dc.contributor.author | OLFER, Ivan | |
dc.date.accessioned | 2022-12-22T12:21:50Z | |
dc.date.available | 2022-12-22T12:21:50Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | OLFER, Ivan. Vectors of exact forecast in the study of behavioral finance. In: Competitiveness and sustainable development : 4th economic intern. conf., 3-4 Nov. 2022, Chişinău, Republica Moldova: conf. proc., Chişinău, 2022, pp. 243-246. ISBN 978-9975-45-872-6. | en_US |
dc.identifier.isbn | 978-9975-45-872-6 | |
dc.identifier.uri | https://doi.org/10.52326/csd2022.44 | |
dc.identifier.uri | http://repository.utm.md/handle/5014/21814 | |
dc.description.abstract | Strongly determined that for true planning and right decision in the economic markets circle the standard (classical) economic theory is not enough. Not infrequently economic forecasting according to classical theory, in the circle of markets, founds, enterprises relatively to results is not profitable and expected. For right prognosis and decision making is necessary to use behavioral theory. Some theory and methods for scientific research may be similar, and representative for all investigations. There are numerous similarities and differences in these theories according to institutions, methods and theory aspects. The behavioral theory refers to psychological and human behavioral algorithms, some biases, emotional filters, heuristic, farming and emotional concepts. Analyzing these factors open the way to more accurate and exact analysis. Behavioral finance can be analyzed to understand different outcomes across a variety of sectors and industries when we can`t fully understand it with standard theory. During the time appears a lot of schools of thoughts about human behavior, wishes and irrationality created with emotions, emphasized changing irrationality according to age, social status, gender, even wealth and level of educations. Recognized that these factors are interrelated, and this relating create biases, that could use like axioms for behavior understanding, and create representative sample for different environments (markets, companies etc.), and countries (low or high developed) where presented low level of shadow economy or even extremely high, all justified with number of variables. Methods. Classification, Analytic-Synthetic, Historical-Logical, Modeling, Systematization. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Technical University of Moldova | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | behavioral finance | en_US |
dc.subject | economic forecasting | en_US |
dc.subject | behavioral theory | en_US |
dc.subject | decision making | en_US |
dc.title | Vectors of exact forecast in the study of behavioral finance | en_US |
dc.type | Article | en_US |
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