article_16_20260511235412 1778543652 Journal System noreply@positive-science.com Journal System Positive Science - Economics 10.65957/journal.1 https://positive-science.com/journal/human_economics_B1057f9a86 05 11 2026 Nischal Shrestha Forecasting stock market behavior remains an important issue for investors, policymakers, and financial researchers, particularly in emerging markets where market volatility and informational inefficiencies may influence investment decisions. Despite growing interest in forecasting the Nepal Stock Exchange (NEPSE) index, existing studies have primarily focused on conventional ARIMAbased approaches without sufficiently incorporating rolling-window out-of-sample evaluation and benchmark comparison within the context of weak-form market efficiency. Addressing this gap, the present study examines the forecasting performance of the NEPSE daily closing index using an ARIMA/SARIMA-based time series framework and compares the selected model with a naïve random walk benchmark. The study utilized 1,157 daily observations of the NEPSE index and applied descriptive statistics, Augmented Dickey-Fuller stationarity testing, autocorrelation analysis, SARIMA model selection procedures, residual diagnostic testing, and rolling-window one-step-ahead forecasting techniques. Based on model selection criteria, seasonal structure, and diagnostic adequacy, SARIMA (3,1,0) (2,0,0) [5] was selected as the final forecasting model. The findings revealed that the SARIMA model generated slightly lower forecasting errors than the naïve benchmark during the Positive Science-Economics 05 11 2026 10.65957/article.16 https://positive-science.com/article/time_series_modeling_and_forecasting_of_nepse_inde_2a7955Db29 10.1016/j.csda.2017.11.003 Bergmeir, C., Hyndman, R. J, & K, B.. " A note on the validity of cross-validation for evaluating autoregressive time series prediction.". Computational Statistics & Data Analysis. Vol. 120, pp. 70–83. (2018) 10.1016/0304-4076(92)90064-x Bollerslev T, Chou R, Kroner K. "ARCH modeling in finance". Journal of Econometrics. Vol. 52, No. 1-2, pp. 5–59. (1992) 10.1080/0015198x.2020.1734375 Brown S. "The Efficient Market Hypothesis, the Financial Analysts Journal, and the Professional Status of Investment Management". Financial Analysts Journal. Vol. 76, No. 2. (2020) 10.2307/1912773 Engle R. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation". Econometrica. Vol. 50, No. 4, pp. 987. (1982) 10.2307/2325486 Fama E. "Efficient Capital Markets: A Review of Theory and Empirical Work". The Journal of Finance. Vol. 25, No. 2, pp. 383. (1970) 10.3126/nrber.v29i1.52530 Gaire H. "Forecasting NEPSE Index: An ARIMA and GARCH Approach". NRB Economic Review. Vol. 29, No. 1. (2017) 10.3126/jnbs.v5i1.2085 G., S.. "Volatility Analysis of Nepalese Stock Market". Journal of Nepalese Business Studies. Vol. 5, No. 1. (2009) 10.1111/j.1540-6261.1993.tb04702.x Jegadeesh N, Titman S. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency". The Journal of Finance. Vol. 48, No. 1. (1993) 10.1016/0169-2070(92)90130-2 Leitch G, Tanner E, J.. "Economic Forecast Evaluation: Profit Versus the Conventional Error Measures". International Journal of Forecasting. Vol. 8, No. 2. (1991) 10.1093/rfs/1.1.41 Lo A, Mackinlay A. "Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test". Review of Financial Studies. Vol. 1, No. 1. (1988) 10.1257/089533003321164958 B.. "The Efficient Market Hypothesis and its Critics". Positive Science -Economics Malkiel. Vol. 17, No. 1. (2003) 10.1086/294632 Mandelbrot B. "The Variation of Certain Speculative Prices". The Journal of Business. Vol. 36, No. 4, pp. 394. (1963) 10.47001/irjiet/2022.602014 Maskey A. "Predicting NEPSE Index Using ARIMA Model". International Research Journal of Innovations in Engineering and Technology. Vol. 06, No. 02. (2022) 10.3126/ljbe.v12i1.70318 Paudel S. "Predicting NEPSE Index: An ARIMA-Based Model". The Lumbini Journal of Business and Economics. Vol. 12, No. 1. (2024) 10.3126/njs.v8i1.73159 Shrestha K, Kayastha R. "Risk Behavior of Different Weekdays in NEPSE Index". Nepalese Journal of Statistics. Vol. 8. (2024) Box G. "Box and Jenkins: Time Series Analysis, Forecasting and Control". Palgrave Macmillan UK. pp. 161–215. (1970)