Moving Average Convergence Divergence Research Articles

Web-Based Decision Support Systems Application of Stock Recommendation Using Bayesian Methods

We propose an application that can support traders by providing recommendation about the right stock transaction. The expected impact from this application is to reduce the risk of loss, even achieve the maximum profit for traders who use this application. Recommendation that resulted by application is based on Bayesian methods calculation and four technical analysis indicators that most commonly used by stock experts, i.e. Bollinger Bands, Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), and Stochastic Oscillator. Methodology used in this paper consists of data collection, data analysisa, application design, implementation, and testing. From the results of application testing, the accuracy of the application is 87,37%.

Long Term Trend Analysis in the Capital Market – The Case of Serbia

Abstract The paper explores the possibility of making investment decisions in emerging markets by using the trend analysis method on a particular example of the capital market in Serbia. The authors, starting from the common features of technical analysis, have analysed the common share index value in the capital market in Serbia, in the Belgrade Stock Exchange - Belexline from 1 March 2006 to 31 March 2009, by the usage of two moving averages method - Moving Average Convergence Divergence (MACD): an intermediate term of 50 days and a long-term one of 100 days. The above mentioned moving averages identify the establishment of a trend, the cessation of the existing one, a change and an establishment of the new one. The capital market in Serbia had two distinctive long-term trends within the above mentioned observed period of time. The method of two moving averages in combination with the MACD indicator analysis gave quite reliable signals of weakening and change of the long-term trend direction. Analysis of the long-term trend has not been considered for the period from 2009 to date because the market during this period was illiquid with little trading volume, while some stocks that are entered in the Belexline are not more subject of trade.

Moving Average Convergence Divergence filter preprocessing for real-time event-related peak activity onset detection : application to fNIRS signals.

Real-time solutions for noise reduction and signal processing represent a central challenge for the development of Brain Computer Interfaces (BCI). In this paper, we introduce the Moving Average Convergence Divergence (MACD) filter, a tunable digital passband filter for online noise reduction and onset detection without preliminary learning phase, used in economic markets analysis. MACD performance was tested and benchmarked with other filters using data collected with functional Near Infrared Spectoscopy (fNIRS) during a digit sequence memorization task. This filter has a good performance on filtering and real-time peak activity onset detection, compared to other techniques. Therefore, MACD could be implemented for efficient BCI design using fNIRS.

Stock Market Simulation Using Support Vector Machines

ABSTRACTThe aim of this research was to analyse the different results that can be achieved using support vector machines (SVM) to forecast the weekly change movement of different simulated markets. The markets are developed by a GARCH model based on the S&P 500. These simulated markets are grouped by a main parameter: high volatility, bearish trend, bullish trend and low volatility. The inputs retained of the SVM are traditional technical trading rules used in quantitative analysis, such as relative strength index (RSI) and moving average convergence divergence (MACD) decision rules. The outputs of the SVM are the degree of set membership and market movement (bullish or bearish). The design of the SVM algorithm has been developed by Matlab and SVM‐KM. The configuration for the SVM shows that the best results are achieved in simulated markets with high volatility; also results are good in trend simulated markets. Copyright © 2014 John Wiley & Sons, Ltd.

A Predictive Stock Market Technical Analysis Using Fuzzy Logic

Decision making process in stock trading is a complex one. There are numbers of technical indicators that are used by traders to study trends of the market and make buying and selling decisions based on their observations. This research seeks to deploy fuzzy inference to stock market, with four indicators used in technical analysis to aid in the decision making process in order to deal with probability. The four technical indicators are the Moving Average Convergence/Divergence (MACD), Relative Strength Index (RSI), Stochastic Oscillator (SO) and On-Balance Volume (OBV). The fuzzy rules are a combination of the trading rules for each of the indicators used as the input variables of the fuzzy system and for all the four technical indicators used, the membership functions were also defined. The result is a recommendation to buy, sell or hold. Data were collected for two Nigerian banks for testing and evaluation of the system. The technical indicators were then computed for each data and from the computed technical indicators; experiment was carried out for two months. The system generated satisfactory recommendation as when to buy, sell or hold, when the output is compared with actual data collected from the Nigerian Stock Exchange. The system can therefore act as an effective model for traders in the stock market when there is a combination of the recommendation with the individual’s trading skills.

