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Багш ажилтан
Актуальность исследования определяется тем, что в Монголии индивидуальное инвестирование находится на стадии формирования, и участие населения в фондовом рынке остаётся низким. Недостаточная изученность факторов индивидуального инвестиционного поведения осложняет разработку мер по расширению финансовой инклюзивности. Анализ социально-демографических и поведенческих характеристик позволяет выявить ключевые стимулы и барьеры, влияющие на инвестиционные решения, и способствует укреплению долгосрочной финансовой культуры. Цель исследования состоит в комплексной оценке влияния социально-демографических и поведенческих факторов на вероятность участия в фондовом рынке и величину инвестируемых средств в условиях Монголии, а также в выявлении механизмов, формирующих различия в инвестиционном поведении. Задачи исследования включают: определение влияния пола, возраста, размеров домохозяйства и дохода на вероятность приобретения акций; оценку воздействия инвестиционного горизонта, образования, опыта и специализированного обучения на объём инвестиций; сопоставление различных моделей для выявления устойчивых детерминант. Методология. Методология основана на анализе данных 868 респондентов, собранных за шестнадцать дней, из которых 519 являются активными инвесторами. Применяются пробит-модель для оценки участия и модель Тобита для анализа объёмов инвестиций. Результаты. Получено, что пол, возраст, размер домохозяйства и доход статистически значимо влияют на участие, тогда как доход, пол, опыт, образование, обучение и инвестиционный горизонт существенно увеличивают объём инвестиций. Выводы. Результаты подчёркивают необходимость расширения финансового образования, практико-ориентированной подготовки и стимулирования долгосрочного планирования для увеличения вовлечённости населения и укрепления инвестиционной среды Монголии.
This study employed a PLS-SEM model to examine the impact of behavioral biases on investment decision-making in the Mongolian stock market using survey data collected from 529 investors, of which 385 valid samples were retained after quality screening. The findings reveal that cognitive, emotional, and social behavioral biases have statistically significant effects on investors’ decision-making, while investor sentiment, financial literacy, and risk tolerance partially mediate these relationships. The study further confirms that information asymmetry and differences in financial literacy within the Mongolian stock market intensify behavioral distortions, leading investors toward less rational investment decisions.
This study explores how cognitive biases shape investment decision-making by explicitly examining the mediating roles of financial literacy and investor sentiment within an emerging market environment. Drawing on primary survey data from 529 individual investors in Mongolia collected in 2025, the analysis employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate both direct and indirect behavioral relationships. The findings indicate that cognitive biases do not influence investment decisions in a uniform manner. Anchoring bias and availability bias show no significant direct or mediated effects through financial literacy or investor sentiment, suggesting that these heuristics function mainly as context-dependent judgmental shortcuts. In contrast, mental accounting and representativeness bias exert statistically significant indirect effects on investment decision-making through both cognitive and affective channels. Financial literacy and investor sentiment emerge as key determinants of decision quality, highlighting the importance of knowledge-based capacity and psychological factors in shaping investor behavior. By modeling behavioral transmission mechanisms rather than focusing solely on bias existence, the study offers a more nuanced explanation of how investor rationality is constrained and reinforced. The results provide novel empirical evidence from Mongolia and contribute to behavioral finance research by clarifying the conditions under which cognitive biases become decision-relevant in emerging financial markets.
This study examines the impact of behavioral factors on stock prices in the Mongolian Stock Exchange using empirical models based on behavioral finance theory. Monthly data from 2019 to 2025 were analyzed using CSAD, CSSD, and AR(1) GLS regression models. The results indicate that herding behaviors and loss aversion bias significantly reduce price volatility under certain market conditions. Conversely, overconfidence bias was found to increase volatility during bullish markets. Sectoral differences in behavioral patterns were evident, with stronger effects observed in food, finance, and light industry sectors, highlighting the theoretical and practical importance of integrating behavioral factors into investment decisions and risk management.
