Technical Analysis Models Research Articles

Novel comparative methodology of hybrid support vector machine with meta-heuristic algorithms to develop an integrated candlestick technical analysis model

PurposeThe proposed model has been aimed to predict stock market signals by designing an accurate model. In this sense, the stock market is analysed by the technical analysis of Japanese Candlestick, which is combined by the following meta heuristic algorithms: support vector machine (SVM), meta-heuristic algorithms, particle swarm optimization (PSO), imperialist competition algorithm (ICA) and genetic algorithm (GA).Design/methodology/approachIn addition, among the developed algorithms, the most effective one is chosen to determine probable sell and buy signals. Moreover, the authors have proposed comparative results to validate the designed model in this study with the same basic models of three articles in the past. Hence, PSO is used as a classification method to search the solution space absolutelyand with the high speed of running. In terms of the second model, SVM and ICA are examined by the time. Where the ICA is an improver for the SVM parameters. Finally, in the third model, SVM and GA are studied, where GA acts as optimizer and feature selection agent.FindingsResults have been indicated that, the prediction accuracy of all new models are high for only six days, however, with respect to the confusion matrixes results, it is understood that the SVM-GA and SVM-ICA models have correctly predicted more sell signals, and the SCM-PSO model has correctly predicted more buy signals. However, SVM-ICA has shown better performance than other models considering executing the implemented models.Research limitations/implicationsIn this study, the authors to analyze the data the long length of time between the years 2013–2021, makes the input data analysis challenging. They must be changed with respect to the conditions.Originality/valueIn this study, two methods have been developed in a candlestick model, they are raw based and signal-based approaches which the hit rate is determined by the percentage of correct evaluations of the stock market for a 16-day period.

Public Awareness in Paying Land and Building Tax in Indonesian

This study aims to describe and analyze how PBB-P2 payment policies are implemented. It will also tell and analyze the factors that help and hurt the policy's implementation, based on Malang Regency Regional Regulation number 1 of 2019 about changes to Regional Regulation number 8 of 2010 about regional taxes in Lawang District. The type of research is descriptive research with a qualitative approach, and this study implementation of PBB-P2 Payment Policy Based on Malang Regency Regional Regulation Number 1 of 2019 concerning Amendments to Regional Regulation Number 8 of 2010 regarding Taxes. Also, Miles and Huberman's interactive technical analysis model was also used to look at the data. This model has four stages: data collection, data consolidation, data presentation, and conclusions. The study's results show that the communication factor shows how clear policymakers' instructions are, even though several things need to be written down in the regional regulation. Also, the level of human resources education affects their ability to manage monthly reports, so they need help from UPT officers. The facilities for paying PBB-P2, however, are enough and make payments more manageable. Policy executors' willingness to send in SPPT on time, a clear bureaucratic structure, and policy executors' cooperation and support for sending due dates to taxpayers. Factors supporting implementing PBB-P2 payment policies include rewards, proof of ownership, and procedures by the District Government of Lawang. Meanwhile, inhibiting factors include taxpayers being reluctant to pay their taxes and no taxpayers being found.

Improving Stock Trend Prediction using LSTM Neural Network Trained on a Complex Trading Strategy

Abstract: Technical analysis in stock trading addresses the crucial matter of making optimal trading decisions promptly. Predicting directional movement in the target market using technical indicators is quite common. Besides its many other applications, machine learning helps to solve the algorithmic trading problem of determining optimal trading positions, and some types of deep neural networks have been proven as up-and-coming methods for forecasting the returns of the stock market. The current work presents the idea of training a neural network on a new trading strategy, named, Unified Trading Strategy (UTS) that integrates technical indicators from three well-known categories referred to as leading, lagging, and volatility. The trained network serves as an excellent alternative to the classical technical analysis model by simplifying the process of finding potential events of effective trade with better performance and reusability.

Trading strategy based on investment diversification technical analysis model

This paper takes gold and bitcoin as research objects and develops a model for traders. In this period, we established a multivariate quantitative technical analysis model of investment, selected 6 technical indicators with low correlation MA, MACD, BOLL, RSI, KDJ and Stoch RSI as evaluation indicators of trading intentions, and used the fuzzy evaluation model to combine the trading intentions of the 6 indicators to obtain the final daily trading intentions score. Combined with the trading intention score and risk tolerance coefficient of the day to adjust the asset allocation, the investment trading model proposed in this paper can provide support for relevant practitioners and has practical application significance.

