scholarly journals Forecasting Stock Market Momentum in Nepal: Application of Fuzzy Logic Model

2021 ◽  
Vol 6 (1) ◽  
pp. 17-28
Author(s):  
John Koirala ◽  
Swachhanda Aabhas Rai
Keyword(s):  
Fuzzy Logic ◽  
Stock Market ◽  
Investment Decision ◽  
Fuzzy Model ◽  
Exploratory Research ◽  
Market Capitalization ◽  
Past Data ◽  
The Right ◽  
Stock Momentum ◽  
Total Market

Background: Stock market experts analyse various indicators to estimate the stock market, including historical prices, economic analysis, industry analysis and company analysis, but this study uses historical prices for the NEPSE index, making forecasting more precise. Purpose: The purpose of this study is to explore short-term stock market momentum using fuzzy logic. The study also aims to establish a suitable fuzzy model to predict stock momentum, reduce the risk, and make the right investment decision. Methodology/Design: This study employed exploratory research design to understand the problem of chaotic decision making in the stock market. The mathematical method employed in this study is membership functions, which are part of fuzzy logic. This includes only the commercial banks, as it has the highest market capitalization, 53.11% of total market capitalization. Using 14-day past data as a base, the suggested fuzzy model determines the stock index’s momentum over the next 5 days. Findings: The forecasted trend value for the Nabil, Civil, and Prime Commercial bank is 0.92, 0.92, and 0.80, which shows a bullish trend. Compared to previously collected data, the findings closely reflect the expected real-world values.

scholarly journals Type-2 Fuzzy Expert System Approach for Decision-Making of Financial Assets and Investing under Different Uncertainty

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Zuzana Janková ◽  
Petr Dostál
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Stock Market ◽  
Fuzzy Sets ◽  
Financial Time Series ◽  
Fuzzy Model ◽  
Exchange Traded Funds ◽  
International Equity Markets

Extensive research results of stock market time series using classical fuzzy sets (type-1) are available in the literature. However, type-1 fuzzy sets cannot fully capture the uncertainty associated with stock market developments due to their limited descriptiveness. This paper fills a scientific gap and focuses on type-2 fuzzy logic applied to stock markets. Type-2 fuzzy sets may include additional uncertainty resulting from unclear, uncertain, or inaccurate financial data through which model inputs are calculated. Here we propose four methods based on type-2 fuzzy logic, which differ in the level of uncertainty contained in fuzzy sets and compared with the type-1 fuzzy model. The case study aims to create a model to support investment decisions in Exchange-Traded Funds (ETFs) listed on international equity markets. The created models of type-2 fuzzy logic are compared with the classic type-1 fuzzy logic model. Based on the results of the comparison, it can be said that type-2 fuzzy logic with dual fuzzy sets is able to better describe data from financial time series and provides more accurate outputs. The results reflect the capability and effectiveness of the approach proposed in this document. However, the performance of type-2 fuzzy logic models decreases with the inclusion of increasing uncertainty in fuzzy sets. For further research, it would be appropriate to examine the different levels of uncertainty in the input parameters themselves and monitor the performance of such a modified model.

scholarly journals Investment Decision Support Based on Interval Type-2 Fuzzy Expert System

2021 ◽  
Vol 32 (2) ◽  
pp. 118-129
Author(s):  
Zuzana Janková ◽  
Dipak Kumar Jana ◽  
Petr Dostál
Keyword(s):  
Fuzzy Logic ◽  
Financial Markets ◽  
Degrees Of Freedom ◽  
Chaotic Behavior ◽  
Investment Decision ◽  
Fuzzy Model ◽  
Financial Model ◽  
Interval Type

The decision-making process on investing in financial markets is a very complex and difficult task, mainly due to the chaotic behavior and high uncertainty in the development of the prices of investment instruments. For this reason, financial markets are increasingly using means of artificial intelligence, namely fuzzy logic, which is able to capture the nonlinear behavior.Fuzzy logic provides a way to draw definitive conclusions from vague, ambiguous, or inaccurate information.However, there are some drawbacks associated with type-1 fuzzy logic, so the type-2 fuzzy logic comes forward, which can work with greater uncertainty. Type-2 fuzzy logic works with a new third dimension fuzzy set that provides additional degrees of freedom and allows to model and process numerical and linguistic uncertainties directly. The paper applies type-2 fuzzy logic to the stock market with the aim to create a simple and understandable model for deciding on investing in investment instruments, which is important for investors in this area. The proposed type-2 fuzzy model uses return, risk, dividend and total expense ratio of ETF as input variables. The created system is able to generate aggregated models from a certain number of language rules, which allows the investor to understand the created financial model. Using type-2 fuzzy logic can lead to more realistic and accurate results than type-1 fuzzy logic.

scholarly journals Eliminating Knowledge Bottlenecks Using Fuzzy Logic

Organizacija ◽  
2013 ◽  
Vol 46 (5) ◽  
pp. 206-213
Author(s):  
Maja Zajec ◽  
Davorin Kofjač ◽  
Matjaž Roblek
Keyword(s):  
Fuzzy Logic ◽  
Decision Model ◽  
Critical Path ◽  
Fuzzy Model ◽  
Knowledge Structure ◽  
Work Role ◽  
Heat Map ◽  
Actual Knowledge ◽  
Starting Point ◽  
The Right

