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Copyright of Journal of Social Sciences Institute / Sosyal Bilimler Enstitüsü Dergisi is the property of Bingol University / Rectorate and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Using event-study techniques, we investigate the impact of Brexit-related events on the spot exchange rate of the British pound against the euro and the US dollar. We want to find out whether Brexit-related news, including the Brexit referendum itself, has an impact on British pound exchange rates. By splitting our Brexit-related events into 'good' Brexit news and 'bad' Brexit news, we find that Brexit news has an impact on British pound exchange rates. Bad Brexit news is associated with a depreciation of the British pound against the euro and the US dollar whereas 'good' Brexit news appreciates the Pound against the euro. Furthermore, our empirical results suggest that market participants display a delayed reaction to bad Brexit news. As the referendum has clearly a significant impact on both British pound/euro and British pound/US dollar exchange rate volatility, the impact of Brexit news is only for the British pound/euro exchange rate volatility measurable. Besides the asymmetric volatility pattern towards positive and negative shocks in general, we find that the statistically significance and the magnitude of the impact of good Brexit news is higher than these of bad Brexit news. Concerning the British pound/US dollar exchange rate volatility, our results display a weak presence of volatility asymmetry in terms of shocks and good/bad Brexit news, respectively. [ABSTRACT FROM AUTHOR]

Highlights • A new integrated model is proposed to better describe electricity price changes. • It integrates the improved EMD (IEMD) approach and the ARMAX-EGARCH-ANFIS methods. • The new model is validated by the data of both Spanish and Australian markets. • The new model has higher forecasting accuracy than some well-recognized models. Abstract Electricity price forecasting proves useful for power producers and consumers to make proper decisions in a market-oriented environment. However, due to the complex drivers and sharp fluctuation of electricity prices, accurate electricity price forecasting turns to be very difficult. To better capture the characteristics of day-ahead electricity prices, a new integrated model based on the improved empirical mode decomposition (IEMD), autoregressive moving average with exogenous terms (ARMAX), exponential generalized autoregressive conditional heteroscedasticity (EGARCH) and adaptive network-based fuzzy inference system (ANFIS) is proposed in this paper. Then it is validated by using the data from Spanish and Australian electricity markets. The results indicate that the forecasting accuracy of the new integrated model proves higher than that of some well-recognized models in the literature. [ABSTRACT FROM AUTHOR]

The difference between the theoretical prices of Black-Scholes derivatives and market prices is reason for researchers to look for more accurate and sophisticated models of financial markets. There is no doubt that volatility as a parameter of financial market changeability due to the emergence of "good" and "bad" news, is not a constant and can be considered as a stochastic process. The financial market models under this approach are called stochastic volatility models and have been known since R. Engle's research. In an effort to improve this approach, we propose the so-called chaotic volatility models, which are formed from the known ARCH stochastic volatility models, GARCH, EGARCH, by using "dynamic chaos" sequences instead of white noise. The ideo of the existence of a fractal market and the application of "dynamic chaos" was discussed in the works of B. Mandelbrot, Y. Fam, A. Shiryaev and others. A. Shiryaev in his works indicates that the behavior of sequences of "dynamic chaos" under certain parameter values is similar to the behavior of "white" noise. In the work among the representatives of chaotic sequences, was selected the logistic sequence. For real data, three models were constructed from the class of autoregressive heteroscedastic models with stochastic and chaotic volatility. The news impact curve was considered, which measures how new information is incorporated into volatility estimates. An asymmetric reaction of volatility to world positive and negative news has been revealed. In practice it is proven that EGARCH model accounts the best the asymmetry effect and describes the changing situation in the securities and derivatives market. The theoretical stock prices were predicted by using stochastic and chaotic volatility models. Having conducted a comparative analysis of the model prices with the market prices by calculating the relative error, it can be seen that the models proposed in the article with chaotic volatility have less relative error. [ABSTRACT FROM AUTHOR]

