Inhaltsangabe:Introduction: The following paper will outline the suitability of Technical Analysis (TA), regarding selective chosen tools for performance increase versus the classic Buy-and-Hold-Strategy (BHS). These two approaches, beside the Fundamental Analysis (FA), are the foundations used by investors concerning their Investment strategy and differ substantially in their nature. Thereby, this dissertation will investigate whether the application of active TA is a productive approach, yielding to favourable results and having the ability to outperform the passive BHS. To achieve substantive results, the comparisons of performances will be stretched to 21 years and are based on the following three indices, which differ significantly concerning their location, volume and importance. Standard a Poor s 500 (SaP 500). German Stock Exchange (DAX). Japanese Nikkei 225 (N225). However, to reinforce the impression of the analysis, semi-annual and annual performances will also be measured. This is an essential element of the comparisons, as due to the nature of TA, the seed capital of 1.000.000 Sterling will not be invested at all times. In this case, the capital will yield the current base rate of interest of the Bank of England minus 0.5 % per annum. The measurements will be assessed by means of three established Indicators and Oscillators. Indicators: Exponential Moving Averages; 200 days and 100 days. Moving Average Convergence Divergence. Bollinger Bands. Oscillators: Relative Strength Index. Slow Stochastic. Momentum. TA can be divided into Chartism and the statistical based TA. Although a clear demarcation between these groups is not given in reality, as most proponents of TA combine both techniques. The vast majority of this dissertation will only reflect the latter. This can also be justified, as Chartists predict future price developments based on trend lines, patterns and formations. Murphy (1999) states that all Chartists are Technical Analysts, but not all Technical Analysts are Chartists. Due to the lack of standardised price characteristics, Chartism implies a high degree of subjectivity. Therefore, the absence of operational ability of this sub-area would not lead to a feasible analysis concerning an increase in performance. We maintain that financial markets are either moving in boom or bust cycles (Bull or Bear Markets). The classic BHS, based on the Investment-Legend Benjamin Graham, has generated high profits in the past. However, at least since the burst of the Dot-com-bubble in March 2000 this approach must be questioned and leads us to believe that timing and behavioural finance, do play an important role concerning an investment strategy. An Investor, following the BHS, can always wait and hope for a comeback of his underlying investment; however, would it not be more profitable and economically efficient to buy at low prices and get out at high prices? Investors use TA to benefit from movements through an accurate determination of buy- and sell signals. Clearly, the aim of this investment approach is to beat the classic BHS and the FA. The FA is based on the economical power of supply and demand, which leads to rising, declining or stagnating prices. The determining factor is the intrinsic value of the underlying asset. In case the value is below the current price, the asset is overpriced and should be sold. If the price lies under the fair intrinsic value, the asset should be bought. This approach is very time demanding as many further factors, for example domestic and foreign political and economic events and government policies must be considered as well. This approach is widely used by Wall Street Players (including the Oracle of Omaha Warren Buffet) and professional analysts. The TA stands in stark contrast to FA. The TA confines itself concerning profitable buy- or sell decisions only on the analysis of the current price of the underlying asset. Intrinsic values are considered as ineffective. Deployment of this assumption, the technical analyst attempts to beat the fundamental based proponent, through the provision of future price developments using historical data. In other words, the FA studies the causation of market movements, while the TA analyse their impacts. In contrast, the statistical based TA only uses computer-assisted trading signals, which are based and generated by an objective and unemotional trading system. These systems are composed of Indicators and Oscillators and eliminate any emotions from trading. This is crucial to set up an empirical and clearly comprehensible analysis that market participants are able to generate an excess return through TA. Unlike the BHS, TA also attempts to benefit from trend-less times where prices languish in no-man s land. Sophisticated short-selling techniques in short term or secondary downtrends, as a result of retracements and volatility impulses, can lead to substantial profits during times when the market oscillates between a certain range. Therefore, back-tests will demonstrate that TA enables investors to generate