Most existing portfolio choice models ignore the prevalent periodic market closure and the fact that market volatility is significantly higher during trading periods. We find that market closure and the volatility difference across trading and nontrading periods significantly change optimal trading strategies. In addition, we numerically demonstrate that transaction costs can have a first order...

In this paper we review the factors that may lead to structural changes in stock market volatility and present an analysis that assesses whether emerging stock market volatility has changed significantly over the period 1976:01-2002:03. This period corresponds to the years of more profound development of both the financial and the productive sides in emerging countries. We use alternative metho...

This paper presents an econometric analysis of the effects of price support program and stocks on price dynamics and price volatility. Considering a price support program as a censoring scheme, market prices are specified as a dynamic Tobit model under time varying volatility. The model is applied to the U.S. nonfat dry milk market, based on monthly data for the period of 1970-2000. The econome...

The implied volatility, calculated using the Black-Scholes model, is currently the most popular method of estimating volatility and is considered by traders to be a significant factor in signalling price movements in the underlying market. Thus, the ability to develop accurate forecasts of future volatility allows a trader to establish the proper strategic position in anticipation of changes in...

in this research the asymmetric and non-linear correlation between the market returns and trading volume variables has modeled with the dcc-garch approach; and the impacts of market shocks, weekend and calendar effects on the market returns and trading volume are surveyed. the estimation results of parameters of the model by the maximum likelihood method show that previous day’s market return h...

Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model that is able to generate volatility clustering with hyperbolically decaying autocorrelations via traders with multiple trading frequencies, using Bayesian information updates in an incomp...

Estimation of a consistent volatility model of the underlying is crucial for option hedging. The authors illustrate that, compared to the implied/constant volatility method, a local volatility function method can estimate the underlying volatility from option prices more consistently. The result is more accurate hedge parameters and smaller hedging errors. The evidence provided includes an exam...

the emphasis of this paper is the role of volatility indices on improvement artificial neural networks (anns) forecasting models for the daily usd/eur and usd/gbp exchange rates two volatility indices are used. first; the realized volatility, which is based on intra-daily data, and second the garch volatility. they are applied into the model in two ways. firstly, the lagged volatility index is ...

This study attempts to investigate the transmission of market-wide volatility between the equity markets and bond markets of Japan and the U.S. To measure the volatility transmission, the BEKK method, a decomposition approach of the multivariate GARCH (1,1) model, is used to examine the cross-market contemporaneous effect of information arrival. The time series analysis provides evidence to the...

the agricultural products’ market has always been faced with many structural problems such as marketing weakness, price fluctuations and inadequate infrastructure and transportation in iran. a major cause of such structural problems has been referred to the traditional and inefficient structure of the agricultural products’ market. hence, iran mercantile exchange started its activity since 2007...