Developing an integrated social, economic, environmental, and technical analysis model for sustainable development using hybrid multi-criteria decision making methods

Selecting an appropriate location for a large infrastructure project poses difficult situations. It shall satisfy sustainability indicators and establish harmony among multiple goals of multiple stakeholders. In such a situation, Multi-Criteria Decision Making techniques allow assessing qualitative and quantitative attributes, analysing and removing subjective biases and help in arriving at objective decisions. However, a single Multi-Criteria Decision Making technique may not be an effective tool to generate concrete results as there is no validation of the results. By utilising hybrid Multi-Criteria Decision Making methods, one can incorporate, gauge, and assess the range of social, economic, and environmental impacts precisely and achieve an accurate result by validating results by other methods. Therefore, this paper develops a model called as Social, Economic, Environmental and Technical Assessment model. It combines four fuzzy Multi-Criteria Decision Making techniques viz. Fuzzy Stepwise Weighted Assessment Ratio Analysis, Fuzzy Multi-Objective Optimization by Ratio Analysis, Fuzzy Weighted Aggregated Sum Product Assessment and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution. This paper utilises the case of hydropower plants in India, how the policy and decision-makers can arrive at the selection of the best location for an infrastructure project. According to the assessment value, Teesta Low Dam IV (Darjeeling, West Bengal) isthe preferred hydropower plantfor all selected methods. The State could bring social justice, ecological stability; achieve economic benefits and sustainability by appropriating this proposed model in other development fields.

PENGARUH MOTIVASI DIRI DAN PEMBERDAYAAN DOWN LINE TERHADAP EFEKTIVITAS KEPEMIMPINAN TRANSFORMASIONAL PADA PT. RATU NUSANTARA DI KOTA AMBON

This study aims to analyze the influence of self-motivation and empowerment of human resources (down line) on the effectiveness of transformational leadership (study at PT.Ratu Nusantara in Ambon City), using the several technical analysis model / tool. There are several techniques / approaches to collecting data, namely through interviews, observations, questionnaires and literature. Indicators used to measure the effect of self motivation and downline empowerment on the effectiveness of transformational leadership are motivation, namely the need for achievement, affiliation needs, power needs. Whereas for empowerment that builds strengths and resources by encouraging, motivating and raising employee awareness of their authority and striving for their development. While the effectiveness of transformational leadership is a leader with integrity according to words and actions, which shows the attitude of trustworthiness / honesty as the foundation of a trusting relationship between leaders and employees. The results showed that the coefficient of determination was 0.563 or 56.3%. This means that the two independent variables (self-motivation variables and empowerment variables) in this study were only able to explain 56.3% of the variation that occurred in the dependent variable (the effectiveness of transformational leadership). While other variations of 100% - 56.3% = 43.7% are explained by other variables not explained in this research model. Keyword: Self Motivation, Empowerment of Human Resources (down line), Transformational Leadership

The Integration of Fundamental and Technical Analysis in Predicting the Stock Price

Fundamental Analysis and Technical Analysis have long been used by investors as an analysis instrument to predict the stock price in gaining optimal return. The purpose of this study is to test the predictive ability of Fundamental Analysis and Technical Analysis model partially, then simultaneously test the integrated model of both analysis. The scope of this study includes the listed companies in LQ 45 stock exchange during 2007- 2016 period. The Fundamental Variable used in this study are Earning per Share (EPS), Dividend Payout Ratio (DPR) and Return on Equity (ROE). The Technical Variable used is the price during the previous six months ( price t-0.5), Positive extreme price increase (D-Up), and Negative extreme price decline momentum (D-Down). The result of this study shows that Technical Model produces highest predictive ability compared to the other two models, while Integration model produces higher predictive ability compared to fundamental model. Using Integration model, EPS variable affects positively and significant, DPR variable affects negatively and insignificant, ROE variable, t-0.5, and D-Up affect positively and significant, while variable D down affects negatively and insignificant to the Stock Price. This result indicates that investors need to combine both analysis models i.e. fundamental and technical to generate optimal stock returns. 
 
 Keywords and phrase : Earning Per Share, Dividend Payout Ratio, Extreme Positive Momentum, Extreme Negative Momentum.