Executive Summary. In this study, we investigate the time-varying response of conditional variance to endogenous and exogenous shocks. Using MSA-level monthly data spanning 31 years and two asymmetric volatility models, we find evidence of volatility clustering and the asymmetric effects of good and bad news on conditional variance. The conditional variances of "superstar" cities suggest that they strongly respond to good news but mildly respond to bad news. Conversely, the conditional variances of Southern and Midwestern cities in the U.S. respond strongly to bad news but marginally to good news. The evidence has important implications for the pricing of real estate derivatives and on the adoption of dynamic hedging strategies after major shocks. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of the European Central Bank's unconventional monetary surprises on major European stock markets. Three measures for surprises are used: (a) the change in domestic 10‐year government bond yields, (b) the change in the spread between German and Italian (Spanish) 10‐year bond yields, and (c) the change in yields of a safe euro‐denominated asset, such as German bonds. I show that unconventional monetary policy surprises significantly influence stock returns. For instance, monetary decisions that cause a decrease in Italian (Spanish) sovereign spread led to an increase in the stock returns. In addition, I find that a positively surprising shock—a fall in the domestic bond yield and an increase in German interest rates—leads to higher stock returns. Finally, sovereign spreads seemed to have larger effects on stock returns both during crisis and postcrisis years. [ABSTRACT FROM AUTHOR]

Vietnam is one of the countries in Asia with the highest nonperforming loans (NPL) ratio, which has affected the operations of the bank and further, to the development of the Vietnamese economy. The State Bank of Vietnam has decided to establish the Vietnam Asset Management Company. This is a special tool of the State Bank for handling nonperforming loans, making healthy financials, minimizing risk for financial institutions and enterprises, and promoting credit growth of the economy. The purpose of this study is to investigate the impact of the Vietnam Asset Management Company as a political event on stock market return and volatility in the Vietnam stock exchange. We collected VN-index data in the Ho Chi Minh stock exchange from 2008 to the third quarter of 2014 as sample data. Using the Exponential General Autoregressive Conditional Heteroscedasticity (EGARCH) model, we found some evidence that the VAMC performances have a positive significant effect on stock market return and volatilities. [ABSTRACT FROM AUTHOR]

Copyright of Financing is the property of Financing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article considers modelling nonnormality in return with stable Paretian (SP) innovations in generalized autoregressive conditional heteroskedasticity (GARCH), exponential generalized autoregressive conditional heteroskedasticity (EGARCH)  and Glosten-Jagannathan-Runkle generalized autoregressive conditional heteroskedasticity (GJR-GARCH) volatility dynamics. The forecasted volatilities from these dynamics have been used as a proxy to the volatility parameter of the Black-Scholes (BS) model. The performance of these proxy-BS models has been compared with the performance of the BS model of constant volatility. Using a cross section of S&P500 options data, we find that EGARCH volatility forecast with SP innovations is an excellent proxy to BS constant volatility in terms of pricing. We find improved performance of hedging for an illustrative option portfolio. We also find better performance of spectral risk measure (SRM) than value-at-risk (VaR) and expected shortfall (ES) in estimating option portfolio risk in case of the proxy-BS models under SP innovations. Abbreviation: generalized autoregressive conditional heteroskedasticity (GARCH), exponential generalized autoregressive conditional heteroskedasticity (EGARCH) and Glosten-Jagannathan-Runkle generalized autoregressive conditional heteroskedasticity (GJR-GARCH) [ABSTRACT FROM AUTHOR]

Given the complex characteristics of crude oil price volatility, a new hybrid forecasting method based on the hidden Markov, exponential generalized autoregressive conditional heteroskedasticity, and least squares support vector machine models is proposed, and the forecasting performance of the new method is compared with that of well‐recognized generalized autoregressive conditional heteroskedasticity class and other related forecasting methods. The results indicate that the new hybrid forecasting method can significantly improve forecasting accuracy of crude oil price volatility. Furthermore, the new method has been demonstrated to be more accurate for the forecast of crude oil price volatility particularly in a longer time horizon. [ABSTRACT FROM AUTHOR]

This paper employs a realized beta generalized autoregressive conditional heteroskedasticity model for optimal futures hedging. The model has a flexible structure and is complete because all observed returns and realized measures are jointly modeled in a system. This enables the incorporation of important features that may affect the hedge ratio estimation. The model is applied to equity indices, and substantial dependence between return and volatility indicates the essential of modeling statistical leverage. Predictive ability testing confirms the superiority of the model for reducing the hedged portfolio risk. The predictive ability of the model can translate into pronounced economic benefits, particularly for short‐term hedges. [ABSTRACT FROM AUTHOR]