The study investigates investor sentiment in Mongolia by integrating market-based indicators with survey-based investor behavior measures using Principal Component Analysis (PCA). Market data-including abnormal trading activity, search intensity, TOP20 index dynamics, and return-based variables-reveal two core behavioral dimensions: a dominant market performance-driven optimism factor and a secondary attention-driven speculative factor. These components explain 68.7% of overall variance, enabling the construction of a robust market-based sentiment index. Results show that nearly 85% of monthly sentiment scores fall below the neutral benchmark, indicating persistent risk aversion and a broadly cautious market environment throughout the observation period. Survey-based PCA results, derived from 480 respondents, present a contrasting pattern. The first component reflects broader optimism associated with expectations of earnings growth, currency movements, interest rate changes, and stock index performance. The average sentiment score of 62.47 indicates that over half of participants hold an optimistic outlook toward the market's long-term trajectory. This divergence - market-level pessimism versus individual-level optimism - points to a behavioral segmentation shaped by liquidity constraints, information asymmetry, and forward-looking expectations. The combined PCA framework provides a meaningful behavioral metric for monitoring shifts in investor confidence and offers valuable insights for policy design and financial market development in frontier economies.
This study analyzes socio‑demographic and experiential determinants of stock market participation and investment intensity in Mongolia. A 16‑day survey resulted 868 responses, including 519 active participants. Probit estimation shows that gender, age, household size, and income significantly affect the decision to purchase stocks. Tobit estimation reveals that gender, income, investment horizon, education, experience, and training positively influence the amount invested, with experience and training being the strongest predictors. Comparative results highlight gender and income as consistent determinants across both models. Findings suggest that targeted education, training, and long‑term planning can enhance participation and investment levels.
This study aims to identify and explain, both theoretically and empirically, how financial influencers’ information disseminated through social media platforms affects the stock prices of commercial banks listed on the Mongolian Stock Exchange. By integrating Price Theory, Information Theory, Behavioral Finance Theory, and Decision Theory, the research constructs a multidimensional analytical framework to interpret investor behavior and market reactions to influencer-driven information. Empirically, a dataset of 284 influencer posts published between 2022 and 2025 was compiled, of which 177 observations met the criteria for time consistency, data reliability, and analytical relevance. Using Bayesian Conditional Probability, Multivariate OLS Regression, the EGARCH(1,1) model, and Event Study Analysis, the research quantitatively evaluates the short-term effects of influencer communications on bank stock returns and volatility. The Bayesian analysis reveals heterogeneous conditional probabilities of positive stock returns, ranging between 26.9% and 62.5%, depending on both the platform and the specific bank. Results from OLS and volatility analyses indicate that influencer activity does not exert a uniform or persistent impact across all banks; rather, certain institutions exhibit statistically significant sensitivities in return fluctuations and volatility clustering following influencer-related events. The Event Study confirms that these effects are short-lived and asymmetric, implying that the influence of financial influencers operates through context-specific, lagged, and conditional transmission mechanisms. In summary, while financial influencers have begun to form an emergent layer of informational and behavioral influence within Mongolia’s capital market, their impact on stock prices remains unstable, heterogeneous, and relatively moderate. As information credibility, public trust, and investor literacy improve, influencer-generated financial communication may evolve into a more structured and stabilizing informational force, contributing to greater transparency and efficiency in the Mongolian capital market.
The aim of this study is to examine and compare internationally utilized methodologies for calculating the Investor Sentiment Index and to develop a model that corresponds to the characteristics of the capital market in Mongolia. In doing so, indices commonly applied in global practice were selected according to representative criteria and analyzed using both quantitative and qualitative research methods. A mixed-methods approach was employed, incorporating data source evaluation, sampling procedures, and statistical hypothesis testing. Based on the empirical analysis, an Investor Sentiment Index appropriate for Mongolia was constructed by integrating primary survey data from domestic stock market investors with secondary quantitative indicators of the Mongolian capital market. Quantifying the influence of investors’ behavioral factors during the decision-making process holds both theoretical and practical significance, particularly for improving the capacity to forecast market trends in the context of Mongolia.
Abstract: the research work was made with the aim of analyzing and identifying the structure of the mortgage loan, its average interest rate, terms, growth or decline and any demand or needs of mortgage loan for energy efficient apartments and its disbursement, opportunites to have such loan, any challenges. Within the scope of the research work, sustainable development goals, theory of the mortgage loans and current situation were deeply studied. Bank report and sustainable development reports were analyzed. The result of the research work was compared against the theory and the study of the current situation. Therefore, advantages of increasing the energy efficient mortgage loans were studied too.
