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Stock Indices (stock + index)
Terms modified by Stock Indices Selected AbstractsOptimal sampling frequency for volatility forecast models for the Indian stock marketsJOURNAL OF FORECASTING, Issue 1 2009Malay Bhattacharyya Abstract This paper evaluates the performance of conditional variance models using high-frequency data of the National Stock Index (S&P CNX NIFTY) and attempts to determine the optimal sampling frequency for the best daily volatility forecast. A linear combination of the realized volatilities calculated at two different frequencies is used as benchmark to evaluate the volatility forecasting ability of the conditional variance models (GARCH (1, 1)) at different sampling frequencies. From the analysis, it is found that sampling at 30 minutes gives the best forecast for daily volatility. The forecasting ability of these models is deteriorated, however, by the non-normal property of mean adjusted returns, which is an assumption in conditional variance models. Nevertheless, the optimum frequency remained the same even in the case of different models (EGARCH and PARCH) and different error distribution (generalized error distribution, GED) where the error is reduced to a certain extent by incorporating the asymmetric effect on volatility. Our analysis also suggests that GARCH models with GED innovations or EGRACH and PARCH models would give better estimates of volatility with lower forecast error estimates. Copyright © 2008 John Wiley & Sons, Ltd. [source] Intraday Volatility Patterns in the Taiwan Stock Market and the Impact on Volatility ForecastingASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 1 2010Yaw-Huei Wang G10; C10; C30 Abstract Given the growing importance of the Taiwan stock market, the present study sets out to provide a comprehensive investigation of the intraday time series of the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). We begin by exploring the intraday volatility patterns and then go on to examine their impact on intraday volatility forecasting. We find that the volatility of the TAIEX returns exhibits an L-shaped intraday periodic pattern, which is distinct across each day of the week. Our empirical results indicate that taking the intraday periodic pattern into account in a generalized autoregressive conditional heteroskedasticity model can substantially improve the precision of intraday volatility forecasting. [source] Regime-switching in stock index and Treasury futures returns and measures of stock market stressTHE JOURNAL OF FUTURES MARKETS, Issue 8 2010Naresh Bansal We investigate bivariate regime-switching in daily futures-contract returns for the US stock index and ten-year Treasury notes over the crisis-rich 1997,2005 period. We allow the return means, volatilities, and correlation to all vary across regimes. We document a striking contrast between regimes, with a high-stress regime that exhibits a much higher stock volatility, a much lower stock,bond correlation, and a higher mean bond return. The high-stress regime is associated with higher average values of stock-implied volatility, stock illiquidity, and stock and bond futures trading volume. The lagged implied volatility from equity-index options is useful in modeling the time-varying transition probabilities of the regime-switching process. Our findings support the notions that: (1) stock market stress can have a material influence on Treasury bond pricing, and (2) the diversification benefits of combined stock,bond holdings tend to be greater during times with relatively high stock market stress. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:753,779, 2010 [source] Tick sizes and relative rates of price discovery in stock, futures, and options markets: Evidence from the Taiwan stock exchangeTHE JOURNAL OF FUTURES MARKETS, Issue 1 2009Yu-Lun Chen This study examines the competition in price discovery among stock index, index futures, and index options in Taiwan. The price-discovery ability of the Taiwan Top 50 Tracker Fund, an exchange-traded fund based on the Taiwan 50 index is examined. The authors find that, after the minimum tick size in the stock market decreases, the bid,ask spreads of the component stocks of the stock index and the Taiwan Top 50 Tracker Fund get lower, and the contribution of the spot market to price discovery increases. