Josip Arneric, Elza Jurun, Snjezana pivac describes that technical analysis is done to find out the price movements where as fundamental analysis is done to predict values by looking at the fundamentals of a particular company. They focuses on technical analysis in their article and defines that trend can be of two types on the basis of either time structure or general direction.
In their article they apply smoothing techniques by using simple moving averages. They also discussed Bollinger bands and relative strength index.
This paper mainly focused on the technical analysis by applying exponential weighted moving averages because of the disadvantage of simple moving averages by observing the Podravka stocks in order to find out difference in the long and short term strategies by finding out the reliable signals to buy and sell.
Professor Veroljub says in his article that the way of investing is to sell when prices are at top and to buy when prices are at lower whatever the patterns are. In his articles he has discussed the market efficiency theory, Classical theory, confidence theory and Dow Theory. He also differentiates between the Classical and Confidence theory.
He says that Technical analysis is mainly used by those who are interested in share prices movements and trends for a short period of time that according to him ranges from 1-3 months.
His article focuses on how people can be able to reach to the secrets of share prices and changes and movements in them. He says that it is very difficult to deal with stock markets because there are so many factors and those factors sometimes behave so unpredictably that people have very less chances to get something out of their investments or sometimes even both the experts or the investors have equal chances due to instability of market and factors.
He concludes that if we are not able to play with stock market efficiently then it is better to have profits more than inflation and with minimum risks by focusing on diversification.
Wing-Keung Wong, Meher Manzur and Boon-Kiat Chew (2002) article discuss that the helpful principle of technical analysis is to identify trends and then go with the trend whether it is occurring randomly or due to fundamental factors. He also discussed the techniques of moving averages and relative strength index (RSI) by applying it on Singapore stock exchanges.
His results shows that application of RSI using (touch, Peak and retracement methods) is good if used in non trending environment and the results indicate that using simple moving averages and 50 crossover method of RSI will provide good results excluding the transaction costs.
The whole article concludes that using indicators like RSI and simple moving averages in Singapore market provides positive gains. As it has also been seen that members of Singapore market uses such indicators and enjoy good results.
Manuel Ammann, Matthias Rekate and Rico Von Wyss The text of that article to show an outperformance of technical analysis. The extent of academic acceptance of using technical analysis is not so good as compared to its practical application and it has been said that technical analysis is combination of separate methods than a full proper system or method.
The article discuss that technical analysis is connected with the forces of demand and supply and sentiments in markets so it is very useful in short term also because technical indicators can be calculated and applied quickly whereas fundamental techniques may take days to apply.
They discussed simple moving average techniques, RSI and advance/decline ratios technique and applied it onto 18 stocks out of the Swiss Stock market and conclude that application of technical analysis including transaction costs provides results not more than a buy or hold strategy but advance/decline ratios are more helpful and successful even when transaction costs are taken into account.
Treynor and Ferguson (1985) has established the first theoretical model to apply technical analysis and model describes that investors choose strategies to hold a security for a particular time period either long or short in order to get benefit from it later after they receive private information at particular point of time. The model concludes that this private information is helpful only with the combination of some additional or further information.
Brown and Jennings (1989) in the article on outperformance of technical analysis says that portfolio strategies works so well when the market does not contain all relevant information and there are only few investors who are well aware of that information.
Osler and Chang (1995) in their research work on application of technical analysis by using "head and shoulders" and results showed that the charts technique also gives partially fruitful predictions.
William Brock, Josef Lakonishok and Blake LeBaron(1992) In his article describes that technical analysis is helpful in predicting future price movements by observing past prices and their trends and it also discuss that movements in supply and demand can also be seen from charts and graphs. According to the article, Technical analysis has been considered to be the most original form of investment and the oldest technique in this regard is presented by Charles Dow which can range from very simple to the extremes.
Their article explore moving averages and support and resistance levels in order to find out generation of signals for the long and short time period and then to check high and low hits of prices. Article says that we cannot allow to leave those false patterns which are not covered by technical analysis tools and techniques because it is very difficult to enquire too much about data but we can be able to reduce this problem either by providing full reporting of techniques used or by using a very long data and information.
