Modeling Volatility Asymmetry in Government-Owned Stocks: Evidence from Value at Risk Estimation in Indonesia

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This study evaluates the comparative effectiveness of four volatility models—EWMA, GARCH(1,1), EGARCH, and TGARCH—in estimating daily Value at Risk (VaR) for a portfolio of Indonesian state-owned enterprise (SOE) stocks over the period 2019–2024. Motivated by the rapid growth of retail investor participation and increasing exposure to market risk in Indonesia’s emerging capital market, the research addresses a critical gap in empirical risk modeling for government-owned equities. A key contribution of this study lies in the integration of asymmetric GARCH-family models with Student-t innovations into a VaR estimation framework, tailored specifically to SOE stocks—an approach seldom explored in the Southeast Asian context. The analysis uses daily return data from ten liquid, sectorally diverse SOEs. Volatility is estimated via parametric methods, assuming a normal distribution for EWMA and Student-t distributions for GARCH-type models. Model accuracy is evaluated through in-sample and out-of-sample backtesting, employing MAE, RMSE, and the Kupiec and Christoffersen tests. The findings indicate that GARCH(1,1) performs most reliably at the 95% confidence level, while TGARCH demonstrates superior performance at the 99% level, particularly in capturing downside risk. EGARCH tends to produce conservative estimates, whereas EWMA underestimates tail risk. The results support a dual-model strategy for operational monitoring and capital risk management.

Strategic Multi-Factor Root Cause Analysis for Lead Time Optimization in Jewellery Manufacturing

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One of the strengths that company need to have been the ability to release new models faster than competitors. It will give the opportunity for the company to capture the market share. However, company need to have a quick mass producing for the new models after prototype released to the market. Slow mass producing will open the window for the competitor to imitate the prototype and give the chance for them to capture all the markets if they have quicker mass-producing time. This issue happens in jewellery companies in Indonesia, one of the companies is XYZ Company. Prototype models from XYZ company are widely imitated by competitors who have faster production time. To overcome this issue, company need to analyse the root cause of slow mass production process in the company. Based on this analysis, recommendations can be given to the company and applied to accelerate the production process so the company will not lose the market anymore. The root cause analysis was conducted by using a fishbone diagram with a case study in XYZ company. Through the analysis, it can be seen that the root cause of the slow production time is due to lack of human resources thar involved in production. Based on this finding, series of measures such as hiring additional employees and implementing the overtime hours for the employee can be applied to speed up the production time and even increase the capacity.