Value at Risk (VaR) is a widely used measure of market risk. Precision in the estimation volatility leads to accurate VaR forecasts. As time-varying and has clustering effect, GARCH class models helpful modeling more precisely. Studies have also shown that range-based estimates are efficient than traditional use only closing prices. Therefore, this study uses family model forecast VaR. The comp...

Background: In light of the latest global financial crisis and the ongoing sovereign debt crisis, accurate measuring of market losses has become a very current issue. One of the most popular risk measures is Value-at-Risk (VaR). Objectives: Our paper has two main purposes. The first is to test the relative performance of selected GARCH-type models in terms of their ability of delivering volatil...

Article history: Received 31 August 2012 Received in revised form 22 April 2013 Accepted 19 May 2013 Available online 25 May 2013 This paper investigates the dynamic dependence between crude oil prices and stock markets in ten countries across the Asia-Pacific region during the period from January 4, 2000 to March 30, 2012 by using unconditional and conditional copula models. The model is imple...

this research aims to use var as a risk measure to find the optimum portfolio in tehran stock exchange. in this research var which is calculated with parametric method by using the 15 daily returns of 100 companies from march 21, 2001 to november 22, 2007 was added to the markowitz model of portfolio optimization as additional constraint. by changing the accepted var and accepted confidence lev...

This study offers an application of Infinite dimension VAR technique in measuring the performance of Greek and Cypriot financial market efficiency. The model aims to explore the forces driving the performance of a large banks proxy by returns on FTSE/ATHEX20 and FTSE/ATHEX BANKS stock indices during the period of 1997–2009. IVAR analysis can be used as either an alternative or complement to rat...

today, stock investment has become an important mean of national finance. apparently, it is significant for investors to estimate the stock price and select the trading chance accurately in advance, which will bring high return to stockholders. in the past, long-term trading processes and many technical analysis methods for stock market were put forward. however, stock market is a nonlinear sys...

Contact Author: David Giles, Dept. of Economics, University of Victoria, P.O. Box 1700, STN CSC, Victoria, B.C., Canada V8W 2Y2; e-mail: [email protected]; FAX: (250) 721-6214 Abstract Extreme value theory (EVT) measures the behavior of extreme observations on a random variable. EVT in risk management, an approach to modeling and measuring risks under rare events, has taken on a prominent role in ...

Recent studies show that a negative shock in stock prices will generate more volatility than a positive shock of similar magnitude. The aim of this paper is to appraise the hypothesis under which the conditional mean and the conditional variance of stock returns are asymmetric functions of past information. We compare the results for the Portuguese Stock Market Index PSI 20 with six other Stock...

Abstract Two of the most unpredictable uncertainty indices could explain business and stock price performance TATA Consultancy Services (TCS) before after COVID‐19 pandemic. This pandemic affects predictability from indices. With second spread pandemic, IT industries have been prepared for high networking bandwidth. Moreover, bivariate VAR(1)‐GARCH(1,1) model is weaker during period. outsourcin...

In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using neural network, TS fuzzy system and hierarchical TS fuzzy techniques. To demonstrate the different techniques, we considered Nasdaq−100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index. We analyzed 7 year’s Nasdaq 100 main index values and 4 year’s NIFTY index values. ...