So in their article, they used data series i-e Dow Jones Industrial Average (DIJA) and in addition to statistical tools applied bootstrap methodology.
The main focus of their study is on the simplest trading techniques and rules because they are helpful in finding out the much hidden patterns and trends but including transaction costs will make the application of Technical rules more powerful.
So the article concludes that application of technical rules using moving averages and support/resistance are not consistent when compared with the models of AR (1), GARCH-M and Exponential GARCH.Buy signals are more useful and less volatile in getting positive returns as compared to the sell signals.
Michael D. Goldberg and Stephan Schulmeister (1988) the text of the Article explains the technical analysis and market efficiency. The concept that Financial markets are efficient discuss that in such world, the use of trading rules on the basis of previous price movements is not reasonable but on the other hand, according to the efficient market views, Technical analysis has its own importance and is well-known in today's market.
They says that application of trading rules sometimes at a particular period of time are profitable but in fact causes some of investors to consider mistakenly that they have able to beat the market. But if done for proper time, will result in finding that these are only "noise" which makes us feel that it is profitable.
Another major finding is the above text Article is that technical analysis rules are more profitable when the amount of data is increased; it means investors can have more profits with hourly data as compared to the daily data. They conclude that generally used Technical rules are more constantly profitable as compared to Filter rule.
The text of the article also focuses on using trading rules on the basis of gross returns, on the basis of net returns and concludes that past prices do contain some information relevant for predicting future prices. And that Flter rule produces large number of trading signals.
The text of Article presents an analysis based on observation and experiments on the profitability of stock market from 1970-1980 to check whether excess profits can be gained by using the information in past prices of stocks and the results showed that stock prices do contain such profitable information but such information is unsuccessful in future markets and so market in broader view is not efficient.
One of the major results of the study concludes that technical rules are more successful with hourly data as compared to daily data.
Paul A. Weller, Geoff C. Friesen and Lee M. Dunham (2007) the text of the article is to explain the theoretical and empirical examination of price trends and patterns in Technical analysis. Technical analysis has been defined in the Article as to use information from the past price trends and movements which are then summarized into charts which then helps investors to predict price movements in future. Such signals are widely used by practitioners but have very little importance in academics. The aim of the Article is to find out the success of both trend following and pattern based technical rules by the help of confirmation bias model with an introduction of single cognitive bias.
It is also the part of argue that many people who are making investments without proper know how will make poor decisions and will try to rationalize their decisions by biasing with their interpretations about the information important for accessing the results of decisions.
The model contains the arrived information which is then modeled with signals of different magnitudes at different frequencies. They also find that markets react similarly to public information as well as private information but there are some models in which reaction towards public and private information differs.
Article supports the model and tells that it produces well standard patterns of prices and these patterns can be exploited by trend following technical rules. Several predictions made by the model is that return autocorrelations are negative for short period of time, positive for halfway and then again negative for long time period. The Article also shows that less frequency signals are more informative because they are clearer.
For the purpose of showing results about price patterns, "Head and Shoulders" pattern has been used and experimentation shows that both "Head and Shoulders" and "inverted Head and Shoulders" patterns shows healthy results for different values used and different intervals among the signals.
The above text concludes that: a model is made in which people are subject to proof biasness and the model produces three results. First the model uses price patterns that confirm certain well-known trading methods especially the "Head and Shoulders" patterns. Second it has been found by the model application that autocorrelations varies according to time periods and last was that the sequential changes in prices for a certain stock will be positively auto correlated.
Kadida Ramadhani Shagilla Mashaushi (2006) the text of the Article shows the analysis of Technical trading strategies. In the 1980s, Technical strategies have made a significant "come back" for predictions and it motivated researchers to reconsider technical analysis as Well. Observed evidence from many recent studies has shown that returns are Knowable from the current price, past prices and other variables like volume etc.
It has been noticed that the theoretical basis of technical analysis is not generally Accepted as the efficient market hypothesis but still few previous works explains why technical analysis is used to make profits and forecast price movements in a way similar to Efficient Market Hypothesis (EMH).The Article also follows the risks estimations while doing Technical analysis strategies. The common objective of this thesis, therefore, is to examine the differences in risk levels between stocks groups in particular market and predictability and profitability from technical trading rules.
