<![CDATA[This study forecasts the monthly closing values of the NASDAQ Composite Index for 2015-2025 using the ARIMA model and examines its implications for reading technology sector trends. The research is based on NASDAQ’s role as an index that widely represents technology-related companies and is contextually associated with digitalization, interest rate changes, the COVID-19 pandemic, and artificial intelligence developments. This study applies a quantitative univariate time series approach using the Box-Jenkins procedure, including log transformation, Augmented Dickey-Fuller (ADF) stationarity testing, ACF-PACF identification, AIC/BIC-based model selection, parameter estimation, residual diagnostics, and accuracy evaluation using MAE, MSE, RMSE, and MAPE. The results show that ARIMA(0,1,0) with drift follows the general direction of NASDAQ Composite movements with a MAPE of 12.21%, indicating good forecasting accuracy. However, the model tends to underestimate sharp upward movements and is better interpreted as a random walk with weak positive drift. Contextually, NASDAQ Composite movements can be read as part of technology and digital economy dynamics. Thus, ARIMA offers a simple, transparent, and replicable framework, while sectoral interpretations remain contextual and non-causal.]]>
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