Methods for Minimizing Risks in Investments in High-Tech Projects

Maria Azatyan

Citation: Maria Azatyan, "Methods for Minimizing Risks in Investments in High-Tech Projects", Universal Library of Business and Economics, Volume 02, Issue 03.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This article is devoted to the analysis of contemporary methods for minimizing risks when investing in high-technology projects. Its relevance stems from the growing uncertainty of innovation markets and the high sensitivity of capital to changes in both technological and institutional environments. The paper describes and systematizes approaches to managing investment risks—ranging from flexible structures such as real options and modular architectures to the application of stochastic models and patent analysis. Sources reflecting a diversity of conceptual frameworks and empirical findings were reviewed. Special attention is given to the mechanism of adaptive planning and the assessment of project-instability factors. The study aims to develop analytically grounded principles for crafting resilient investment strategies under conditions of uncertainty. To this end, comparative analysis, source-systematization methods, and content modeling were employed. The conclusions present a typology of effective solutions. This work will benefit the academic community, investors, and project managers in innovative sectors. Practical recommendations for integrating risk analytics into the project lifecycle are provided. The importance of adaptive solutions—capable of accounting for phase-specific characteristics and the real-time dynamics of the technological environment—is emphasized.


Keywords: Investment Risks; High-Technology Projects; Stochastic Modeling; Flexibility; Real Options; Patent Analysis; Project Resilience; Risk Management; Adaptation; Monte Carlo.

Download doi https://doi.org/10.70315/uloap.ulbec.2025.0203006