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The paper aimed at modelling the density of inflation based on time-varying conditional variance, skewness and kurtosis model developed by Leon, Rubio, and Serna (2005) who model higher-order moments as GARCH-type processes by applying a Gram-Charlier series expansion of the normal density function. Additionally, it extended their work by allowing both conditional skewness and kurtosis to have an asymmetry term. The results revealed the significant persistence in conditional variance, skewness and kurtosis which indicate high asymmetry of inflation. Additionally, diagnostic tests reveal that models with nonconstant volatility, skewness and kurtosis are superior to models that keep them invariant. JEL Classification: C13, E31, E37.

As time‐varying volatility has found applications in roughly all time series modelling in economics, it largely draws attention in the areas of financial markets. This study also examines the characteristics of conditional volatility in the Baltic Stock Markets (Estonia, Latvia and Lithuania) by using a broad range of GARCH volatility models. Correctly forecasting the volatility leads to better understanding and managing financial market risk. Daily returns from four Baltic stock indexes are used; Estonia (TALSE index), Latvia (RIGSE index), Lithuania (VILSE index) and synthetic BALTIC benchmark index. We test a large family of GARCH models, including; the basic GARCH model, GARCH‐in‐mean model, asymmetric exponential GARCH and GJR GARCH, power GARCH and component GARCH model. We find strong evidence that daily returns from Baltic Stock Markets can be successfully modelled by GARCH‐type models. For all Baltic markets, we conclude that increased risk will not necessarily lead to a rise in the returns. All of the analysed indexes exhibit complex time series characteristics involving asymmetry, long tails and complex autoregression in the returns. Results from this study are firmly recommended to financial officers and international investors. Santrauka Straipsnyje analizuojamas salyginis Baltijos vertybiniu popieriu rinku (Estijos, Latvijos ir Lietuvos) nepastovumas, taikant eile GARCH kintamumo modeliu. Pažymetina, kad tinkamai prognozuojant nepastovuma, galima geriau suvokti ir valdyti finansiniu rinku rizika. Straipsnyje remiamasi keturiu Baltijos šaliu kasdienemis akciju indeksu gražomis; Estijos (TALSE indeksu), Latvijos (RIGSE indeksu), Lietuvos (VILSE indeksu) ir sintetiniu palyginamuoju BALTIC indeksu. Pritaikius eile GARCH kintamumo modeliu, galima teigti, kad didejanti rizika Baltijos šaliu rinkose nebūtinai itakos vertybiniu popieriu gražos augima. Tyrimo metu gauti rezultatai rekomenduojami finansu specialistams ir investuotojams. First Published Online: 10 Feb 2011 Reikšminiai žodžiai: Baltijos vertybiniu popieriu rinkos, salyginis nepastovumas, GARCH modeliai, finansine rizika, graža

• The paper analyzes whether COVID-19 forecasts volatility returns. • It is based on a set of five cryptocurrencies. • It uses asymmetric GARCH models. • The results show that the COVID-19 exerts a positive effect on returns volatility. • The models with COVID-19 variables improve forecasting performance. This paper analyzes the role of COVID-19 pandemic crisis in determining and forecasting conditional volatility returns for a set of eight cryptocurrencies through an asymmetric GARCH modeling approach. The findings report that the COVID-19 pandemic exerts a positive effect on the conditional volatility of those returns, while explicitly considering the pandemic event improves volatility predictions. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the performance of parametric ARCH class models to forecast out-of-sample VaR for two portfolios of Tehran Stock Exchange (TSE) companies (Market portfolio and a portfolio of 50 liquid companies), using a number of distributional assumptions and sample sizes at low and high confidence levels. We find, first, that leptokurtic distributions are able to produce better oneday- ahead and 10-day-ahead VaR forecasts; second, the choice of sample size is important for the accuracy of the forecasts.

Present study analyzes the impact of futures trading on cash market volatility and information dissemination efficiency both on index as well as individual stocks trading at National Stock Exchange of India. Surrogate index has been used to control the impact of other market reforms introduced in India. Returns in the cash market have been observed to be asymmetric in nature and it has been found that after introduction of futures trading in the Indian capital market, cash market volatility has decreased. It has also been found that although information assimilation efficiency in the cash market after introducing futures trading remains inefficient but the role of new information in the price discovery process has increased. Furthermore, it has been observed that both volatility and daily returns are different across various trading days of the week but both returns and volatility are highly significant around the settlement day of the futures contracts. [ABSTRACT FROM AUTHOR]