Trading with Tigers: A Technical Analysis of Southeast Asian Stock Index Futures

ABSTRACTOur paper examines the profitability of technical trading rules in Southeast Asian (SEA) ‘tiger cub’ stock index futures markets during and after the global financial crisis (GFC) of 2007/2008. Using daily closing price data from 2007 to 2012, we explore technical trading rules such as exponential moving averages (EMA (20), EMA (100), EMA (20,100)) and moving average convergence divergence (MACD) in Indonesia, Malaysia, the Philippines and Thailand. The findings reveal that after applying trading rules that account for transaction costs and risk, abnormal profits cannot be achieved above a naı¨ve ‘buy-and-hold’ strategy (with the exception of EMA (100) and EMA (20,100) in Indonesia, and EMA (20,100) in both the Philippines and Thailand). There appears to be some degree of success with the application of longer-term trading rules; however, unless transaction costs can be reduced, investors are best advised to pursue passive investment approaches. Despite the economic uncertainty associated with the GFC and ongoing market volatility, it appears that SEA tiger cub stock index futures markets are weak-form efficient.

A Flexible Approach Towards Multi-frequency Re-engineering of the Moving Average Convergence Divergence Indicator

The study develops an innovative and flexible methodology for re-defining the traditional convergence–divergence indicators in the light of multi frequency trading behaviour of the heterogeneous agents. The developed indicator is labelled as multi-resolution convergence divergence indicator (MRCD). In contrast to the traditional moving average convergence divergence (MACD), the MRCD is “flexible” as it reacts to fluctuations arising at any frequency interval and is thereby capable of adapting to a wide variety of future possibilities. The “innovative dimension” underpinning this methodology is the replacement of the traditional trend extractor (moving-average) with a more novel methodology—the multi-resolution analysis. The forecasting ability of this newly engineered indicator is examined by structuring a neural network based MRCD–NARX model. The performance of this model is bench-marked against that of a similar model developed using the traditional MACD indicator. Out-of-the sample mean square error and the Diebold–Mariano test are used to examine the statistical accuracy of the forecasts. The profitability of the indicator is ascertained using the correlation measure and the hit ratio. A “long-short trading rule” is developed and back-tested on the testing data-sample to validate the practical applicability and “reproducibility” of the methodology.

Revisiting the Performance of MACD and RSI Oscillators

Chong and Ng (2008) find that the Moving Average Convergence–Divergence (MACD) and Relative Strength Index (RSI) rules can generate excess return in the London Stock Exchange. This paper revisits the performance of the two trading rules in the stock markets of five other OECD countries. It is found that the MACD(12,26,0) and RSI(21,50) rules consistently generate significant abnormal returns in the Milan Comit General and the S&P/TSX Composite Index. In addition, the RSI(14,30/70) rule is also profitable in the Dow Jones Industrials Index. The results shed some light on investors’ belief in these two technical indicators in different developed markets.

Designing a Stock Trading System Using Artificial Nero Fuzzy Inference Systems and Technical Analysis Approach

This paper has been designed a stock trading systems using Artificial Nero Fuzzy Inference Systems (ANFIS) and technical analysis approach. The proposed model receives 14 last days information and predictes 14 next day's variables' values Simple Moving Average (SMA), Exponential Moving Average (EMA), Moving Average Convergence - Divergence (MACD), Relative Strength (RSI), stochastic oscillator (SO) using ANFIS. Then, the net output are changed to signal of buy and sell after apply trading rules. In the next step, the final signal is created by the sum of generated signals. Thus, bye and sale will propose during the next 14 days. Performance Designed systems were studied for 17 shares. Results showed that the mean of all generated networks Percentage of correct predictions (96/55%) is more than random cases (50%). Given the positive returns SMA ?EMA ?SO and proposed method It's can be results that using these indices of technical analysis can predict trading optimal time of Iran stock market.

Could a Trader Using Only “Old” Technical Indicator be Successful at the Forex Market?

