Бидний тухай
Багш ажилтан
This study employs a bibliometric approach to map the intellectual structure, thematic landscape, and geographical distribution of research on financial contagion in emerging markets. It examines 824 peer-reviewed journal articles indexed in Scopus between January 2010 and March 2025, identifying leading countries, influential authors, dominant keywords, methodological patterns, and evolving research trends. The dataset was processed using the Bibliometrix package in R through Biblioshiny, together with VOSviewer for keyword co-occurrence analysis and CiteSpace for burst detection. Positioned within a broader historical frame from 1980 to 2026, annual scientific production shows that the 1997–98 Asian Financial Crisis marked the field’s emergence, the 2007–09 Global Financial Crisis drove its first major expansion, and the COVID-19 pandemic produced its strongest acceleration, with output reaching a record 142 articles in 2024. The findings also reveal a broader geographical base of knowledge production, with growing contributions from China, India, Turkey, Brazil, and South Africa, even as the United States and the United Kingdom remain central. Overall, the study highlights a shift toward network-based, cross-asset, and shock-oriented approaches, while showing that research intensity reflects topical relevance more than national income globally.
Quantitative syntheses of the financial contagion literature are scarce, with frontier markets at the edge of the emerging-market category particularly under-represented. We meta-analyse 312 effect sizes from 87 studies (2002–2024) spanning 26 economies. A three-level random-effects model with cluster-robust variance estimation and Hartung–Knapp–Sidik–Jonkman adjustment returns a pooled standardised contagion coefficient of 0.187 (95% CI: 0.156–0.218; I-squared = 76.4%; tau-squared = 0.022). Multilevel meta-regression attributes 28% of between-study variance to methodological choice: DCC-GARCH and TVP-VAR connectednessmeasures exceed the Forbes–Rigobon adjustment by 35–45%, consistent with heteroscedasticity-induced bias. Regional moderators diverge sharply: the BRICS bloc registers 0.241, against 0.124 for Central Asia and Mongolia (k = 14), the lowest sub-sample mean. Selective-reporting diagnostics—Egger regression, trim-and-fill, PEESE, p-curve, p-uniform-star and a Vevea–Hedges selection model—indicate moderate but bounded distortion. Leave-one-out and Cook-distance diagnostics confirm that no single study drives the result. We draw three conclusions: methodological choice has first-order consequences for measured contagion; small open frontier markets exhibit attenuated direct co-movement but pronounced commodity-mediated transmission; and Central Asia and Mongolia warrant a focused research agenda calibrated to commodity-and currency-channel measurement.
This study investigates the optimal timeline for university enrollment confirmation using survival analysis, focusing on behavioral data from the National University of Mongolia (hereinafter NUM). As higher education institutions streamline operations and competition intensifies, the timing of student decisions becomes increasingly critical. Applying the Cox proportional hazards model to multi-year administrative data, we find that approximately 90% of confirmations occur within the first 600–700 minutes of the registration window. Factors such as program type, institutional affiliation, entrance scores, and regional origin significantly influence confirmation timing. These findings suggest that an 11-hour confirmation period balances logistical efficiency with student decision-making needs. The results align with theories of bounded rationality and decision overload, offering a novel empirical basis for policy reform in developing higher education systems.
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.
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.
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.
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.
Abstract Within the scope of this research, using the quantitative data of 88 quarters of Mongolian budget income and expenditure for 2020-2021, the structural effect was divided into two parts: pre-pandemic and post-pandemic, which were shown in the budget income and expenditure portfolio using the Markovitch portfolio choice model. Optimum values are obtained through programming or optimization, and how much the optimal value deviates from the original value is analyzed by the one-sigma rule. According to the results of the survey, the pandemic had a 48 percent impact on budget expenditures and 32 percent on budget revenue. Therefore, to improve budget efficiency, budget spending should be implemented effectively. In particular, policymakers should pay attention to the gradual increase in investment in the health and education sectors.
Since 2017, milk and dairy products have been declared a strategic food in Mongolia, leading to the launch of a milk production campaign and the implementation of various projects and programs. The goal of this campaign is to ensure the supply of milk and dairy products to consumers without seasonal fluctuations. In this context, it is essential to study the subjective evaluations and assessments of experts in the Mongolian dairy sector. Furthermore, there is a need to produce products that comprehensively incorporate the characteristics of processing, price, taste, proper production practices, standards, and hygiene to meet consumer needs.
