Nur Hamidah Abdul Halima, D. Susanti, Alit Kartiwa, E. S. Hasbullah
It has been widely studied how investors will allocate their assets to an investment when the return of assets is normally distributed. In this context usually, the problem of portfolio optimization is analyzed using mean-variance. When asset returns are not normally distributed, the mean-variance analysis may not be appropriate for selecting the optimum portfolio. This paper will examine the consequences of abnormalities in the process of allocating investment portfolio assets. Here will be shown how to adjust the mean-variance standard as a basic framework for asset allocation in cases where asset returns are not normally distributed. We will also discuss the application of the optimum strategies for this problem. Based on the results of literature studies, it can be concluded that the expected utility approximation involves averages, variances, skewness, and kurtosis, and can be extended to even higher moments.
{"title":"Abnormal Portfolio Asset Allocation Model: Review","authors":"Nur Hamidah Abdul Halima, D. Susanti, Alit Kartiwa, E. S. Hasbullah","doi":"10.46336/ijbesd.v1i1.18","DOIUrl":"https://doi.org/10.46336/ijbesd.v1i1.18","url":null,"abstract":"It has been widely studied how investors will allocate their assets to an investment when the return of assets is normally distributed. In this context usually, the problem of portfolio optimization is analyzed using mean-variance. When asset returns are not normally distributed, the mean-variance analysis may not be appropriate for selecting the optimum portfolio. This paper will examine the consequences of abnormalities in the process of allocating investment portfolio assets. Here will be shown how to adjust the mean-variance standard as a basic framework for asset allocation in cases where asset returns are not normally distributed. We will also discuss the application of the optimum strategies for this problem. Based on the results of literature studies, it can be concluded that the expected utility approximation involves averages, variances, skewness, and kurtosis, and can be extended to even higher moments.","PeriodicalId":441425,"journal":{"name":"International Journal of Business, Economics, and Social Development","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115958022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Exogenous liquidity risk measurement is a measurement of liquidity risk that affects all market participants and is not affected by the actions of any other actors. Exogenous liquidity risk measurement is usually called the Cost of Liquidity (COL). The main problem is how the level of liquidity of one currency against other currencies and the effect of liquidity risk on VaR (Value at Risk) on a single asset. This thesis examines the importance of liquidity risk on a single asset. Combining basic VaR and liquidity risk will result in more effective calculations. The model used is to add the basic VaR value with the Cost of Liquidity (COL) or also called Liquidity VaR (L-VaR). The calculation results show the different effects of liquidity for each country's currency. Indonesian Rupiah (IDR) is the currency that has the highest liquidity component compared to the Japanese Yen (JPY) and the Thai Baht (THB). The lower the liquidity component of a currency, the currency is very liquid, and the Japanese Yen (JPY) is the most liquid currency compared to the Indonesian Rupiah (IDR) and the Thai Baht (THB).
{"title":"Application of Exogenous Liquidity Risk Models to Analyze Single Assets","authors":"Y. Salih, Riaman Riaman, K. Komar, Alit Kartiwa","doi":"10.46336/ijbesd.v1i1.15","DOIUrl":"https://doi.org/10.46336/ijbesd.v1i1.15","url":null,"abstract":"Exogenous liquidity risk measurement is a measurement of liquidity risk that affects all market participants and is not affected by the actions of any other actors. Exogenous liquidity risk measurement is usually called the Cost of Liquidity (COL). The main problem is how the level of liquidity of one currency against other currencies and the effect of liquidity risk on VaR (Value at Risk) on a single asset. This thesis examines the importance of liquidity risk on a single asset. Combining basic VaR and liquidity risk will result in more effective calculations. The model used is to add the basic VaR value with the Cost of Liquidity (COL) or also called Liquidity VaR (L-VaR). The calculation results show the different effects of liquidity for each country's currency. Indonesian Rupiah (IDR) is the currency that has the highest liquidity component compared to the Japanese Yen (JPY) and the Thai Baht (THB). The lower the liquidity component of a currency, the currency is very liquid, and the Japanese Yen (JPY) is the most liquid currency compared to the Indonesian Rupiah (IDR) and the Thai Baht (THB).","PeriodicalId":441425,"journal":{"name":"International Journal of Business, Economics, and Social Development","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130541459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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