Decision Support System Based on Fuzzy Logic for Assessment of Expected Corporate Income Performance

2021 ◽  
pp. 2150009
Author(s):  
Arthur Yosef ◽  
Eli Shnaider ◽  
Rimona Palas ◽  
Amos Baranes
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Operating Income ◽  
Explanatory Variables ◽  
Section Model ◽  
Evaluation Mechanism ◽  
One Year ◽  
High Degree ◽  
Decision Support Method ◽  
Very High

This study presents a decision-support method to estimate the next year performance of corporate Operating Income Margin (OIM). It is based on a unique combination of cross-section model and the rules-based evaluation mechanism. The estimate is done in terms of broad categories, and not precise numerical values. The model is constructed as follows: its dependent variable (OIM) is one year ahead vs. the corresponding explanatory variables. This structure of the model allows us to view explanatory variables as reflecting financial potential of corporations. The evaluation component consists of a set of rules designed to identify the companies whose “potential” clearly points to an opportunity to invest. For the method presented here to succeed, it is necessary to utilize a highly reliable modeling method, even if it is “Fuzzy”. We apply Soft Regression (SR), which is a Soft Computing modeling tool based on Fuzzy Logic, and utilize all available proxy variables by creating intervals of values. Advantages of utilizing SR, and the intervals’-based modeling are extensively discussed. Modeling results for five consecutive years are consistent and stable, thus indicating high degree of reliability. Testing indicates very high success rate for the stock market related domain, the lowest being 87.9%.

Identifying financial ratios associated with companies’ performance using fuzzy logic tools

2021 ◽  
Vol 40 (1) ◽  
pp. 117-129
Author(s):  
Amos Baranes ◽  
Rimona Palas ◽  
Eli Shnaider ◽  
Arthur Yosef
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Manufacturing Industry ◽  
Detailed Comparison ◽  
Financial Ratios ◽  
Modeling Tool ◽  
Operating Income ◽  
Publicly Traded Companies ◽  
Comparison Of The Results ◽  
High Degree

This study introduces computerized model for evaluation of corporate performance for companies traded in the main world stock markets. The main contribution of this study is to utilize a “Soft Regression” modeling tool, which is a soft computing tool based on fuzzy logic in financial statement analysis. Specifically, the tool is used to identify the most important financial ratios explaining the performance (as reflected by Operating Income Margin) of publicly traded companies, belonging to the manufacturing industries 2000–3999. We used data extracted from the XBRL database for years 2012 to 2016. The main results and conclusions of the study are: 1. The study identified relevant financial ratios for the manufacturing industry. It also revealed the relative importance of the various categories of financial ratios. 2. Detailed comparison of the results for 2012 and for 2016 indicated high degree of consistency and stability over time. 3. Not all financial ratios are equally relevant for all industries. 4. Proxy variables belonging to the same category of financial ratios are interchangeable in our model. It does not matter, which of the ratios belonging to the same category are used, the results are very similar for both, 2012 and for 2016. 5. All the resulting indicators imply that the model is highly reliable and robust. The main contribution of this study is to present a soft computing modeling tool based on fuzzy logic which is intuitive, stable and not based on restrictive assumptions.

Electron Microscopy in Molecular Biology

1967 ◽  
Vol 25 ◽  
pp. 2-3
Author(s):  
Cecil E. Hall
Keyword(s):  
Electron Microscopy ◽  
Molecular Biology ◽  
Noise Level ◽  
Molecular Structures ◽  
Material Structure ◽  
The Arts ◽  
Shadow Casting ◽  
Electron Image ◽  
High Degree ◽  
Very High

The visualization of organic macromolecules such as proteins, nucleic acids, viruses and virus components has reached its high degree of effectiveness owing to refinements and reliability of instruments and to the invention of methods for enhancing the structure of these materials within the electron image. The latter techniques have been most important because what can be seen depends upon the molecular and atomic character of the object as modified which is rarely evident in the pristine material. Structure may thus be displayed by the arts of positive and negative staining, shadow casting, replication and other techniques. Enhancement of contrast, which delineates bounds of isolated macromolecules has been effected progressively over the years as illustrated in Figs. 1, 2, 3 and 4 by these methods. We now look to the future wondering what other visions are waiting to be seen. The instrument designers will need to exact from the arts of fabrication the performance that theory has prescribed as well as methods for phase and interference contrast with explorations of the potentialities of very high and very low voltages. Chemistry must play an increasingly important part in future progress by providing specific stain molecules of high visibility, substrates of vanishing “noise” level and means for preservation of molecular structures that usually exist in a solvated condition.