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 29:74,93, 2009 [source] Combining wavelet-based feature extractions with relevance vector machines for stock index forecastingEXPERT SYSTEMS, Issue 2 2008Shian-Chang Huang Abstract: The relevance vector machine (RVM) is a Bayesian version of the support vector machine, which with a sparse model representation has appeared to be a powerful tool for time-series forecasting. The RVM has demonstrated better performance over other methods such as neural networks or autoregressive integrated moving average based models. This study proposes a hybrid model that combines wavelet-based feature extractions with RVM models to forecast stock indices. The time series of explanatory variables are decomposed using some wavelet bases and the extracted time-scale features serve as inputs of an RVM to perform the non-parametric regression and forecasting. Compared with traditional forecasting models, our proposed method performs best. The root-mean-squared forecasting errors are significantly reduced. [source] Tail-dependence in stock-return pairsINTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 2 2002Ines Fortin The empirical joint distribution of return pairs on stock indices displays high tail-dependence in the lower tail and low tail-dependence in the upper tail. The presence of tail-dependence is not compatible with the assumption of (conditional) joint normality. The presence of asymmetric tail-dependence is not compatible with the assumption of a joint student-t distribution. A general test for one dependence structure versus another via the profile likelihood is described and employed in a bivariate GARCH model, where the joint distribution of the disturbances is split into its marginals and its copula. The copula used in the paper is such that it allows for the existence of lower tail-dependence and for asymmetric tail-dependence, and is such that it encompasses the normal or t-copula, depending on the benchmark tested. The model is estimated using bivariate data on a set of European stock indices. We find that the assumption of normal or student-t dependence is easily rejected in favour of an asymmetrically tail-dependent distribution. Copyright © 2002 John Wiley & Sons, Ltd. [source] Extreme US stock market fluctuations in the wake of 9/11JOURNAL OF APPLIED ECONOMETRICS, Issue 1 2008S. T. M. Straetmans We apply extreme value analysis to US sectoral stock indices in order to assess whether tail risk measures like value-at-risk and extremal linkages were significantly altered by 9/11. We test whether semi-parametric quantile estimates of ,downside risk' and ,upward potential' have increased after 9/11. The same methodology allows one to estimate probabilities of joint booms and busts for pairs of sectoral indices or for a sectoral index and a market portfolio. The latter probabilities measure the sectoral response to macro shocks during periods of financial stress (so-called ,tail-,s'). Taking 9/11 as the sample midpoint we find that tail-,s often increase in a statistically and economically significant way. This might be due to perceived risk of new terrorist attacks. Copyright © 2008 John Wiley & Sons, Ltd. [source] Is there a Difference?JOURNAL OF BUSINESS FINANCE & ACCOUNTING, Issue 1-2 2007The Performance Characteristics of SRI Equity Indices Abstract:, This study analyses whether stock indices that represent socially responsible investments (SRI) exhibit a different performance compared to conventional benchmark indices. In contrast to other studies, the analysis concentrates on SRI indices and not on investment funds. This has several advantages, since transaction costs of funds, the timing activities and the skill of the fund management do not have to be considered. A direct measure of the performance effects of SRI screens is therefore examined. The 29 SRI stock indices are analysed by single-equation models as well as by multi-equation systems that exploit the information in the cross-section. SRI stock indices do not exhibit a different level of risk-adjusted return than conventional benchmarks. But many SRI indices have a higher risk relative to the benchmarks. The findings are robust to the use of different benchmark indices and apply to all common types of SRI screening. [source] The Monday effect in U.S. cotton pricesAGRIBUSINESS : AN INTERNATIONAL JOURNAL, Issue 3 2009Stephen P. Keef There is an extensive literature on the Monday effect with stock indices. It is regularly reported that the return on Monday is correlated with the return on the prior Friday. The bad Monday effect occurs when the return on the preceding Friday is negative. Cotton is an economically important commodity in the United States and around the world. This investigation into the daily price seasonality in the U.S. cotton market is based on spot prices from Memphis and futures prices from the New York Cotton Exchange. The regression methodologies employ adjustments to control for undesirable properties in the error terms. There are three main conclusions. First, the close-to-close changes in the futures price and in the spot price exhibit a negative Monday effect. Second, a negative bad Monday effect is observed on Mondays using close-to-close prices. The effect is present during the weekend nontrading period and continues into trading on Mondays. Third, the negative bad Monday effect does not appear to weaken in close-to-close prices and during the weekend over the period examined (1987,2003). However, there is weak evidence of a temporal decline during trading on Mondays. [EconLit Citations: G12, G14, Q14]. © 2009 Wiley Periodicals, Inc. [source] A new information share measureTHE JOURNAL OF