to the concept of support and resistance.
In general “the troughs, or reaction lows, are called support” (Murphy 1999). The support level on a chart lies under the current market price and is allocated where demand exceeds supply at a special price level (Cesar 1996). This results in a halt of the decline and prices turn back up again.
According to this, the peaks, or reaction highs, are called resistance (Murphy 1999). The resistance level on a chart lies above the current market price and is allocated where supply exceeds demand (Cesar 1996). As a result, the increase is to be halted and the prices turn down again.
In the following the practical aspects of support and resistance are illustrated by the example of BASF AG in figure 2 (chart was created by the authors in MetaStocks 9.1).
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Figure 2: Support and Resistance areas applied by the example of BASF AG, period: 2007/01/01 – 2007/12/31
So far support is defined as a previous low and resistance as a previous high, but however, this is not always the case.
“Whenever a support or resistance level is penetrated by a significant amount, they reverse their roles and become the opposite” (Murphy 1999).
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