The development of stock markets is pivotal for economic growth, particularly through the mobilization of idle resources into productive investments. Despite recent reforms to enhance Uzbekistan’s capital market, public engagement remains limited. This study examines the behavioral determinants of stock market investment intention and participation among university students, employing the Theory of Planned Behavior (TPB) and Partial Least Squares Structural Equation Modeling (PLS-SEM). The model investigates the influence of digital literacy, financial literacy, social interaction, herding behavior, overconfidence bias, risk tolerance, and financial well-being on investment intention and behavior. A survey of 369 university students was conducted to assess the proposed relationships. The results reveal that risk tolerance, overconfidence bias, and herding behavior significantly and positively affect investment intention, while digital literacy demonstrates a notable negative effect, suggesting caution in assuming technology readiness automatically translates to investment readiness. Investment intention, in turn, strongly predicts actual participation and mediates several of these effects. Conversely, financial literacy, financial well-being, and social interaction showed no significant direct or mediating influence. Additionally, differences according to gender and academic background were observed in how intention translates into behavior. The findings underscore the need for integrated financial and behavioral education to enhance market participation and contribute to policy discourse on youth financial engagement in emerging economies.

This study presents a self-contained derivation and solution of the Black and Scholes partial differential equation (PDE), replacing the standard Wiener process with a smoothed Wiener process, which is a differentiable stochastic process constructed via normal kernel smoothing. By presenting a self-contained, Itô-free derivation, this study bridges the gap between heuristic financial reasoning and rigorous mathematics, bringing forth fresh insights into one of the most influential models in quantitative finance. The smoothed Wiener process does not merely simplify the technical machinery but further reaffirms the robustness of the Black and Scholes framework under alternative mathematical formulations. This approach is particularly valuable for instructors, apprentices, and practitioners who may seek a deeper understanding of derivative pricing without relying on the full machinery of stochastic calculus. The derivation underscores the universality of the Black and Scholes PDE, irrespective of the specific stochastic process adopted, under the condition that the essential properties of stochasticity, volatility, and of no arbitrage may be preserved.

The Transactional Asset Pricing Approach (TAPA) is able to handle asset valuations on a portfolio level of size constrained markets against the backdrop of low liquidity hindering the estimation of the variance of returns. Prompted by a numerical simulation of the TAPA algorithm, we develop stability conditions associated with the valuation convergence for any maximal positive time period and positive number of assets. We present stability conditions at the local level, both in continuous and discrete algorithmic time, and we develop them by means of log-linearisation about the steady state of its equations’ variables. We conclude on the analytical existence of stability conditions at the local level up to four assets and any positive time period. We adduce analytical applications within such a region and present a solution for a benchmark calibration of the steady state parameters given two time periods and a single asset.

Uzbekistan has rapidly expanded solar photovoltaic (PV) capacity as part of its transition toward a low-carbon energy system, supported by guaranteed purchase tariffs and an evolving regulatory framework. This paper evaluates the economic feasibility of solar PV investments in Uzbekistan through a combined ex post and ex ante analysis, focusing on both commercial-scale rooftop installations and a proposed large utility-scale floating photovoltaic (FPV) project. Ex post performance data from four commercial rooftop PV systems in Tashkent (20–304 kW) over the period 2024–2025 are analyzed using lifecycle investment appraisal metrics, including the Equivalent Uniform Annual Cost (EUAC)/LCOE framework, Net Present Value (NPV), and Internal Rate of Return (IRR), to benchmark real operating outcomes against modeled expectations. These results are subsequently used to calibrate ex ante simulations for a 491 MW FPV installation planned on the Sardoba reservoir, assessed using RETScreen Expert and a bespoke three-statement financial model incorporating detailed tax, financing, and operational assumptions. The findings indicate that commercial-scale rooftop PV projects in Tashkent operate close to the financial break-even point, with EUAC-based levelized costs of energy broadly aligned with current guaranteed purchase prices for PV electricity, resulting in near-zero NPVs. In contrast, the large-scale Sardoba FPV project demonstrates moderate but positive financial viability, with nominal IRRs of approximately 14–16% and payback periods under ten years at the prevailing tariff levels. Importantly, the monetized value of environmental externalities—primarily avoided CO₂ emissions—amounts to roughly from one quarter to a third of initial capital expenditure, materially enhancing the project’s overall economic value. The results suggest that while large-scale solar projects in Uzbekistan generate limited private financial rents, their societal benefits justify continued policy support, stopping short of additional direct subsidy disbursements but conducive to lower cost-of-capital measures.