The use of technical analysis indicators for trading is widely known and discussed. Quite a large number of indicators and the long time period of their usage provide opportunities for creating profitable and successful trading strategies. On the other side technical analysis indicators were constructed for the stock market and therefore to traders on the Forex market it places the question. Can be a strategy based purely on technical analysis indicators profitable on the market with high volatility? Do we use the old, proven indicators, or use the newer ones? Will indicators generate good trading entries in time of crisis? The paper tries to find answers to some of these questions. On the basis of Moving Average Convergence Divergence (MACD) indicator, the trading strategies have been developed and back-tested at the Forex market with different timeframes. An important element of the research is to distinguish the time period of the crisis and beyond the crisis period and tested success of created strategies at the major, most traded currency pair. At the end of the paper the performance and profitability of the created strategies are discussed.

An Algorithm for Testing the Efficient Market Hypothesis

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH).

TECHNICAL ANALYSIS OF FUZZY METAGRAPH BASED DECISION SUPPORT SYSTEM FOR CAPITAL MARKET

This study proposes a Fuzzy Metagraph based Decision Support System (DSS) for short term and long term investment in share market. This rule base decision system will help traders to make correct decision at very low risk. Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD) and WILLIAM- %R are some of the Technical Indicators which are used as input to train the system which is integrated with Fuzzy Metagraph. This approach of incorporating Fuzzy Metagraph with RSI, MACD and WILLIAM-%R would be a new attempt in decision making on share market investment. Stocks listed in Bombay Stock Exchange (BSE) in India are used to evaluate the performance of the system. The results obtained from the proposed Fuzzy Metagraph based model are found to be satisfactory with very low risk. Three most used technical indicators MACD, RSI and WILLIAM-%R integrated with Fuzzy Metagraph are used to support the system. This method reduces the risk factor considerably for both short term and long term investors.

Multi-objective Optimization of Technical Stock Market Indicators using GAs

financial researches showed that technical indicators are useful tools for stock prediction. Technical indicators are used to generate trading signals (buy/sell) signals. The main problem of an indicator usage is to determine its appropriate parameters. In this paper a new GA based technique for optimizing the parameters of a collection of technical indicators over two objective functions Sharpe ratio and annual profit is proposed. The technique handles four indicators DEMAC (Double Exponential Moving Average Crossovers), RSI (Relative Strength Index), MACD (Moving Average Convergence Divergence), and MARSI (Moving Average RSI) indicators. The technique was tested on 30 years of historical data of DJIA (Dow Jones Industrial Average) stock index. Results showed that the optimized parameters obtained by the proposed technique improved the profits obtained by the indicators with their typical parameters, the Buy and Hold strategy and the random strategy.

Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies

The aim of this research is to examine the result of the application of the indicators Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Momentum and Stochastic in different companies of the Spanish continuous market. By using these indicators, it is intended to give purchase and sale recommendations to small investors. The generation of great capital gains depends on the type of the stock exchange company and the indicator which is being used. In addition, this research solves the problems in case of ambiguity, in the indicators, for the traders.

Stock Prediction Based on Phase Space Reconstruction and Echo State Networks

In this paper a synthetic model for stock prediction is proposed based on phase space reconstruction, Echo State Networks (ESN) and Moving Average Convergence/Divergence (MACD). In this model, time series data is reconstructed in phase space before feeding to the ESN. Guided by the MACD strategy, stock prices are predicted and valuable trading advices are provided. The proposed model is tested by Microsoft Company stock price. The experiments are compared with those provided by other models such as BackPropagation Neural Networks (BNN), Support Vector Machine (SVM), Hidden Markov Model (HMM) and Procedural Neural Networks (PNN). The test results show that the proposed model is effective and efficient in stock price prediction.

SMA and MACD combinations for stock investment decisions in frontier markets: evidence from Dubai financial market

One of the most challenging financial decisions is when to buy and sell stocks. Frontier markets offer high profit opportunities but also have high risk. Consequently, technical analysis is used to assist in properly timing entry and exit points from stock trades. Previous research presented applications of technical analysis in developed and emerging markets since they, unlike frontier markets, exist in an environment of political stability, regulations, and liquidity. This paper shows how trade signals generated from Simple Moving Average (SMA) confirmed by Moving Average Convergence Divergence (MACD) can be used to minimise trading risk in frontier markets such as Dubai Financial Market (DFM). The results show that the standard time-periods for SMA and MACD do not apply well to frontier markets and that trade signals generated from SMA and confirmed by signals generated from medium to long-term MACD or vice versa result in excellent hit ratios.

