(untitled) (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