This study compares the conventional EGARCH(1,1) model and its extension which incorporates a realized measure of volatility, namely EGARCH-X(1,1) and REGARCH(1,1) models. The comparison is performed in terms of the estimating method performance and the model fit to the historical FTSE100 and SP500 stock indices over the daily period from January 2000 to December 2017. The models assume the Normal and Student-t distributions for the return errors and are estimated by using the GRG (Generalized Reduced Gradient) Non-Linear method in Excel's Solver and the Adaptive Random Walk Metropolis (ARWM) method which is implemented in Matlab program. The empirical study shows that the Excel's Solver's GRG Non-Linear method is able to estimate the model parameters since the estimation results are not considerably different from those obtained by ARWM method. In terms of fitting performance, the Akaike Information Criterion (AIC) indicates that the Student-t distribution seems to capture heavy tails in return distribution better than the Normal distribution. On the basis of loglikelihood ratio test and AIC, the models with realized measure (realized kernel in this study) provide a significant improvement over the EGARCH-X(1,1) model in each distribution, where the best fit model is given by the REGARCH(1,1) model with Student-t distribution. [ABSTRACT FROM AUTHOR]

With the advent of the Internet and the availability of user search query data on a broader scale, since the early 2000s researchers have started using collective search query information instead of, or, in addition to, traditional investor sentiment proxies. This study examines whether the leverage (bad news) effect, as measured by the EGARCH (1,1) model, changes with the inclusion of a newly emerging sentiment proxy, internet search volume. The sample consists of 14 US companies belonging to the NASDAQ and NYSE Indices and 501 observations of data collected at weekly frequency spanning a nine year period. Empirical findings suggest that, inclusion of the investor sentiment variable has no clear impact on the bad news effect; there is, however, a discernible increase in volatility persistence. The implications of the findings are that the investor sentiment proxy has additional informational content. Behavioral finance theory and the availability and social proof heuristics serve as potential explanations for such findings.

This paper examines the mean, volatility spillovers and response asymmetries between short-term and long-term interest rates, exchange rates and portfolios of money center, large and medium-sized banks in the U.S. I use the multivariate version of Nelson’s (1991) Exponential Generalized Autoregressive Conditionally Heteroscedastic (EGARCH) model. Results indicate mean and volatility spillovers from short-term interest rates and exchange rates and long-term interest rates and exchange rates to three bank portfolios. Results also show response asymmetries from short-term interest rates and exchange rates and long-term interest rates and exchange rates to all the three bank portfolios. These findings have important implications for bankers in terms of devising different hedging strategies against interest rates and exchange rate risks.

Applying the EGARCH model and using demand and supply analysis, this paper finds that the HUF/USD exchange rate (units of the Hungarian forint per U.S. dollar) is positively associated with the U.S. Treasury bill rate, U.S. real GDP, the U.S. stock index, the Hungarian inflation rate and the expected exchange rate and negatively influenced by the Hungarian Treasury bill rate, Hungarian real GDP, the Hungarian stock index, and the U.S. inflation rate. The HUF/USD exchange rate has a long-term equilibrium relationship with these time series variables.

En este artículo se analiza el efecto apalancamiento en el mercado bursátil colombiano, para dicho fin se usan modelos de la familia ARCH que permitan evaluar si tal efecto está presente en el mercado de acciones, específicamente se usan los modelos no lineales EGARCH y TGARCH. Las series elegidas para realizar dicho análisis son el Índice General de la Bolsa de Valores que es el índice más representativo del mercado de acciones del país junto con el índice COLPAC, adicionalmente se tendrán en cuenta seis de las acciones colombianas que son más transadas en la actualidad. Finalmente se encuentra que el mercado accionario de Colombia sí cuenta con efecto apalancamiento, es decir las malas noticias tienen un impacto mayor en la volatilidad de los rendimientos financieros.

Resumo: O presente estudo buscou verificar se os preços da mamona no estado da Bahia estão sujeitos à instabilidade estrutural e se a implementação do Programa Nacional de Produção e Uso do Biodiesel (PNPB) elevou tal instabilidade. Foram utilizados modelos TGARCH e EGARCH de heterocedasticidade condicional para medir a instabilidade estrutural dos preços da mamona e o efeito do PNPB sobre a volatilidade dos preços. Os resultados indicam que os preços de mamona na Bahia são instáveis, que aumentos nos preços elevam a instabilidade e que o PNPB aumentou o risco de preço no estado. Dada a aversão ao risco por parte dos produtores, a implementação do PNPB tornou a atividade menos atrativa, o que pode ter contribuído para a baixa relevância da mamona dentro do programa.

