Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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The past decade has witnessed the rapid growing of the world palladium market. Thus, it is even more important to develop effective quantitative tools for risk management of palladium assets at this moment. In this paper, we investigate five different types of widely-used statistical distributions and employ the industry standard risk measurement, Value at Risk, for risk management of daily palladium spot returns. We first apply four different criteria to compare the goodness of fit of the five distributions, and then calculate the VaRs based on the parameters estimated from the first step. Our results indicate the Skewed t distribution has the best in-sample fitting and generate VaR values closest to the nonparametric historical VaR values.
Jianhua Ding. 2018. \u201cFat Tails Value at Risk and the Palladium Returns\u201d. Global Journal of Management and Business Research - B: Economic & Commerce GJMBR-B Volume 18 (GJMBR Volume 18 Issue B3): .
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Crossref Journal DOI 10.17406/GJMBR
Print ISSN 0975-5853
e-ISSN 2249-4588
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 133
Country: China
Subject: Global Journal of Management and Business Research - B: Economic & Commerce
Authors: Turen Guo, Jianhua Ding, Bin Guo (PhD/Dr. count: 0)
View Count (all-time): 143
Total Views (Real + Logic): 3092
Total Downloads (simulated): 1492
Publish Date: 2018 05, Fri
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Neural Networks and Rules-based Systems used to Find Rational and
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The past decade has witnessed the rapid growing of the world palladium market. Thus, it is even more important to develop effective quantitative tools for risk management of palladium assets at this moment. In this paper, we investigate five different types of widely-used statistical distributions and employ the industry standard risk measurement, Value at Risk, for risk management of daily palladium spot returns. We first apply four different criteria to compare the goodness of fit of the five distributions, and then calculate the VaRs based on the parameters estimated from the first step. Our results indicate the Skewed t distribution has the best in-sample fitting and generate VaR values closest to the nonparametric historical VaR values.
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