When global crisis struck at a time of great global and regional interdependence, contagion occurs; it can work via capital flows or through spillovers of the returns/yields on financial assets. The analysis in the paper deals with the latter. Focusing on the shocks in the United States and Eurozone bonds market, and using multivariate GARCH models with conditional variance-covariance matrix being positive definite, it is shown that the shock and volatility spillovers in some emerging Asian countries are quite significant. They spread throughout different asset classes, threatening the region's financial stability, and making it more difficult for the policy response to focus on a particular market. Although local bonds volatilities are more determined by their own respective shocks and volatilities, in some markets the direct shock and volatility spillovers remain significant; so does the indirect spillovers within domestic asset markets and across economies. Absent of policy coordination within and across countries. Such undesirable spillovers due to other country's unilateral policy can be damaging. Growing financial nationalism in the midst of a crisis is likely to spark strong reactions from affected countries, potentially creating a conflict situation. [ABSTRACT FROM AUTHOR]

Abstract: We examine empirical evidence of the behavior of stocks and bonds from BRIC nations by using daily data from January 2003 to July 2010. We present unconditional and conditional empirical results depending upon a simple measure of U.S. financial stress. In the long term, BRIC bond markets deviate much more from the U.S. financial stress measure than the BRIC bonds and stocks that deviate among themselves. Stock and bond return correlations for Brazil and Russia are significantly large and negative. The own correlations are more important in determining the evolution of the conditional correlations relative to unexpected news. Dynamic conditional correlations between stock returns, bond returns and U.S. financial stress increase after the Lehman Brothers'' event in September 2008, except for the bond returns in India. [Copyright &y& Elsevier]

This paper has two central aims. The first one is to deal empirically with the effects of financial crises on emerging stock markets volatility. The second objective consists in testing if the level of stock market development affects this relationship. For this purpose, we estimate a static panel data model for a sample of nine emerging economies from January 1990 to December 2006. We consider three types of financial crises, i.e. banking, currency and twin crises. Our empirical results suggest that the onset of financial crises strongly increased stock market volatility. In addition, we find that the biggest impact is exerted by twin crises. When dealing with the second objective, our results show that the market size and the liquidity level can attenuate the effects of banking and currency crises, but not the one associated to twin crises. Nevertheless, the degree of stock market integration seems to reduce the effects of banking, currency and twin crises on stock market volatility. [ABSTRACT FROM AUTHOR]

China's railway is an important component of logistics transportation to promote the rapid development of modern logistics. It also facilitates the growth of economy. How to improve the efficiency of railway freight is becoming a crucial issue for the development of modern logistics. This paper uses symmetric and asymmetric conditional volatility models, GARCH (1, 1), GJR-GARCH (1, 1) and EGARCH (1, 1), to estimate the volatility in monthly railway freight volume. The volatility estimated results indicate that it has an asymmetric effect on risk from positive and negative shocks of equal magnitude. Moreover, there is a leverage effect in the monthly growth rate of railway freight volume, whereby negative shocks increase volatility but positive shocks of very similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics are also applicable to railway freight volume. Volatility experienced by logistics transportation industry has significant implications for capital investment, resource allocation and yield management. The empirical findings of this paper provide useful insights which can be expected to be of interest to the private and public sectors in the formulation of logistic management policy especially on railway transportation. [ABSTRACT FROM AUTHOR]

We construct an inflation-targeting index for a group of seven Organization for Economic Co-operation and Development (OECD) countries that ranks countries according to the key features of formal inflation targeting regimes. The relationship between this index and bond markets is empirically examined to investigate whether inflation targeting reduces the mean of the conditional volatility of the difference between actual yields and those predicted by the expectations hypothesis. We find that the adoption of a more stringent inflation-targeting regime is generally associated with a statistically significant drop in conditional volatility, suggesting that inflation targeting reduces noise in bond markets. [ABSTRACT FROM AUTHOR]

This study investigates the effect of sporting performances on the volatility of listed football clubs. The theoretical background is based on the importance of intangible assets in the football industry and the difficulty in evaluating them. The empirical analysis is based on the family of autoregressive conditional heteroskedasticity (ARCH) models and relates to a sample of football clubs listed on the Alternative Investment Market (AIM) and included in the Dow Jones STOXX Football Index. The findings show that sporting performances have a significant impact on the volatility of listed football clubs. The magnitude of the market reaction depends on the result nature (defeat, draw, or win) and the match venue (home or away). This study fills a gap in the empirical literature by providing a level of analysis unmatched by previous research. Thus, it should be of interest to academics as well as investors in better understanding and evaluating the volatility movements of listed football clubs. [ABSTRACT FROM AUTHOR]

