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Examining the consistence of futures margin levels using bivariate extreme value copulas
Abstract
This study examines the consistence of the futures margin levels of different commodities and combinations in the CME group by Extreme Value Copula (EVC).We find that if we ignore the co-movements of the commodities, the margins become consistent with each other, and the margin violation rates hover around 0.5%. However, if we consider the co-movement of the related commodities using EVC, the margin levels are found to be not consistent anymore, especially in the combinations of strongly related commodities which are in the same category. Therefore, we suggest that the CME group should try to harmonize the margins policy with respect to the dependence between the futures in the future. © 2014 by the Mathematical Association of Thailand. All rights reserved.
Background:
Worldwide, patients have posted millions of online reviews for their doctors. The rich textual information in the online reviews holds the potential to generate insights into how patients' experience with their doctors differ across nations and how should we use them to improve our health service.
Objective:
We apply customized text mining techniques to compare online doctor reviews from China and the United States, in order to measure the systematic differences in patient reviews between the two countries, and assess the potential insights that can be derived from this large volume of online text data.
Methods:
We compare the textual reviews of obstetrics and gynecology (OBGYN) doctors from the two most popular online doctor rating websites in the U.S. and China, respectively: RateMDs.com and Haodf.com. We apply a customized text mining technique, Latent Dirichlet Allocation (LDA) topic modeling to identify the major topics in positive and negative reviews of those two countries. We then compare their similarities and differences.
Results:
Among the positive reviews, both Chinese and American patients talked about medical treatment, bedside manner, and appreciation/recommendation, but Chinese patients commented more about medical treatment while American patients focused more on recommendation. Also, reviews about bedside manner from Chinese patients were more related to doctors while on the American side, they were more about staff. This reflects the difference between the two countries' health systems. Further, among the negative reviews, both countries' patients talked about medical treatment, bedside manner, and logistics. However, Chinese patients focus more on the registration process, while American patients are more related to the staff, wait time, and insurance, which further shows the differences between the two nations' health systems.
Conclusions:
Online doctor reviews contain valuable information that can generate insights on the similarities and differences of patient experience across nations. They are useful assets to assist healthcare consumers, providers, and administrators in moving toward a patient-centered care. In this age of big data, online doctor reviews can be a valuable source for international perspectives on healthcare systems.
Being the limits of copulas of componentwise maxima in independent random samples, extreme-value copulas can be considered
to provide appropriate models for the dependence structure between rare events. Extreme-value copulas not only arise naturally
in the domain of extreme-value theory, they can also be a convenient choice to model general positive dependence structures.
The aim of this survey is to present the reader with the state-of-the-art in dependence modeling via extreme-value copulas.
Both probabilistic and statistical issues are reviewed, in a nonparametric as well as a parametric context.
Along with price limits and capital requirements, the margin mechanism ensures the integrity of futures markets. Margin committees and brokers in futures markets face a trade-off when setting the margin level. A high level protects brokers against insolvent customers and thus reinforces market integrity, but it also increases the cost supported by investors and in the end makes the market less attractive.This article develops a new method for setting the margin level in futures markets. It is based on “extreme value theory,” which gives interesting results on the distribution of extreme values of a random process. This extreme value distribution is used to compute the margin level for a given probability value of margin violation desired by margin committees or brokers. Extreme movements are central to the margin-setting problem, because only a large price variation may cause brokers to incur losses. An empirical study using prices of silver futures contracts traded on COMEX is also presented. The comparison of the extreme value method with a method based on normality shows that using normality leads to dramatic underestimates of the margin level. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 127–152, 1999
This paper applies the extreme-value (EV) generalised pareto distribution to the extreme tails of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses tail estimators from these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to VaR and expected shortfall (ES) risk measures, and compares the precision of their estimators. It also discusses the usefulness of these risk measures in the context of clearinghouses setting initial margin requirements, and compares these to the SPAN measures typically used.
A copula approach is used to examine the extreme return–volume relationship in six emerging East-Asian equity markets. The empirical results indicate that there is significant and asymmetric return–volume dependence at extremes for these markets. In particular, extremely high returns (large gains) tend to be associated with extremely large trading volumes, but extremely low returns (big losses) tend not to be related to either large or small volumes.