accurate buy/sell signals, complied with a consistent trading approach. The key aims of this dissertation can be illustrated as follows: Investigate the evidence that financial markets are not efficient. Evaluate if TA with the selected instruments during the chosen time period outperformed the BHS. Identify that TA will lead to different results on different markets despite a high grade of correlation. Explore and appraise the results and their significance. The paper is divided into a theoretical and a practical part. To understand the results of the practical part, it is essential to comprehend the functionality and meaning of the discussed Indicators a Oscillators. These will be explained in detail in the appendix. The first chapter of the paper will focus on an in-depth literature review. Therefore, I will investigate the share analysis and its premises, including a critical review of their strengths and weaknesses. In addition, I will look into detail if TA and its tools are theoretically suitable for the attempt to outperform the classic BHS. Furthermore, I will point out that financial markets are not perfectly efficient and the hypothesis of random walk can be seriously questioned. Evidence that these hypotheses can be falsified, would clearly underpin the theory that TA can lead to an increase in performance versus the classic BHS. The third Chapter will illustrate and outline the methodology, while justifying and explicitly defining the test conditions and tested indices. Chapter four will explain the three intentionally selected Indicators and Oscillators and clarify the chosen set-up. Generally, users of TA can adjust their set-up to some extent. The aim is to visualise to the reader how Indicators a Oscillators can be combined to read and analyse a chart and how to adopt those in current trades. Moreover, it will be explained and commented on why the analysis of TA in this paper applies to the three chosen Stock Exchanges. In Chapter five, the practical analysis will take place. Therefore, the three selected markets will be evaluated concerning their performance using the TA and the classic BHS. The sixth Chapter will examine the findings of the former chapter in more detail. This section will shed light on, why one of both trading techniques (TA vs. BHS) has achieved a better performance within a certain period and on different markets. An empirical comparison will show which of the different instruments of TA has lead to the most reliable and profitable outcomes. Chapter seven will briefly summarise the dissertation and critically answer the research question consistent with a discussion on the limitations of the conclusion. Furthermore, possible further future research will be alluded and give an outlook of trends and development potentialities of TA. Inhaltsverzeichnis:Table of Contents: TABLE OF FIGURESI GLOSSARYII 1.INTRODUCTION1 2.SHARE ANALYSIS AND ITS PREMISES5 2.1CLASSIFICATION AND DEVELOPMENT5 2.2DOW THEORY IN CORRESPONDENCE WITH TA6 2.2.1The Averages Discount Everything (except Acts of God )6 2.2.2The Three Trends7 2.2.3The History repeats itself10 2.2.4Criticism of the Dow Theory11 2.3RANDOM WALK THEORY IN CORRESPONDENCE WITH BHS12 2.3.1Criticism of the Efficient Market Hypothesis15 2.4FUNDAMENTAL ANALYSIS17 2.5TECHNICAL ANALYSIS VERSUS FUNDAMENTAL ANALYSIS17 3.METHODOLOGY20 3.1TEST CONDITIONS20 3.2TESTED INDICES23 4.INSTRUMENTS OF TECHNICAL ANALYSIS25 4.1INDICATORS25 4.1.1Moving Averages25 4.1.2Moving Average Convergence Divergence26 4.1.3Bollinger Bands27 4.2OSCILLATORS28 4.2.1The dilemma of Oscillators28 4.2.2Momentum28 4.2.3Relative Strength Index30 4.2.4Slow Stochastic31 4.2.5Combination of Indicators and Oscillators32 4.3APPROACH TO PERFORMANCE TESTS32 5.RESULTS/FINDINGS34 5.1BHS34 5.2EMA35 5.3MACD36 5.4BOLLINGER BANDS37 5.5MOMENTUM38 5.6RSI39 5.7SLOW STOCHASTIC40 6.ANALYSIS41 6.1EMA41 6.2MACD43 6.3BOLLINGER BANDS44 6.4MOMENTUM45 6.5RSI47 6.6SLOW STOCHASTIC48 7.CONCLUSION50 8.APPENDIX53 9.REFERENCES71 Textprobe:Text Sample: Chapter 4, Instruments of Technical Analysis: 4.1, Indicators: 4.1.1, Moving Averages: Moving Averages (MA) are one of the oldest, most common and multifaceted trend-following indicators and are an indispensable element of every sound trading-system. However, studies from Alexander (1961, 1964), Fama and Blume (1966), Levy (1967), Van Horne and Parker (1967) and James (1968) found evidence that the strict use of MA will not lead to abnormal returns comparing the BHS. In spite of these findings, this dissertation will attempt to justify the right to exist of this popular Indicator. Edwards et al (2007) among others declare that the most used time span of MA is 10-day, 30-day, 50-day, 100-day and 200-day, whereby those MA can either be used alone or in conjunction with each other. To avoid too much noise , the following tests will only consider the 100- and 200-day MA. This can be justified by the fact that the use of too many MA would generate too many trading signals, attended with the danger that entry or exits in positions are liable to