00000caa a22000003i 4500 UP-1685594773862408641 Buklod 20210406144147.0 m | | ta 210706s2015 xx a r |||| u|eng d 16551516 (iLib)UPBAG-00039679799 BAG rda eng ARTICLE-2971 Cayton, Peter Julian A. author. Time-varying conditional Johnson Su density in value-at-risk methodology Peter Julian A. Cayton and Dennis S. Mapa. [Quezon City] School of Economics, University of the Philippines 2015. pages 23-44 illustrations 23 cm text rdacontent unmediated rdamedia volume rdacarrier Title was 'Philippine Review of Business and Economics' until 1979. Title changed to 'Philippine Review of Economics and Business' from 1980-2000, and again changed to 'Philippine Review of Economics' since 2001. Includes bibliographical references (pages 42-43) Value-at-Risk (VaR) is a standard method of forecasting future losses in a portfolio of financial assets. An alternative method of estimating VaR using time-varying conditional Johnson SU distribution is introduced in this paper, and the method is compared with other existing VaR models. Two estimation procedures using the Johnson distribution are developed in the paper: (1) the joint estimation of the volatility; and (2) the two-step procedure where estimation of the volatility is separated from the estimation of higher parameters, i.e., skewness and kurtosis. Empirical analyses of the two procedures are illustrated using data on foreign exchange rates and the Philippine Stock Exchange index. The methods are assessed using the standard forecast evaluation measures used in VaR models. Modeling procedures where estimation of higher parameters can be integrated in VaR methodology are introduced in the paper. Income forecasting Econometric models Philippines. Financial risk management Econometric models Philippines. Financial risk Econometric models Philippines. Risk management Philippines. Estimation theory. Mapa, Dennis S. author. The Philippine Review of Economics Vol. 52, no. 1 (June 2015), p. 23-44. Request full-text access via UPB University Library through https://forms.gle/KZjBv7aRtY6jiL5E9 FI UPBAG UPBAG-MAIN ARTICLE-2971 Analytics