New efficient hybrid candlestick technical analysis model for stock market timing on the basis of the Support Vector Machine and Heuristic Algorithms of Imperialist Competition and Genetic

In this paper, two hybrid models are used for timing of the stock markets on the basis of the technical analysis of Japanese Candlestick by Support Vector Machine (SVM) and Heuristic Algorithms of Imperialist Competition and Genetic. In the first model, SVM and Imperialist Competition Algorithm (ICA) are developed for stock market timing in which ICA is used to optimize the SVM parameters. In the second model, SVM is used with Genetic Algorithm (GA) where GA is used for feature selection in addition to SVM parameters optimization. Here the two approaches, Raw-based and Signal-based are devised on the basis of the literature to generate the input data of the model. For a comparison, the Hit Rate is considered as the percentage of correct predictions for periods of 1–6 day. The results show that SVM-ICA performance is better than SVM-GA and most importantly the feed-forward static neural network of the literature as the standard one.

A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters

In this study, we propose a stock trading system based on optimized technical analysis parameters for creating buy-sell points using genetic algorithms. The model is developed utilizing Apache Spark big data platform. The optimized parameters are then passed to a deep MLP neural network for buy-sell-hold predictions. Dow 30 stocks are chosen for model validation. Each Dow stock is trained separately using daily close prices between 1996-2016 and tested between 2007-2016. The results indicate that optimizing the technical indicator parameters not only enhances the stock trading performance but also provides a model that might be used as an alternative to Buy and Hold and other standard technical analysis models.

Technical Analysis as a Rational Tool of Decision Making for Professional Traders

ABSTRACTThe psychological background of technical analysis usage is investigated to further explain the popularity and common usage of technical analysis as an investment decision tool. Attitudes toward technical analysis of professional futures market traders and neophyte investors, represented by finance students, were examined. Technical analysis is one of the most popular methods supporting investment decisions and it is much more popular among future market traders than among neophyte investors. The concept of processing information was used to explain this phenomenon. Neophyte investors are more experiential and intuition-driven while using technical analysis models, while futures market traders are more rationally driven. Technical analysis methods help professional traders on futures markets, which are less transparent than regulated stock markets, to process information; those methods are perceived by them as rational, cognitive tools supporting their decision making.

What Makes Technical Analysis Popular?

According to the Efficient Market Hypothesis, investors cannot achieve above-average returns by using technical analysis tools. This paper attempts to answer the question as to what makes technical analysis popular, regardless of the efficiency of capital markets. The objective is to verify whether investors have certain cognitive inclinations that make them more likely to believe in the efficiency of technical analysis models. We postulate a positive relationship between different forms of overconfidence and faith in the effectiveness of technical analysis methods. This relationship was confirmed only in the case of the “better than average” effect. The two other examined forms of overconfidence, namely, overprecision and illusion of control, did not yield statistically significant results. However, the lack of confirmation by all three forms of overconfidence is in line with the results presented in the literature, namely, that there are no significant relationships between different forms of overconfidence.

O mercado acionário e o desempenho dos ativos financeiros no Brasil com emprego da análise técnica

This study aims to investigate the performance of technical analysis model used in the management of a portfolio, created from the shareholding with greater participation in the theoretical portfolio of IBOVESPA. It also evaluates the performance and the available return of shareholding portfolio comparing to other strategies and Brazilian financial assets. The period chosen to the analysis was from January 02, 2007 until August 29, 2008 and the twelve stockholdings, in order of participation in the IBOVESPA theoretical portfolio on December 28, 2006 that were Petrobras PN, Vale R. Doce PNA-N1, Bradesco PN-N1, Usiminas PNA, Telemar PN, Itaubanco PN-N1, Vale R. Doce ON-N1, Gerdau PN-N1, Siderurgica National ON, Net PNN2, VIVO PN and Petrobras ON. The evidences had pointed out that the management of stockholdings portfolio by moving averages from technical analysis model yielded 69.27% from January 02, 2007 up to August 29, 2008. Therefore, this result was higher than it was reached by the strategy of buy & hold from the same portfolio of 44,61%. Also this yield was greater than any other financial asset like investment fund or other indicator based on stockholding prices as IBOVESPA. Key words: technique analysis, stockholdings, Ibovespa, theoretical portfolio, mobile averages,capital market.