International Conference on Actuarial Sciences [ICActS] 2025

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/4496

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Subject: search.filters.subject.Sri Lanka

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    PublicationOpen Access
    Designing an Economic Scenario Generator for Financial Risk Management of Low-Income Households in Sri Lanka: A Review
    (Department of Mathematics and Statistics, Faculty of Humanities and Sciences, SLIIT, 2025-10-10) Peiris, K. G. H. S.; Premarathna, L. P. N. D
    Low-income households in Sri Lanka face increasing financial vulnerabilities driven by unstable income, high dependence on essential goods, and exposure to inflation and external shocks. Economic Scenario Generators (ESGs), widely used in institutional risk management, offer a structured way to model uncertainty but have rarely been adapted for household-level applications. This review synthesizes literature on ESG methodologies, household financial risk in developing economies, and Sri Lanka’s socio-economic realities. It highlights the need for a household-oriented ESG framework that integrates macroeconomic shocks with micro-level financial behavior to support budgeting, debt avoidance, and policy interventions.
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    PublicationOpen Access
    Predictive Model for Monthly Made Tea Production in Sri Lanka
    (Department of Mathematics and Statistics, Faculty of Humanities and Sciences, SLIIT, 2025-10-10) Subasinghe, C; Wattegedara, N; Silva, T; Balasooriya, S; Dassanayake, K; Guruge, M.L
    This study forecasts monthly tea production in Sri Lanka by developing a suitable time series model to identify future trends in the national tea industry. The analysis is based on monthly made tea production data from January 2000 to June 2025, obtained from the Central Bank of Sri Lanka and the Sri Lanka Tea Board. After confirming the non-stationarity of the original series through the Augmented Dickey-Fuller test, both first-order and seasonal differencing were applied to achieve stationarity. The Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plotswere used to identify potential model structures.