Энэхүү судалгааны зорилго нь Монгол Улсын хөрөнгийн зах зээл дэх хөрөнгө оруулагчдын хэт итгэлийн гажуудлыг шинжлэх бөгөөд судалгаагаар Вектор авторегрессийн (VAR) загвар ашиглан хэт итгэлийн гажуудлын үр нөлөө болон түүний үргэлжлэх хугацааг шинжлэхдээ зах зээлийн өгөөж, арилжааны хэмжээний хоорондын харилцаа, хэлбэлзлийн үзүүлэлтүүдийг ашигласан. Судалгааны үр дүнгээс харахад Монголын хөрөнгийн зах зээлд тооцдог ТОП-20 индексийн хүрээний хэт итгэлийн гажуудал тодорхой хэмжээгээр оршиж байгааг тогтоосон. Тухайлбал, хөрөнгө оруулагчид зах зээлийн өгөөжийн богино хугацааны өсөлтийг эерэг дохио гэж хүлээн авч, арилжааны идэвхээ нэмэгдүүлдэг боловч энэ нь эцэстээ тогтворгүй байдалд хүргэдэг. Судалгаагаар энэхүү нөлөө нь богино хугацаанд (ойролцоогоор 10 хоног) үргэлжилж, улмаар тогтворжиж байгааг харуулсан. Энэхүү судалгааны үр дүнгээр хөрөнгө оруулагчдын хэт итгэлийн гажуудлыг багасгаж, зах зээлийн үр ашгийг нэмэгдүүлэхэд судалгааны өгөгдөл, үр дүнг ашиглах боломжтой гэж үзэж байна.
Behavioral finance is a subfield of finance that integrates insights from psychology and economics to understand how human emotions, cognitive biases, and social factors influence financial decision-making. Unlike traditional finance, which assumes that investors are rational and markets are efficient, behavioral finance recognizes that investors often make irrational decisions based on psychological factors, leading to market inefficiencies. We have researched the development of Behavioral Finance over the last half century, and have achieved results in areas such as Recognition of Behavioral Biases, Integration into Financial Markets, Empirical Research & Applications, Technological Integration and Data Analysis, Globalization and Cross-Cultural Studies Behavioral finance has shifted from a niche field questioning classical models to a central discipline in understanding financial markets and decisions. The integration of psychology into economics has challenged the notion of rational markets, emphasizing the importance of human behavior, emotions, and biases. With advancements in technology and a growing focus on global and sustainable markets, the future of behavioral finance is poised for continued growth and broader application.
Олон улсад, ялангуяа хөгжиж буй улсад гарааны компани ба гарааны бизнес өрхлэгчдийг дэмжих эрх зүйн тохиромжтой орёин бүрдүүлэх нь чухал асуудал хэвээр байна. Хөгжиж буй орны хувьд Монгол улс гарааны санхүүжилтэд ээлтэй орчин бүрдүүлэхэд чиглэсэн орчин үеийн эрх зүйн чиг хандлагыг нэвтрүүлэх шаардлагатай. Санхүүжилт авах боломж хязгаарлагдмал байдаг нь гарааны бизнесийн өсөлтөд учирдаг гол маадын нэг болдог. Энэ ажлын зорилго нь Монгол улсын гарааны санхүүжилтийн эрх зүйн орчин, бодлоготой холбоотой тулгамдсан асуудлыг тодорхойлохын тулд холбогдох хууль, тогтоомж, бодлогын баримт бичгүүдийг судалж, грааны бизнест тулгамдсан санхүүжилтийн асуудлыг судлахад чиглэгдсэн. Мөн дотоодын нөхцөл болон сонгон судалсан зарим улс орнуудын байдлыг харьцуулан дүгнэж, шилдэг туршлагыг нэвтрүүлэх, гарааны санхүүжилтийн эрх зүйн зохицуулалтад өөрчлөлт оруулах санал дэвшүүлсэн.
This study aimed to determine the impact of financial literacy on financial behavior among teachers of secondary and high schools. Financial behavior in this study was explored as saving behavior, shopping behavior, short-term and high planning and long-term planning. Data were from collected from 3437 participants who were approached conveniently. Data were analysed using smart PLS. As a result, financial literacy had a significant positive impact on financial behavior in terms of saving behavior, short-term planning and long-term planning.
Having appropriate regulation and policies for supporting startups and SMEs is a key priority for both developed and developing countries. As a developing country, Mongolia needs to adapt emerging rules to create friendly environment for startup financing. One of the main barriers to startup growth is a restricted access to finance. The focus of this study is to address issues related to startup financing regulation and policy in Mongolia. In order to identify possible challenges in the financing regulation, the study explores financial challenges that startups face, and how regulation and policy designed for startups. We discuss key findings and conclude by suggesting to adopt best practices from selected countries and change the startup financing regulations.
