High frequency foreign exchange rate (HFFX) series are analyzed on an operational time scale using models of the ARCH class. Comparison of the estimated conditional variances focuses on the asymmetry and persistence issue. Estimation results for para-metric models connrm standard results for HFFX series, namely high persistence and no signiicance of the asymmetry coeecient in an EGARCH model. T...

In this paper, we have examined abrupt changes in volatility of TEPIX index in Tehran stock exchange during August 23, 2010 to June 12, 2014. Applying the iterated cumulative sum of squares (ICSS) algorithm proposed by Inclan and Tiao (1994) and the modified version of this algorithm consisting Kappa 1 and Kappa 2 test statistics developed by Sansó et al. (2004), we have specified that the dete...

â â â  â â â â â  the main purpose of present study is to analyze the relationship between stock and exchange markets in two asian countries, iran and south korea. a monthly time series of stock price and exchange rate are used over the period 2002: 05 - 2012: 03. the data is collected from the central bank of each country and wdi. the calculated stock return and real exchange rate change are u...

This paper investigates the existence of long memory in the volatility of the Mexican stock market. We use a stochastic volatility (SV) model to derive statistical test for changes in volatility. In this case, estimation is carried out through the Kalman filter (KF) and the improved quasi-maximum likelihood (IQML). We also test for both persistence and long memory by using a long-memory stochas...

Research on the impact of the introduction of derivatives on the market volatility has reported mixed evidences. In this paper, we study the volatility implications of the introduction of derivatives on the stock market in India using S&P CNX IT index. To account for the heteroscedasticity in the time series, GARCH model is used. We find clustering and persistence of volatility in different deg...

This paper proposes a new mechanism to explain the dynamics of asset return volatility. Random shocks to asset fundamentals arrive according to a Poisson process. Financial analysts gradually reduce the uncertainty created by a shock subject to capacity constraints or cost of effort associated with processing information. In the short-run, analysts work at their maximum capacity to digest the s...

How persistent is volatility? In other words, how quickly do financial markets forget large volatility shocks? Figure 1.1, Shephard (attached) shows that daily squared returns on exchange rates and stock indices can have autocorrelations which are significant for many lags. In any stationary ARCH or GARCH model, memory decays exponentially fast. For example, if {εt } are ARCH (1), the {εt} have...

This study compares the dynamic characteristic of Chinese and American energy prices from perspectives learning expectation, volatility, persistence, so on. First, most suitable speeds for are determined price expectations calculated by models. Second, volatility characteristics Granger-spillover effects among different examined using stochastic models based on coefficient significance DIC crit...

Recent empirical studies show that the squares of high-frequency stock returns are long-range dependent and can be modeled as fractionally integrated processes, using, for example, long-memory stochastic volatility models. Are such long-range dependencies common among stocks? Are they caused by the same sources of variation? In this paper, we classify daily stock returns of S&P 500 companies on...

  The main purpose of present study is to analyze the relationship between stock and exchange markets in two Asian countries, Iran and South Korea. A monthly time series of stock price and exchange rate are used over the period 2002: 05 - 2012: 03. The data is collected from the Central Bank of each country and WDI. The calculated stock return and real exchange rate change are used in analysis....