Abstract In the formation of new processes, innovations generated by people possessing the right knowledge and talent play a crucial role. Our starting point was the fact that every new change in processes can alter the knowledge structure of a work position or work role. This means that a person can become a knowledge bottleneck in the process. If this person is found on a critical path, the process cannot produce the output in a desired form, extent or quality, unless the bottleneck is removed. For this reason, we developed a decision model founded on fuzzy logic. The result of the fuzzy model is knowledge estimation based on deviation between the required and actual knowledge. For faster decision making, we made a presentation of allocated people on desired roles using the heat map technique. Therefore, the employers make better decisions on actual knowledge allocation, acquiring missing knowledge, or defining knowledge required for the future, which makes them more competitive.

scholarly journals The Vietnamese stock and bond markets in 2020

2021 ◽  
Author(s):  
AISDL
Keyword(s):  
Stock Market ◽  
Gross Domestic Product ◽  
Domestic Product ◽  
Bond Markets ◽  
Market Capitalization ◽  
Total Market

As the stock market has increased by 60% in prices from the bottom at the end of March, the total market capitalization now reached US$200 billion, equivalent to nearly 60% of the country's gross domestic product.

scholarly journals The role of pairing the RSI and the Japanese candlestick in making sure to choose the right time to sell and purchasing the stock Applied in a selected sample of companies listed in the Iraqi Stock Exchange

2019 ◽  
Vol 5 (1) ◽  
pp. 61
Author(s):  
Ammar Shihab Ahmed
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Investment Decision ◽  
Supply And Demand ◽  
Analytical Techniques ◽  
Technical Analysis ◽  
Analysis Techniques ◽  
Real Market ◽  
The Right

The issue of determining the appropriate timing for the decisions of buying and selling shares is one of the most important topics and the concern of all investors in the stock market, whether they are natural or Morality persons . This interest has been generated by many of those interested in technical analysis to invent techniques, methods and indicators for the purpose of analyzing the performance of the stock market. Maximize the chances of profit and reduce the chances of loss, and investors suffer from the problem of choosing the right time to conduct the sale or purchase of shares of different sectors and companies, and contribute technical analysis techniques in tracking the movement of the prices of those shares to indicate their direction If it is in the case of continuous rise or in the case of continuous decline, if the trend of the movement of shares in the case of continuous rise, this rise will not continue to the end must come a period of time in which prices fluctuate and change direction downward and vice versa in the case of continuous decline, Technical analysis techniques that move through the different graphics and shapes we can use and make use of in the timing of buying and selling shares. There are a lot of technical analysis techniques including Japanese candlesticks, RSI and many more, but important when we want to use We need to use at least two analytical techniques in order to avoid uncertainty in determining the real market trends and thus making the right investment decision, whether it is the sale of shares and the analysis of the mechanism of supply and demand.

MODELS FOR DESCRIBING AND SUPPORTING AUTOMATED SYSTEM SCENARIOS

2020 ◽  
pp. 18-22
Author(s):  
В.П. Хранилов ◽  
П.В. Мисевич ◽  
А.Э. Ермилов
Keyword(s):  
Fuzzy Logic ◽  
Life Cycle ◽  
Automated System ◽  
Just In Time ◽  
Success Factor ◽  
Situational Analysis ◽  
Frame Model ◽  
Information Logistics ◽  
The Right ◽  
The Mathematical Model

В статье представлены модели описания сценариев функционирования автоматизированных систем (АС). Вводится и анализируется категория "жизненный цикл сценариев АС". Наиболее важными этапами жизненного цикла сценария являются следующие: этап формирования событийного набора для формирования сценария, этап выполнения последовательности сценарных событий и этап ситуационного анализа внешней и внутренней среды события. В статье предложена математическая модель функционирования АС, которая используется для поддержки этапа выполнения последовательности сценарных событий и основана на принципе информационной логистики: каждый параметр (набор данных) находится в нужном месте в АС, "точно в срок" и в нужном формате. Для поддержки ситуационного анализа предлагается модифицированная фреймовая модель. Ситуационный анализ используется для разработки алгоритмов событий и определения следующего события в сценарии. Модифицированная фреймовая модель основана на использовании нечетких логических процедур в фреймовой сети. The paper presents models for describing the operating scenarios of automated systems. The authors introduce and analyze the category “the life cycle of automated system scenarios”. The life cycle consists of a sequence of stages. The leading success factor of any scenario is the support of the scenario during all stages of its life cycle. The most important stages of the scenario life cycle are the following: the stage of forming the event set for generating the scenario, the stage of performing the sequence of scenario events and the stage of situational analysis of the external and internal environment of the event. In the article it is proposed to use a theoretical set model in order to select an element from a set of alternatives. The elements are events for designing a scenario. The model uses fuzzy logic and is based on the process of controlling an array of parameters if variants are available. The model is used to support the stage of forming a set of events for generating the scenario. The mathematical model of automated system operation which is used to support the stage of performing the sequence of scenario events is suggested in the article. The model is based on the principle of information logistics: each parameter (a set of data) is in the right place in the automated system, ‘just-in-time’ and in the required format. A modified frame model is proposed to support situational analysis. The situational analysis is used to operate the event algorithms and to determine the next event in the scenario. The modified frame model is based on the use of fuzzy logic procedures in a frame network.