This paper analyzes the volatility dynamics in the financial markets of the (three) most powerful countries from a military perspective, namely, the U.S., Russia, and China, during the period 2015–2018 that corresponds to their intervention in the Syrian war. As far as we know, there is no literature studying this topic during such an important distress period, which has had very serious economic, social, and humanitarian consequences. The Generalized Autoregressive Conditional Heteroscedasticity (GARCH (1, 1)) model yielded the best volatility results for the in-sample period. The weighted historical simulation produced an accurate value at risk (VaR) for a period of one month at the three considered confidence levels. For the out-of-sample period, the Monte Carlo simulation method, based on student t-copula and peaks-over-threshold (POT) extreme value theory (EVT) under the Gaussian kernel and the generalized Pareto (GP) distribution, overstated the risk for the three countries. The comparison of the POT-EVT VaR of the three countries to a portfolio of stock indices pertaining to non-military countries, namely Finland, Sweden, and Ecuador, for the same out-of-sample period, revealed that the intervention in the Syrian war may be one of the pertinent reasons that significantly affected the volatility of the stock markets of the three most powerful military countries. This paper is of great interest for policy makers, central bank leaders, participants involved in these markets, and all practitioners given the economic and financial consequences derived from such dynamics.

The volatility spillover is defined as the transmission of instability from market to market. It occurs when the volatility price change in one market causes a lagged impact on volatility price in another market above the local effects of market. In this study the garchmodels are used to examine the possibility of volatility transmission between the KSE100 index (Pakistan) and S&P500 index (usa); in other words, to examine how the volatility in one market mayinfluence the other and vice versa. The egarchmodel is also applied and it was observed that our attempt to analyze symmetry and persistence in the KSE100 index and the S&P500 index volatility proved that there is clear evidence that shocks to the volatitlity of the KSE100 and S&P500 indexes have asymmetric and persistent effects. It is observed from the study that the shocks to the stock returns in one market do not transmit to the other; in other words, it appears that there is no spillover effect between the two stock markets.

This paper aims to test the effect of asymmetric shocks on the volatility of the Dow Jones Sukuk. To this end, we applied the EGARCH model to give a clear idea of the effect of asymmetric shocks on the volatility of the sukuk. Considering the daily returns of the Dow Jones Sukuk for the period from 09/06/2009 to 31/12/2013, our results suggest that the volatility of the 2009-2010 period is very sensitive to market events over the period 2010-2013 and positive shocks are more volatile than negative one. The results have important implications for the sukuk market. This result can be explained by the good transparency, disclosure and better incentives that make investors expand their business in the market for sukuk.

This paper examines short-run determinants of the U.S. dollar/Polish zloty (USD/PLN) exchange rate based on a simultaneous-equation model of demand and supply. Using a reduced form equation and the EGARCH model, the paper finds that the USD/PLN exchange rate is positively associated with the real reference rate in Poland, real GDP in the U.S., the real stock index in Poland and the expected exchange rate and is negatively influenced by the U.S. real federal funds rate, real GDP in Poland, and the real stock index in the U.S. Hence, monetary policy is effective in influencing the USD/PLN exchange rate.

Good news and bad news (commonly known as the asymmetric effect) on the price of palm oil, has been the grounds of palm oil price volatility. Estimation of volatility needs to be conducted for the purposes of advance financial analysis namely computation of the risk factors, portfolio, futures, etc. In addition, the data of palm oil price is heterscedastical. The heteroscedasticity needs to be overcome in order to generate a sound estimation of volatility. One of the forecasting models for heteroscedastical data and that capable of explaining the good news and bad news over the commodity’s price is the Exponential Autoregressive Conditional Heterocedastic (EGARCH) model.The result of this research, the best of EGARCH models was EGARCH(1,1) with t-distribution. That base of AIC and SIC value.

This paper uses daily data to investigate the behavior of institutional investors in Taiwan’s stock market. We adopted TGARCH and EGARCH models to test various news. We found that, for the entire sample, a significant clustering phenomenon exists in the investment behavior of three institutional investors, and the impact due to a change of news content shows significant asymmetry and leverage effects. That is, the impact of bad news from the market is stronger than that of good news. In addition, an asymmetric phenomenon can also be seen for the international news aspect as responded to by foreign institutional investors. This phenomenon is more significant than those of the dealers and institutional trust investors. Moreover, the asymmetric phenomenon as responded to by the dealers for domestic news is more significant than those of foreign investors and institutional trust investors.