Moving average based trading systems are the simplest and most popular trend-following systems among practitioners. Moving average systems take different forms according to the method used. In this study, two moving average systems are virtual: the Simple Moving Average with Percentage Price Band and the Dual Moving Average Crossover. The Moving Average with Percentage Price Band system uses a simple moving average with a price band centered around it. The Dual Moving Average Crossover system is the comparison of two moving averages, generating a buy (sell) signal when a short-term moving average rises (falls) above (below) a long-term moving average. Since previous studies, it has been argued that the role of Technical analysis differs a lot both in practicality and in academics. Some previous studies favors that Technical strategies are still profitable as the charts do contain such information that is beyond the already contained information and some argue that Technical strategies give different results in different times.
The research in the predictability of assets return results in EMH theory which has three forms and assumptions OF EM discussed in the Article is: there is need of such participants who want to earn maximum profits and they do analyze and give value to the securities. Secondly the information regarding the stocks in any market arrives according to trends and fashion and other news and announcements are therefore in general independent. Last is that the investors should quickly adjust the stocks prices in order to reflect the effect of arrived information.
In the Article, the theoretical basis of Technical analysis also focuses on the theories explaining the behavior of prices.
This paper mainly conclusion is about the effectiveness of technical analysis in the course of the `risk premium view'. Results show that First, we usually believe on the theoretical alternatives to the efficient market hypothesis theory which encourages potential for markets to be inefficient. It then investigates the link between the risk involved in trading rule methods and procedures and the resulting excess returns. The observed analysis is done by taking a sample of Stocks drawn from the London Stock Exchange, (LSE), portfolios constructed from three US markets; the New York Stock Exchange, (NYSE), the American Stock Exchange, (ASE), and the National Association of Securities Dealers Automated Quotation market, (NASDAQ). And the data is taken from ten small emerging markets of Africa. The analyses find that, to large degree liquidity, book-to-market ratio, and other arrangements can explain the excess profits from technical analysis. Empirical tests have been conducted to judge the suitability of some risk estimates for trading rules. Some recently developed techniques have been used with the belief that certain risk estimates may not be appropriate for adjusting trading rule returns for risk.
Michael D. McKenzie in an Article explains Technical trading rules in emerging markets and the 1997 Asian currency crises. The term 'technical analysis' in the article is again defined as: it is the wide range of systematic tools and techniques which share a common idea that the past can be used to predict the future. In general, the evidences suggest that some trading rules do hold predicative power, but this does not helps us in getting the information which is profitable for us because of the element of trading costs.
The intend of this paper is to provide further evidence on the predictive ability of three common classes of technical trading rule: the Variable Length Moving Average, Fixed Length Moving Average and Trade Range Breakout. These three rules have proven to be most popular in the literature and their use will help us in making comparisons with the previous done researches.
In this paper, both techniques of t-statistics and boot strap are used to check its impact on the importance of the results established. The Article also provides some observations on how the trading volume affects our ability of predictions by using Technical trading methodologies and also clarifies on whether or not the information provided by such rules can be used profitably.
In this paper, only rules that belong to the final grouping are considered because they collectively signify the most widely tested group of technical trading rules.
The previous analysis discusses the ability of Technical trading rules to forecast price movements and clearly found that technical rules do have predictive ability to forecast in the form of positive returns to buy signals and negative from sell signals. The estimated returns discussed should not be confused with profits, which are basically net of transaction costs but appropriate to be suitably termed as pre-cost trading returns. The cost of carrying out is necessary in order to find out whether these rules generate profitable trading opportunities or not.
Large range of markets has been considered in this paper but still it is very difficult to provide detailed information on the cost of trading on each exchange. Based on the evidence presented in this paper, the 1997 currency crisis constitutes an event that the common nature and direction of movements of prices in the market affects the ability of technical trading strategies to forecast returns.
This paper considers the ability of a large range of simple technical trading strategies to forecast future stock market movements for a model of 17 emerging markets taken from the period of January, 1986 to September, 2003. Some of the trading rules were helpful in providing significant returns, but the information can be exploited on time. The usefulness of technical trading rules can be checked by looking at the market conditions and trading volume because they play an important role in determining the usefulness.