FUTURES MARKETS, Issue 4 2009Donald Lien In this study, we modify the information share (IS) originally proposed by Hasbrouck, J. (1995). The proposed modified information share (MIS) leads to a unique measure of price discovery instead of the upper and lower IS bounds. Performance of MIS is compared with the Hasbrouck IS measure and the Gonzalo,Granger permanent,transitory decomposition (PT/GG)-based measure using simulations with 1,000 replications applied to the same three examples considered by Hasbrouck, J. (2002). The MIS is found to outperform both Hasbrouck IS measure and PT/GG measure. The empirical application of the MIS to three major stock indices indicates that price discovery takes place mostly in the futures market. Hence, the evidence supports the transaction cost hypothesis as well as the model proposed by Garbade, K. D., and Silber, W. L. (1983). © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:377,395, 2009 [source] Value at risk and conditional extreme value theory via markov regime switching modelsTHE JOURNAL OF FUTURES MARKETS, Issue 2 2008Yau Man Ze-to Samuel This study develops a new conditional extreme value theory-based (EVT) model that incorporates the Markov regime switching process to forecast extreme risks in the stock markets. The study combines the Markov switching ARCH (SWARCH) model (which uses different sets of parameters for various states to cope with the structural changes for measuring the time-varying volatility of the return distribution) with the EVT to model the tail distribution of the SWARCH processed residuals. The model is compared with unconditional EVT and conditional EVT-GARCH models to estimate the extreme losses in three leading stock indices: S&P 500 Index, Hang Seng Index and Hang Seng China Enterprise Index. The study found that the EVT-SWARCH model outperformed both the GARCH and SWARCH models in capturing the non-normality and in providing accurate value-at-risk forecasts in the in-sample and out-sample tests. The EVTSWARCH model, which exhibits the features of measuring the volatility of a heteroscedastic financial return series and coping with the non-normality owing to structural changes, can be an alternative measure of the tail risk. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:155,181, 2008 [source] A Markov regime switching approach for hedging stock indicesTHE JOURNAL OF FUTURES MARKETS, Issue 7 2004Amir Alizadeh In this paper we describe a new approach for determining time-varying minimum variance hedge ratio in stock index futures markets by using Markov Regime Switching (MRS) models. The rationale behind the use of these models stems from the fact that the dynamic relationship between spot and futures returns may be characterized by regime shifts, which, in turn, suggests that by allowing the hedge ratio to be dependent upon the "state of the market," one may obtain more efficient hedge ratios and hence, superior hedging performance compared to other methods in the literature. The performance of the MRS hedge ratios is compared to that of alternative models such as GARCH, Error Correction and OLS in the FTSE 100 and S&P 500 markets. In and out-of-sample tests indicate that MRS hedge ratios outperform the other models in reducing portfolio risk in the FTSE 100 market. In the S&P 500 market the MRS model outperforms the other hedging strategies only within sample. Overall, the results indicate that by using MRS models market agents may be able to increase the performance of their hedges, measured in terms of variance reduction and increase in their utility. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:649,674, 2004 [source] Realize the Realized Stock Index VolatilityASIAN ECONOMIC JOURNAL, Issue 1 2004Ho-Chuan (River) Huang This paper constructs estimates of daily stock index volatilities and correlation using high-frequency (one-minute) intraday stock indices. The key feature of these ,realized' volatilities and correlations is that they are not only model-free but also approximately measurement-error-free. In fact, they can be treated as observed rather than latent, so that direct modeling and forecasting of the realized volatilities can be performed using conventional time series approaches. Some interesting results appear in the analysis. Despite the fact that the unstandardized returns are skewed to the right and have fatter tails than normal, the distributions of the raw returns scaled by the realized standard deviations appear to be approximately Gaussian. The unconditional distributions of the realized variances and covariances are leptokurtic as well as highly right-skewed, but the realized correlation tends to be approximately normally distributed. There is no evidence in support of asymmetric volatility effects commonly found in previous findings. However, we find strong evidence to support the fact that there exists high contemporaneous correlation between realized volatilities and high comovement between realized correlation and volatilities. [source] | ||||||||||||||||||||||