false-breaks. Edwards et al (2007) suggest that False signals can be given when prices fluctuate in a Broad Sideways Pattern. One might argue that the chosen long periods and the limitations to two MA will lag behind trends and miss favourable signals. However, I think the aim of the scenario should not be the unlikely event to enter/exit at low/peak prices, but rather to capture the primary trends in terms of the test period of 21 years. Therefore, the set-up is based on the Double Crossover Method. That means that that a buy (sell) signal is generated, if the 100-day MA crosses the 200-day MA bottom-up (top-down). The used MA will be calculated on an exponential basis; that is that prices in the recent past have a bigger weighting. Furthermore, the calculation of the MA are exclusively based on closing prices. These prices are more meaningful as they indicate positions that market participants are willing to carry overnight. Precise information and an example can be viewed in appendix 4. 4.1.2, Moving Average Convergence Divergence: The MACD Indicator is a very popular Indicator and can be described as the further development of the Double Crossover Method, as it is a composition of three Exponential Weighted MA, however embodied in just two lines. The usual suspects like Fama (1965), Neftci (1991) or Hudson et al (1996) do not get anything out of the MACD in their studies. Nevertheless Brock et al (1992) among other authors conclude that the MACD outperform the BHS. Like most Indicators, the user has a free hand and can adjust the set-up relatively generously. The inventor of the MACD Indicator Gerald Appel realised that markets last a longer period in up-trends than in down-trends. Therefore, he suggests using MA periods of 8, 17, 9 for buy signals and 12, 25, 9 for sell signals. However, the standard calibration of 12-, 26-, 9-periods has de facto proven themselves and will be adopted in this paper. That is, the faster line (called MACD line) is the difference of the closing prices of the two EMA s 26 and 12, while the slow line (signal line) can be expressed as the 9-period EMA of the MACD line. Buy signals are triggered when the MACD line crosses the signal line from below. Sell signals arise if the faster line crosses the slower line from above. Additionally, the MACD Indicator displays stronger and weaker signals by means of overbought and oversold areas. Appel (1979) indicates that an overbought or oversold signal for the SaP 500 generates above/below plus/minus 2.50 on the MACD scale. Convergences and Divergences between the underlying security and MACD do not generate tangible trading signals, but possibly approve trends or warn of trend reversals. Please see appendix 5 for an example. 4.1.3, Bollinger Bands: Bollinger Bands (BB) consist of a 20-day MA, surrounded of two bands, which represent two standard deviations. Those assure that 95 % of prices range within these two bands and the remainder indicates that prices are overbought or oversold if one of the standard deviations is touched. The BB are an excellent instrument of TA in times when markets do not reside in clear trends and prices tend to fluctuate around a trading range. The standard deviations and the MA can be adjusted to personal preferences. Edwards et al (2007) elucidate that some investors increase the standard deviations to 2.5 or lower them to 1.5 and alter the MA to 50-day or alternatively 10-day. A higher standard deviation leads to an expansion of the higher and lower BB. Conversely, a lower standard deviation narrows the two bands where most of the data is contained. However, in the following tests the standard approach of two standard deviations (k = 2) and MA 20-day (n = 20) will be selected. BB have the attribute to expand or to contract. Thus, it appears that this instrument considers volatility and leads to the result that if the bands are far away from each other, it is likely that the trend draws to a close and accordingly if the bands are very tight, a new trend will possibly take root. A long signal appears if the price rebounds at the lower BB and crosses the 20-day MA. Accordingly, the price target will be the upper BB. A cross from above generates a sell signal, with a price target of the lower BB. The tests will follow the suggestion of Murphy (1999), Leung et al (2003) and Edward et al (2007) using BB in combination with the Relative Strength Index (RSI). Therefore, a short-position will only be entered if the RSI is above 80 and the price crosses the upper BB. Consequently, the index will not be bought until the price crosses the lower BB and the RSI falls below 20. A long position will be exited if the price closes above the upper BB. Vice versa, a short position will be closed if the closing price is below the lower BB. In appendix 6, an example is illustrated.This is an essential element of the comparisons, as due to the nature of TA, the seed capital of 1.000.000 Sterling will not be invested at all times.
|Title||:||Technical Analysis Myth or Magic?|
|Publisher||:||diplom.de - 2010-12-22|