scholarly journals The Innovation of Government Bonds in the Growth of an Emergent Capital Market

2021 ◽  
Vol 7 (1) ◽  
pp. 103
Author(s):  
Cordelia Onyinyechi Omodero ◽  
Philip Olasupo Alege
Keyword(s):  
Capital Market ◽  
Research Work ◽  
Government Bonds ◽  
Market Capitalization ◽  
Market Growth ◽  
Explanatory Variables ◽  
The Government ◽  
The Impact ◽  
Total Market ◽  
The Capital Market

The growth of an emerging capital market is necessary and requires all available resources and inputs from various sources to realize this objective. Several debates on government bonds’ contribution to Nigeria’s capital market developmental growth have ensued but have not triggered comprehensive studies in this area. The present research work seeks to close the breach by probing the impact of government bonds on developing the capital market in Nigeria from 2003–2019. We employ total market capitalization as the response variable to proxy the capital market, while various government bonds serve as the independent variables. The inflation rate moderates the predictor components. The research uses multiple regression technique to assess the explanatory variables’ impact on the total market capitalization. At the same time, diagnostic tests help guarantee the normality of the regression model’s data distribution and appropriateness. The findings reveal that the Federal Government of Nigeria’s (FGN) bond is statistically significant and positive in influencing Nigeria’s capital market growth. The other predictor variables are not found significant in this study. The study suggests that the Government should improve on the government bonds’ coupon, while still upholding the none default norm in paying interest and refunding principal to investors when due.

scholarly journals In vivo exploration of synaptic projections in frontotemporal dementia

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Salmon ◽  
Mohamed Ali Bahri ◽  
Alain Plenevaux ◽  
Guillaume Becker ◽  
Alain Seret ◽  
...  
Keyword(s):  
Frontotemporal Dementia ◽  
Input Function ◽  
Parahippocampal Gyrus ◽  
Exploratory Research ◽  
Social Brain ◽  
Synaptic Density ◽  
Clinical Disorder ◽  
Significant Difference ◽  
The Right

AbstractThe purpose of this exploratory research is to provide data on synaptopathy in the behavioral variant of frontotemporal dementia (bvFTD). Twelve patients with probable bvFTD were compared to 12 control participants and 12 patients with Alzheimer’s disease (AD). Loss of synaptic projections was assessed with [18F]UCBH-PET. Total distribution volume was obtained with Logan method using carotid artery derived input function. Neuroimages were analyzed with SPM12. Verbal fluency, episodic memory and awareness of cognitive impairment were equally impaired in patients groups. Compared to controls, [18F]UCBH uptake tended to decrease in the right anterior parahippocampal gyrus of bvFTD patients. Loss of synaptic projections was observed in the right hippocampus of AD participants, but there was no significant difference in [18F]UCBH brain uptake between patients groups. Anosognosia for clinical disorder was correlated with synaptic density in the caudate nucleus and the anteromedial prefrontal cortex. This study suggests that synaptopathy in bvFTD targets the temporal social brain and self-referential processes.

An empirical study on big data stock volatility forecasting algorithm based on multivariate hybrid criterion fuzzy model

2021 ◽  
pp. 002072092098399
Author(s):  
Zhang Xiao-Wen ◽  
Zeng Min
Keyword(s):  
Big Data ◽  
Stock Market ◽  
Fuzzy Model ◽  
Reference Value ◽  
Developed Countries ◽  
Theoretical Research ◽  
Prediction Algorithm ◽  
Real Economy ◽  
Stock Volatility ◽  
The Us

The fluctuation of the stock market has always been a matter of great concern to investors. People always hope to judge the trend of the stock market through the trend of the K line, so as to obtain the price difference through trading, Therefore, it is a theoretical research concerned by the academic circles to carry out empirical research through big data stock volatility prediction algorithm, so as to establish a model to predict the trend of the stock market. After decades of development, China's stock market has gradually matured in continuous exploration. However, compared with the stock market in developed countries, there are still imperfections. For example, the market value of China's stock market does not improve well with economic growth. Year-on-year growth and the development of the real economy. By studying the historical data from 2002 to 2017, we use the Multivariate Mixed Criterion Fuzzy Model (MMCFM) to predict the price changes in the stock market, and obtain the market in China through error statistical analysis. (SSE) is more unstable than the US stock market. Therefore, Multivariate Mixing Criterion (MMC) can be used as a reference indicator to visually measure market maturity. In this paper, we establish a multivariate mixed criteria fuzzy model, and use big data to predict the stock volatility. The algorithm verifies the reliability and accuracy of the model, which has a good reference value for investors.

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