Namibia introduced the “Small Stock Marketing Scheme” (SSMS) in 2004 which replaced 15% export duty on live sheep exports to South Africa with progressively demanding quantitative restrictions. This policy increased price volatility in the Namibian sheep market. We used relevant monthly price data and employed EGARCH modeling to determine if price volatility spilled-over from the sheep market in Namibia to South African sheep market. About 71 percent of the volatility in the Namibian sheep market is transmitted to the retail market in South Africa and the transmitted volatility remains persistent.

This paper analyses the impact of German macroeconomic news announcements and ECB meeting days on the conditional volatility of the Czech, Polish, and Hungarian Foreign Exchange markets as proxied by CZK/EUR, PLN/EUR, and HUF/EUR exchange rate returns over six years (2010-2015). A currency intervention period (11/2013-2015) in the Czech Republic is examined separately. EGARCH-type models with normal and Student's t-distributions are employed. The comprehensive analysis shows the following results. (i) The IFO index, Factory Orders increase and the PMI index from the Service Sector, the labour market data decrease conditional volatility of PLN/EUR. (ii) The IFO index and Industrial Production increase conditional volatility of HUF/EUR on the day of the announcement. (iii) Data from the labour market has a calming effect on CZK/ EUR after the central bank launched currency interventions. (iv) IFO index increases and the PMI index from the Manufacturing Sector decreases conditional volatility of CZK/EUR before currency interventions were introduced (2010-11/2013). [ABSTRACT FROM AUTHOR]

Copyright of Journal of Qadisiyah Computer Science & Mathematics is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article investigates the relationship between central bank credibility and the volatility of the key monetary policy instrument. First, we propose a time-varying measure of central bank credibility based on the gap between inflation expectations and the official inflation target. While this new index addresses the main limitations of the existing indicators, it also appears particularly suited to assess the monetary experiences of a large sample of inflation-targeting emerging countries. Second, by means of EGARCH estimations, we formally prove the existence of a negative effect of credibility on the volatility of the short-term interest rate. In line with the expectations channel of monetary policy, the higher the credibility of the central bank, the lower the need to move its instruments to effectively fulfill its objective. [ABSTRACT FROM AUTHOR]

We employ 1440 stocks listed in the S&P Composite 1500 Index of the NYSE. Three benchmark GARCH models are estimated for the returns of each individual stock under three alternative distributions (Normal, t and GED). We provide summary statistics for all the GARCH coefficients derived from 11,520 regressions. The EGARCH model with GED errors emerges as the preferred choice for the individual stocks in the S&P 1500 universe when non-negativity and stationarity constraints in the conditional variance are imposed. 57% of the constraint's violations are taking place in the S&P small cap stocks. [ABSTRACT FROM AUTHOR]

Terrorism, political system instability and currency rate fluctuations are the three most evident issues of 21st century. In this study, comparative analysis is performed to check the impact of all these issues on PSX Volatility. EGARCH (1,1) approach is used on four different kinds of data collected from 1st January 2000 to 31st December 2015. Terrorist events, FX return fluctuations with restoration of democratic political system in Pakistan are considered in this study. Results confirm that democratic political government reduces PSX volatility while terrorism increases it. Terrorist attacks are categorized into various categories. Event day analysis confirms that Pakistan stock market (PSX) is efficient enough to absorb the effects of terrorist attack within a day. Holding portfolios and performing arbitrage activit ies by the investors diversify the risks due to foreign exchange (FX) fluctuations which show no significant impact on PSX volatility. [ABSTRACT FROM AUTHOR]

The central theme of this research paper is about the role of idiosyncratic risk in stock returns of non-financial sector of Pakistan Stock Exchange. In the framework of asset pricing model, literature suggests that idiosyncratic risk is independent to the specific assets therefore it has no role in explaining the returns. However, modern portfolio theory suggests that in an under diversified portfolio, idiosyncratic risk has positive relationship with stock returns, while the negative association of idiosyncratic risk has also been reported by different scholars. To settle this issue in the context of Pakistan, the present study investigates the role of idiosyncratic risk empirically in non-financial sector of Pakistan. The daily and monthly data are taken from January 2005 to 2016 for analysis. Various types of statistical tools are applied to examine the association between idiosyncratic risk and stocks returns. Cross sectional regression is used for testing the association between expected conditional idiosyncratic risk and returns. Conditional idiosyncratic risk is estimated through EGARCH model. The empirical results showed that conditional idiosyncratic risk and return of non-financial, firms has significant positive relationship after controlling different factors such as value, momentum and size, whereas the lag idiosyncratic risk has no relationship with stock returns. The empirical evidence confirms the prediction of previous studies. At the end it is suggested that investors can develop profitable portfolio after considering the idiosyncratic risk. [ABSTRACT FROM AUTHOR]