Using Two Sets of Multiple Moving Averages of Price to Time Positions in a Portfolio of Exchange Traded Funds

This paper attempts to determine if the use of two sets of multiple moving averages of price can be employed to generate above market portfolio rates of return in a portfolio of exchange traded funds. A set of short term moving averages of price and a set of long term moving averages of price and the relationship within each set are used to determine the timing of entry and exit points for establishing positions in the exchange traded funds (ETFs). Returnsusing the moving average convergence divergence (MACD) indicator and a combination of the short term MACD and long term MACD to determine entry and exit points are compared to a buy and hold strategy of the S&P 500 Index. The portfolio returns over a five year time period (1/1/2006 – 12/31/2010) are calculated and compared to their S&P 500 benchmark. A comparison is then performed between a portfolio of seven exchange traded funds using thecombined S-T MACD indicator and the L-T MACD indicator for entry and exit points to a buy and hold equally weighted and rebalanced portfolio comprised of the same exchange traded funds. The asset classes represented in the portfolio include domestic equities, developed foreign equities, emerging market foreign equities, domestic bonds, precious metals, and real estate. The use of two MACD indicators used in sequence with different parameters was found to increase the return of a portfolio of exchange traded funds for the selected holding period over a buy and hold strategy.

Technical Trading Systems as Crystal Balls in Reducing Risk: The Malaysian Stock Market

This study investigates the advantage of technical analysis in reducing risk and generates profits and generates greater return than a passive strategy. Researcher examine the mean returns of 13 technical trading systems against the returns from a buy and hold strategy for the 7 year period from 1996-2009 for Malaysian stocks. The 13 technical trading systems are 1-30 dual simple moving average crossover, 5-20 dual simple moving average crossover, 3-7 exponential moving average crossover, Relative Strength Index (RSI), momentum, stochastic, Moving Average Convergence Divergence (MACD), five Channel Breakout Systems (CBO 20-20, CBO 20-10, CBO 20-5, CBO 10-5 and CBO 15-5) and the Directional Movement Index (DMI). The findings reveal that 12 out of 13 trading systems produced significantly positive gross returns when no transaction costs were involved. These findings refute the assertion that Malaysian stock prices are weak-form efficient suggesting that technical trading systems can be exploited to make abnormal profits.

Forecasting IBEX-35 moves using support vector machines

This research aims at examining the application of support vector machines (SVMs) to the task of forecasting the weekly change in the Madrid IBEX-35 stock index. The data cover the period between 10/18/1990 and 10/29/2010. A trading simulation is implemented so that statistical efficiency is complemented by measures of economic performance. The inputs retained are traditional technical trading rules commonly used in the analysis of equity markets such as the Relative Strength Index (RSI) and the Moving Average Convergence Divergence (MACD) decision rules. The SVMs with given values of the RSI and MACD indicators are used in order to determine the best situations to buy or sell the market. The two outputs of the SVM are both the direction of the market and the probability attached to each forecast market move. The best result that it has been achieved is a hit ratio of 100% using the SVM classifier under some chosen risk-aversion parameters. However, these results are obtained analyzing recent periods rather than using all the dataset information.

Simulasi Perdagangan Saham PT Tambang Batubara Bukit Asam, Tbk. dengan Macd dan Williams % Range

Moving Average Convergence Divergence (MACD) is a momentum indicator to determine the indication of the trend reversal point. Williams% Range is also a momentum indicator that can provide when reversal trend will occur. This analysis will use the data movement of stock prices for PT Tambang Coal Bukit Asam Tbk. (PTBA). PTBA stock prices are influenced by fundamental conditions such as limited supply of fuel which is rumored and coal is the main alternative fuels other than oil. Study period was 241 trade days. Data are analyzed in several periods and then fitted with the MACD indicator and Williams % R, then simulate the trade during the period of research studies to determine the level of trading profits or losses based on the combination of both these technical indicators. The conclusion of this analysis, the MACD is an indicator that is considered slow (lagging) in giving an indication of weakness, but in reverse the MACD is considered to provide an accurate indication of where the indication given is rarely wrong. Williams% R is an rapid indicator in anticipation of a reversal trend, but these indicators often give a false indication since this indicator is quite sensitive to the movement of stock prices goings go up or down.