نتایج جستجو برای: period var using sixteen models for three stock indices
تعداد نتایج: 11925193 فیلتر نتایج به سال:
This paper concerns the application of copula functions in VaR valuation. The copula function is used to model the dependence structure of multivariate assets. After the introduction of the traditional Monte Carlo simulation method and the pure copula method we present a new algorithm based on mixture copula functions and the dependence measure, Spearman’s rho. This new method is used to simula...
the primary goal of the current project was to examine the effect of three different treatments, namely, models with explicit instruction, models with implicit instruction, and models alone on differences between the three groups of subjects in the use of the elements of argument structures in terms of toulmins (2003) model (i.e., claim, data, counterargument claim, counterargument data, rebutt...
The purpose of this study is estimation of daily Value at Risk (VaR) for total index of Tehran Stock Exchange using parametric, nonparametric and semi-parametric approaches. Conditional and unconditional coverage backtesting are used for evaluating the accuracy of calculated VaR and also to compare the performance of mentioned approaches. In most cases, based on backtesting statistics Results, ...
Article history: Received 20 June 2014 Received in revised form 25 September 2014 Accepted 26 September 2014 Available online 5 October 2014 This paper investigates the time-varying impact of oil price uncertainty on stock prices in China using weekly data on ten sectoral indices over the period January 1997–February 2014. The estimation of a bivariate VAR-GARCH-in-mean model suggests that oil ...
This paper generalizes a recently proposed spatial autoregressive model and introduces a spatiotemporalmodel for forecasting stock returns.We support the view that stock returns are affected not only by the absolute values of factors such as firm size, book-to-market ratio and momentum but also by the relative values of factors like trading volume ranking and market capitalization ranking in ea...
Purpose This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining Minimum Capital Requirement (MCR) Islamic stock markets during pandemic health crisis. Design/methodology/approach evaluates performance numerous VaR models computing MCR market risk in compliance with Basel II and II.5 guidelines ten indices. Five were applied—namely RiskMetrics, Gener...
The Chinese stock market has been established for more than 20 years. Although it is not as mature as the highly developed western securities markets, it has a huge influence on the global economy. It is significant to study the risks of the Chinese stock market, especially the risk of stock indexes. Affected by the economic globalization today, more and more financial derivatives and financial...
the purpose of this study is estimation of daily value at risk (var) for total index of tehran stock exchange using parametric, nonparametric and semi-parametric approaches. conditional and unconditional coverage backtesting are used for evaluating the accuracy of calculated var and also to compare the performance of mentioned approaches. in most cases, based on backtesting statistics results, ...
In this paper we propose a multivariate quantile regression framework to forecast Value at Risk (VaR) and Expected Shortfall (ES) of multiple financial assets simultaneously, extending Taylor (2019). We generalize the Multivariate Asymmetric Laplace (MAL) joint Petrella Raponi (2019) time-varying setting, which allows us specify dynamic process for evolution both VaR ES each asset. The proposed...
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
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