A Low-Noise, High-Gain Quasi-Millimeter-Wave Receiver MMIC with a Very High Degree of Integration Using 3D-MMIC Technology

2011 ◽  
Vol E94-C (10) ◽  
pp. 1548-1556 ◽  
Author(s):  
Takana KAHO ◽  
Yo YAMAGUCHI ◽  
Kazuhiro UEHARA ◽  
Kiyomichi ARAKI
Keyword(s):  
Millimeter Wave ◽  
High Gain ◽  
Low Noise ◽  
High Degree ◽  
Very High ◽  
Millimeter Wave Receiver

Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)

2016 ◽  
Vol 7 (1) ◽  
pp. 12-18
Author(s):  
Joko Haryanto ◽  
Seng Hansun
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Application ◽  
Prospective Students ◽  
Fuzzy Logic Method ◽  
Index Terms ◽  
Selection Of

This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy. Index Terms—fuzzy logic, decision support system, UMN, selection of major

scholarly journals A Compensatory Fuzzy Logic Model in Technical Trading

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 36
Author(s):  
Norma P. Rodríguez-Cándido ◽  
Rafael A. Espin-Andrade ◽  
Efrain Solares ◽  
Witold Pedrycz
Keyword(s):  
Fuzzy Logic ◽  
Technical Analysis ◽  
Graphical Analysis ◽  
Logic Model ◽  
Financial Asset ◽  
Financial Assets ◽  
Novel Approach ◽  
Subjective Assessments ◽  
Efficient Prediction ◽  
High Degree

This work presents a novel approach to prediction of financial asset prices. Its main contribution is the combination of compensatory fuzzy logic and the classical technical analysis to build an efficient prediction model. The interpretability properties of the model allow its users to incorporate and consider virtually any set of rules from technical analysis, in addition to the investors’ knowledge related to the actual market conditions. This knowledge can be incorporated into the model in the form of subjective assessments made by investors. Such assessments can be obtained, for example, from the graphical analysis commonly performed by traders. The effectiveness of the model was assessed through its systematic application in the stock and cryptocurrency markets. From the results, we conclude that when the model shows a high degree of recommendation, the actual financial assets show high effectiveness.

scholarly journals Multi-Locus Selection and the Structure of Variation at the white Gene of Drosophila melanogaster

Genetics ◽  
1996 ◽  
Vol 144 (2) ◽  
pp. 635-645 ◽  
Author(s):  
David A Kirby ◽  
Wolfgang Stephan
Keyword(s):  
Drosophila Melanogaster ◽  
White Gene ◽  
Transcriptional Unit ◽  
North American Population ◽  
Evolutionary Mechanisms ◽  
Locus Selection ◽  
Neutral Equilibrium ◽  
History Of ◽  
High Degree ◽  
Very High

Abstract We surveyed sequence variation and divergence for the entire 5972-bp transcriptional unit of the white gene in 15 lines of Drosophila melanogaster and one line of D. simulans. We found a very high degree of haplotypic structuring for the polymorphisms in the 3′ half of the gene, as opposed to the polymorphisms in the 5′ half. To determine the evolutionary mechanisms responsible for this pattern, we sequenced a 1612-bp segment of the white gene from an additional 33 lines of D. melanogaster from a European and a North American population. This 1612-bp segment encompasses an 834bp region of the white gene in which the polymorphisms form high frequency haplotypes that cannot be explained by a neutral equilibrium model of molecular evolution. The small number of recombinants in the 834bp region suggests epistatic selection as the cause of the haplotypic structuring, while an investigation of nucleotide diversity supports a directional selection hypothesis. A multi-locus selection model that combines features from both-hypotheses and takes the recent history of D. melanogaster into account may be the best explanation for these data.

Analysis of Single-Vehicle Crash Injury Severities in Urban River-Crossing Road Tunnels

2015 ◽  
Vol 743 ◽  
pp. 526-532 ◽  
Author(s):  
C.M. Jiang ◽  
J.J. Lu ◽  
L.J. Lu
Keyword(s):  
Heavy Vehicles ◽  
Probit Regression ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Urban Road ◽  
Road Tunnels ◽  
Negative Effect ◽  
Single Vehicle ◽  
Injury Severities ◽  
One Year

Based on the originally unprocessed data from the Official Platform of“110”Alarming Receiving Center (OP110ARC) of Shanghai Public Security Bureau (SPSB), 529 single-vehicle crashes reported during one year and a half which happened at the thirteen urban road tunnels going across the Huangpu River are used in this study. To investigate the factors affecting the crash influence severity levels, ordered probit regression is established. Several categories of factors are considered as explanatory variables in the models. The study finds that the entrance of the tunnels is the site where severe injury crashes trend to occur. Rainy and snowy days impose vehicles and motorists driving via the tunnel sections in danger. Tunnels with a low speed limit (40 km/h in this study) may be not as safe as we thought before. Two-wheel vehicles without sufficient physical protection for its drivers and heavy vehicles also show a negative effect on the operation safety of single-vehicle at these studied tunnels. Alcohol involved drivers are more likely to suffer from a severe crashes and gets badly hurt.

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