This study examines the asymmetry in the volatility of the returns of five indices, namely, PSI 20 (Portugal), ISEQ 20 (Ireland), MIB 30 (Italy), ATHEX 30 (Greece) and IBEX 35 (Spain) using daily data from 2004-2016. For this purpose, we estimate the GJR and EGARCH asymmetric models for the whole sample and then split it into three subperiods of approximately four years each to examine how the coefficient on asymmetry behaves over time. Our results for the full sample show that all indices exhibit different levels of asymmetry. When we consider the subsample analysis however results show that while there is mixed evidence from the first to the second subperiods, all returns evidence an increase in asymmetry from the second to the last subperiod. [ABSTRACT FROM AUTHOR]

This study examines the validity of Samuelson hypothesis and the mixture of distribution hypothesis to uncover time-to-maturity and trading volume as the sources of volatility in gold and copper futures. Exponential generalized autoregressive conditional heteroskedasticity model is used for empirical analysis. Leverage effect is found in copper futures but not in gold futures. We find evidence of the Samuelson maturity effect even after controlling for the trading volume. The mixture of distribution hypothesis is strongly supported. Hence trading volume, a proxy for information arrival, is one of the important determinants of volatility, and it dominates time-to-maturity. The results have implications for setting the desired level of margin requirements in futures contracts, designing effective hedging strategy and strengthening the risk management practices. [ABSTRACT FROM AUTHOR]

This study investigates the incremental information content of implied volatility index relative to the GARCH family models in forecasting volatility of the three Asia-Pacific stock markets, namely India, Australia and Hong Kong. To examine the in-sample information content, the conditional variance equations of GARCH family models are augmented by incorporating implied volatility index as an explanatory variable. The return-based realized variance and the range-based realized variance constructed from 5-min data are used as proxy for latent volatility. To assess the out-of-sample forecast performance, we generate one-day-ahead rolling forecasts and employ the Mincer–Zarnowitz regression and encompassing regression. We find that the inclusion of implied volatility index in the conditional variance equation of GARCH family model reduces volatility persistence and improves model fitness. The significant and positive coefficient of implied volatility index in the augmented GARCH family models suggests that it contains relevant information in describing the volatility process. The study finds that volatility index is a biased forecast but possesses relevant information in explaining future realized volatility. The results of encompassing regression suggest that implied volatility index contains additional information relevant for forecasting stock market volatility beyond the information contained in the GARCH family model forecasts. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekonomik Yorumlar is the property of Journal of Financial Politic & Economic Reviews / Finans Politik & Ekomomik Yorumlar and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper studies goodness-of-fit tests and specification tests for an extension of the Log-GARCH model, which is both asymmetric and stable by scaling. A Lagrange-multiplier test is derived for testing the extended Log-GARCH against more general formulations taking the form of combinations of Log-GARCH and exponential GARCH (EGARCH). The null assumption of an EGARCH is also tested. Portmanteau goodness-of-fit tests are developed for the extended Log-GARCH. An application to real financial data is proposed. [ABSTRACT FROM AUTHOR]

