Empowering investors in the technology sector: Risk assessment for financial resilience and economic sustainability

Given the high volatility of technology-related stocks, accurate downside-risk measurement is important for investor decision-making. This study aims to evaluate and compare the ability of Value at Risk (VaR), Conditional Value at Risk (CVaR), and GARCH-based risk measurement to assess downside risk and volatility dynamics in selected U.S. technology-related stocks. Using a quantitative approach, the study analyzes daily closing prices obtained from the Refinitiv Eikon database for Adobe, Alphabet, Amazon, Apple, Intel, Meta, Microsoft, Netflix, NVIDIA, and Tesla over the period from September 28, 2004, to September 24, 2024. Historical VaR and CVaR are used to estimate downside and tail-risk exposure, while GARCH(1,1) is applied to capture time-varying volatility. The results show that measured risk increases at higher confidence levels, with Tesla, NVIDIA, and Netflix generally displaying higher downside-risk exposure than more stable firms such as Microsoft. The benchmark comparison further shows that the equal-weighted selected stocks exhibit higher volatility and more negative VaR and CVaR values than the NASDAQ Composite. CVaR provides more informative insights into tail risk because it estimates average losses beyond the VaR threshold. The findings contribute to market risk measurement literature by comparing risk estimates across individual technology-related stocks and provide practical implications for investors managing exposure to volatile equity markets.