Short-Term Forecasting of Selected Uzbek NonBank Joint-Stock Company Stock Prices Using Random Walk, ARIMA and VAR(4) Models (American Economist: Journal of Economics Finance and Global Policy, 2026)
Forecasting equity prices in thinly traded frontier markets remains a difficult exercise because liquidity is uneven, news flow is sparse, and the cross-sectional links between issuers are weak. Against this background, this study evaluates the short-term predictive performance of three forecasting specifications-the Random Walk benchmark, a univariate ARIMA, and a fourth-order Vector Autoregression VAR(4)-for four non-bank joint-stock companies listed in Uzbekistan: QZSM, UZTL, URTS and CBSK. Daily closing prices over the period 9 September 2022 to 17 April 2026 (883 price observations and 882 log-return observations) are used jointly with the UCI composite index as a market benchmark. Predictive accuracy at a 63 trading-day horizon is judged using root mean squared error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE), with the lowest MAPE serving as the primary selection criterion
Keywords: Uzbek stock market; non-bank joint-stock companies; Random Walk