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The aim of this paper is to assess whether the availability of high-frequency data enhances the accuracy of extreme market risk estimation in comparison to low-frequency data by using Value-at-risk (VaR) and Expected shortfall (ES). The sample data used for analysis comprised the daily closing stock prices and 5-minute intraday stock prices of DJIA, FTSE100, BOVESPA, and MERVAL Index from 2014 to 2022. The data analysis was done to compare the performance of two-stages hybrid methods called conditional EVT that combined the GARCH, RV and HAR specification models with the EVT approach. To assess the accuracy of the VaR forecasts, out-of-sample VaR forecast was backtested by using unconditional coverage (UC) and conditional coverage (CC) tests. The VaR backtesting procedure also incorporated the utilization loss function which are the regulatory loss function (RLF) and the firm’s loss function (FLF). The accuracy of the forecasted ES was backtested by using the generalized breach indicator (GBI) method. The findings of this research emphasized that high-frequency conditional EVT, incorporating the HAR specification outperformed the low-frequency conditional EVT in predicting market risk during periods characterized by extreme returns. Based on the VaR and ES measure, the HAR-EVT typed models are the best performance model compared to the GARCH-EVT and RV-EVT typed models during both crisis and non-crisis periods. This research study contributes to the current literature on the forecasting ability of risk models by concentrating on the hybrid model of long-memory models (FIEGARCH, RV-FIEGARCH and HAR-FIEGARCH) for with the EVT approach.

This study employs a cross-sectional design with stratified random sampling method to examine if the microcredit programme of the Amanah Ikhtiar Malaysia (AIM) improves the income of hardcore poor households. This study uses a quasi-experimental approach and selected control and treatment group members from AIM's client's base--new and old clients respectively. It is evident that the AIM's microcredit programme increased the household's income and reduced the poverty rate among their hardcore poor clients in Peninsular Malaysia. Findings of the study indicate the effectiveness of microcredit in eradicating poverty. This programme should, therefore, focus on diversifying their products and services in order to increase outreach and decrease inactive borrowers and dropouts. Keywords: Microcredit, hardcore poor, poverty, income, Amanah Ikhtiar Malaysia., I. Introduction The poverty rate in Malaysia has declined dramatically after its independence. While 49.3 per cent of Malaysian households lived below the poverty line in 1970, the poverty rate [...]