Browsing by Subject "The Journal of Risk Management and Insurance -- 2018"
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ItemFactors influencing overindebtedness: a logistic regression analysis of consumers in BangkokOverindebtedness is a source of default risk facing by commercial banks and loan institutions. Although studies of factors influencing individuals’ indebtedness are prevalent, less of previous studies had examined financial factors distinguishing mild-debtors from overindebted individuals. The present study aims at identifying and empirically testing the financial factors (i.e. financial literacy, experiences in using financial services, and money management) which distinguish mild-debtors from overindebted individuals. Questionnaires were distributed to 440 respondents who are at working age in Bangkok area. Logistic regression analysis was employed in order to identify critical factors distinguishing milddebtors from overindebted individuals. Findings from the present study indicated that financial literacy and experience in using financial services were not significant factors that distinguished mild-debtors from overindebted individuals. Money management, i.e. credit management and saving management were found to be the most significant factors distinguishing mild-debtors from overindebted individuals. Results from the present study provide implications for financial institutions to reduce adverse selection problems. Since credit management is the most critical factors influencing overindebtedness beyond other factors, records of previous credit usages and payment behaviors of individuals must be seriously take into account when determining credit approval. To reduce insolvency risk, credit rating must be used as the first priority when financial institutions approving loans. In addition, results from the present study also provide implications for policy makers to reduce personal debt problem. Since financial literacy in term of numeric calculation is not a significant factors affecting overindebtedness, financial education that emphasizes mathematic and numeric calculation may not sufficient to reduce overindebtedness problem, training on how to manage individuals’ budget, saving, and using credit carefully must be emphasized to reduce financial problems.
ItemThe Halloween effect and other seasonal anomalies in the energy sector of the stock exchange of ThailandThis research aims to explore the existence of three well - known seasonal anomalies – the January Effect, the April Effect, and the Halloween Eff ect – as pertains to monthly returns as well as to volatility. Effects on returns and volatility will further be studied within the SET Energy index as well as 9 selected energy stocks from the period April 2005 to July 2016. The objective of this study is to find seasonality hidden within the above Index and stocks, and establish a simple trading strategy to benefit investors. As in preceding studies, our methodology uses the dummy regression technique and the EGARCH model is employed to investigate the impact of these seasonal anomalies on the volatility of returns. The result found that Halloween Effect and the January Effect have a statistically negligible effect on returns within the smaller SET Energy Index. The April Effect does have statistical s ignificance on returns within the SET Energy Index. Buying the SET Energy index before April is likely to yield positive returns at the end of the month. Investors should accumulate positions during these seasonal anomalies – in light of low volatility – a nd take profit once volatility returns to normal.
ItemValue at risk performance in cryptocurrenciesDue to conclusion could not rely on only one test, in this study, we apply various approaches to verify the actuary of VaR model to find out whether VaR model, especially historical VaR and delta normal VaR model, can provide the accura te risk measurement results for cryptocurrencies risk , especially CRIX, BTC, ETH and XRP . We use Kupiec’s POF test, Independence Test - Christoffersen (1998) and Joint Test that widely use for backtesting VaR model. Performance test results for risk measurem ent by historical VaR provide a fairly accurate over delta normal VaR when we use Kupiec’s POF - test for the accuracy of VaR model. Christoffersen (1998) independence test, the exceptions (failures) of historical VaR and delta normal VaR model show independ ence exceptions in accordance with an only high confidence level of critical values (0.99). Otherwise , the low confidence level of critical values (0.90 and 0.95) appears dependence exceptions. For the Joint test, we combine POF - test and independence test because each model has different advantages and disadvantages. The results show that historical VaR model is suitable for measuring cryptocurrency risk over delta normal VaR only high confidence level of critical values.