Copyright of Amity Global Business Review is the property of Amity International Business School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The rate of information flow into the market in generating market volatility has been a much debated issue in the finance research. Moreover, since the rate of information cannot be directly observable and quantifiable, trading volume has been considered to be a good proxy for incorporating such information. The mixture of distribution hypothesis (MDH) and the sequential information hypothesis (SIAH) provide the theoretical justification for the relationship between trading volume and market volatility. This paper revisits the relationship between equity trading volume and returns volatility for the Johannesburg Stock Exchange (JSE) of South Africa using daily data over the period of 6th July 2006 to 31st August 2016. Further, it analyzed an after-crisis period, i.e., 1/04/2008 to 8/31/2016, in order to verify the findings. EGARCH and Granger causality models are employed to analyze the volume-volatility relationship. Also the level of volatility persistence has been compared before and after the inclusion of trading volume in the volatility model as an exogenous variable. The analysis shows that the JSE exhibits volatility asymmetry implying that the return volatility responds more to the bad news than to the good news. The relationship between trading volume and market volatility is found to be positive and contemporaneous supporting the MDH. This study also uncover that the volatility persistence remains high even after the inclusion of trading volume as an explanatory variable in the volatility model. The above set of results also holds for the post-crisis sub-sample. Furthermore, the pairwise Granger causality tests indicate a feedback relationship between volume and volatility only in the case of the sub-sample. But for the full sample, a unidirectional causality between volume and volatility, with trading volume Granger causes market volatility was observed. As it was observed that there is a positive and contemporaneous relationship between volatility, and also that the trading volumes cannot attenuate the level of volatility persistence, findings advise the equity market participants to be cautious in their trading behavior; and through messages to the regulators that risk management practice should be strengthened in order to control for market volatility that associated with increasing trading volume. [ABSTRACT FROM AUTHOR]

We propose an ARMA-based quasi-maximum likelihood estimator for loggeneralized autoregressive conditional heteroscedasticity (GARCH) models that is efficient when the conditional error is normal, and prove its consistency and asymptotic normality under mild assumptions. A study of efficiency shows the estimator can provide major improvements, both asymptotically and in finite samples. Next, two empirical applications illustrate the usefulness of our estimator. The first shows how it can be used to obtain volatility estimates in the presence of zeros, that is, inliers, since ARMA-based log-GARCH estimators enable a practical and straightforward solution to the inlier problem—even when the zero-generating process is non-stationary. Our study shows volatility estimates can be substantially underestimated if zeros are not handled appropriately. In our second empirical application, we show how our estimator can readily be used to model high-order volatility dynamics where one or more squared error autocorrelations are negative, a characteristic that is not compatible with ordinary (i.e., non-exponential) GARCH models. [ABSTRACT FROM AUTHOR]

This research paper analyses the price discovery aspects of future market in trading of four prominent spices selected based on their appraisal since 2010 across dimensions like consistent growth in production, area under cultivation, competitive pricing and volume of export. It tries to explore different angles of price volatility in futures market and its influence if any on spot market when being traded on NCDEX. The study uses co-integration technique and tries to establish the spot-futures relationship using Vector Error Correction Model (VECM) characterized by EGARCH frame work. To study the price discovery process, we have used daily closing prices data with the lag of 2 as per Schwartz Information Criteria (SIC) of four spice commodities such as Chilly, Cumin, Coriander and Turmeric were opted. The empirical research revealed the existence of long-term equilibrium relationship between the spot and futures prices of all commodity spices, with the futures leading the spot. In the short run, spot returns to have a stronger impact on the futures returns in most of the commodities spices. [ABSTRACT FROM AUTHOR]

Using annual data over forty years from 1975 to 2014, this study investigates the gross domestic product (GDP) growth and the conditional volatility of foreign direct investment (FDI) in the Indian subcontinent. The study reports the rising trends of both FDI and GDP and documents that the greater-than-expected FDI due to innovative shocks or policy innovations positively influences conditional volatility of FDI which, in turn, positively contributes to the economic growth/development. The conditional volatility used in the study is the variance derived from the diagnostically selected exponential GARCH ( EGARCH) model. The study also reports the causality of both the FDI and its volatility across borders. More specifically, it reports bidirectional causality of FDI between India and Pakistan but unidirectional causality from Bangladesh to both India and Pakistan. It further documents that this volatility is persistent in all the economies and that it spillovers from both India and Pakistan to Bangladesh. The evidence attributes the economic development in the Indian subcontinent to the economic or policy innovations in attracting FDI. The findings of this study thus contribute to the literature by documenting the contrasting evidence that the volatility along with the trend of FDI contributes to the economic development and by reconciling the contrasting evidence. [ABSTRACT FROM AUTHOR]

For many developing countries, historical inflation figures are rarely available. We propose a simple method that aims to recover such figures of inflation using prices of postage stamps issued in earlier years. We illustrate our method for Suriname, where annual inflation rates are available for 1961 until 2015, and where fluctuations in inflation rates are prominent. We estimate the inflation rates for the sample 1873 to 1960. Our main finding is that high inflation periods usually last no longer than 2 or 3 years. An Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) model for the recent sample and for the full sample with the recovered inflation rates shows the relevance of adding the recovered data. [ABSTRACT FROM AUTHOR]