In this paper, a version of the Vector Auto Regression (VAR) model has been used to investigate the interacted and dynamic effects between social capital and economic development in Iran during the period 1987-2006. To this purpose, variables of human capital, health and income distribution have been considered as the proxies of economic development. In addition, the volume of risky bank chequ...

One of the most important methods employed to measure the market risk is value at risk calculation method. In this study, the value at risk of banks listed on the Tehran Stock Exchange and Over-the-counter (OTC) are calculated using parametric model, Monte Carlo simulation, historical simulation and Two-Sided Power (TSP) Distribution. The sample includes all listed banks in Iran. The results sh...

We develop a new asymptotic theory for autocorrelation robust tests using a vector autoregressive (VAR) covariance matrix estimator. In contrast to the conventional asymptotics where the VAR order goes to in…nity but at a slower rate than the sample size, we have the VAR order grow at the same rate, as a …xed fraction of the sample size. Under this …xed-smoothing asymptotic speci…cation, the as...

This note investigates long-run exclusion in a cointegrated vector autoregressive (VAR) model from the viewpoint of …nite-sample statistical inference. Monte Carlo experiments show that, in various circumstances, a mis-speci…ed partial VAR model, which is justi…ed by the existence of a long-run excluded variable, can lead to better …nite-sample inference for cointegrating rank than a fully-spec...

We estimate values-at-risk (VaR) in the accumulation phase of defined-contribution pension plans. We examine a range of asset-return models (including stationary moments, regime-switching and fundamentals models) and a range of asset-allocation strategies (both static and with simple dynamic forms, such as lifestyle, threshold and constant proportion portfolio insurance). We draw four conclusio...

a r t i c l e i n f o JEL classification: C53 G17 Keywords: GARCH Higher conditional moments Approximate predictive distributions Value-at-Risk S&P 500 Treasury bill rate Euro–US dollar exchange rate It is widely accepted that some of the most accurate Value-at-Risk (VaR) estimates are based on an appropriately specified GARCH process. But when the forecast horizon is greater than the frequency...

In this paper, employing VAR and factor analytic models with quarterly U.K. sectoral business investment data, we show that both common and sector–specific shocks play important roles in explaining business investment fluctuations. JEL: C32, E22, E32.

Article history: Received 10 May 2013 Received in revised form 2 September 2014 Accepted 2 September 2014 Available online 11 September 2014 The study investigates the relative performance of Value-at-Risk (VaR) models using daily share price index data from six different countries across Asia, Europe and the United States for a period of 10 years from January 01, 2000 toDecember 31, 2009. Them...

The main goal of the present study is testing asymmetric risk pricing and comparing it with pricing of traditional risk measures in Tehran Stock Market. Accordingly, a sample consisting of 101 companies listed in Tehran Stock Market during 2002-2013 went under investigation. In order to test asymmetric risk pricing, regression model of panel data was applied. The results revealed a positive and...