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Abstract: The objective of this paper is to explore whether lagged trading activity in one market contributes to the return and volatility process in other markets, using 5-min concurrent data from German and British equity market. Our results lend support to our initial premise that if international investors have access to the same information set as domestic traders, then after observing foreign trading activity, market makers adjust prices to reflect their expectation of the security value, conditional upon all available information, including prior trades. Our findings clearly indicate that intraday trading volume contains predictive power for cross-border return and volatility processes. Moreover, these volume effects are found to be asymmetric in the sense that the impact of positive volume changes upon foreign stock market volatility is greater than is the impact of negative changes. [Copyright &y& Elsevier]

We examine the dynamics and transmission of conditional volatilities with multiple structural changes in return volatility using Bai and Perron ()'s methodology, across five major securitized real estate markets as well as employing a multivariate regime-dependent asymmetric dynamic covariance methodology (MRDADC) that allows the conditional matrix to be both time- and state-varying. Our results imply that a multiple-regime time varying asymmetric variance and covariance approach is important in modeling real estate securities valuation and selection and portfolio optimization, and is consistent with popular beliefs that market volatility changes over time. Our MRDADC models detect the presence of significant mean-volatility linkages across the five major securitized real estate markets under different volatility regimes and would have implications for global investor in terms of estimating a dynamic risk-minimizing hedge ratio in international portfolio management. [ABSTRACT FROM AUTHOR]

Using a data set consisting of more than five years of 5-minute intraday stock index returns for major European stock indices and US macroeconomic surprises, conditional means and volatility behaviour in European markets were investigated. The findings suggest that the opening of the US stock market significantly raises the level of volatility in Europe, all markets responding in an identical fashion. Furthermore, US macroeconomic surprises exert an immediate and major impact on both the European stock markets' intraday returns and volatilities. Thus, high frequency data appear to be critical for the identification of news impacting the markets. [ABSTRACT FROM AUTHOR]

This paper examines the risk-return relationship in Indian stock market using symmetric and asymmetric GARCH-in-mean (GARCH-M) models. First the standard GARCH-M model is used, next since variance is proxy for risk, we ascertain if there is any significant relation between asymmetric variance and return using TGARCH-M, EGARCH-M and Power GARCH models. The study uses daily data on popular index S&P CNX Nifty of National Stock Exchange, India, during a period of two decades from July, 1990 to November, 2010. Further the period of Asian crisis is covered during the pre-derivative period of a decade and sub-prime crisis is covered during the post-derivative period of a decade to see the behaviour of volatility and risk-return relationship. The results show that both the TGARCH-M and PGARCH-M models are good for Indian market conditions. The asymmetric models find strong evidence of time-varying, highly persistent and predictable volatility in Indian market. It establishes that return is positively related to risk in Indian market during all periods. The risk-return relationship is positive and significant only at higher lags that too in the presence of dummyfut (variable which takes value 1 after derivatives and 0 before it). Further during sub-period analysis we find that risk-return parameter is higher in magnitude in pre-derivative period compared to post-derivative period. In both periods both the crisis had negative effect on return and positive effect on volatility. The rise in volatility during Sub-prime crisis is sharper compared to during Asian crisis. The findings are useful for financial decision making. [ABSTRACT FROM AUTHOR]

This article studies the performance of the national stock markets of 16 European countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Holland, Ireland, Italy, Norway, Portugal, Spain, Sweden, Switzerland and the UK), using daily data covering the period between 2 January 2001 and 30 May 2009. Daily expected returns, and the conditional volatility of each index, were calculated using a model combining the market model and an implicit long-term relation between the index prices. Finally, time-varying (conditional) Sharpe ratios were calculated for each index. These were used as the basis for a statistical comparison of the performance of the stock indexes of this group of countries, throughout different sub-periods corresponding to different conditions (of expansion and depression) in the stock markets. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Business Economics & Management is the property of Vilnius Gediminas Technical University 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.)

Abstract: Recently, Pelletier [2006. Journal of Econometrics 131, 445–473] proposed a model for dynamic correlations based on the idea to combine standard GARCH models for the volatilities with a Markov-switching process for the conditional correlations. In this paper, several properties of the model are derived. First, we provide a simple recursion for multi-step covariance forecasts under both Gaussian and Student’s t innovations, which is much simpler to implement than the formula presented by for normally distributed errors. Second, we derive expressions for the unconditional covariances and correlations and the cross correlation function of the absolute returns. An application to returns of international stock and real estate markets shows that correlations between these asset classes increased substantially during the recent financial turmoil; moreover, in the regime–switching framework, employing a Student’s t distribution improves the forecasting performance the Gaussian. [Copyright &y& Elsevier]

As U.S. Treasury securities carry the full faith and credit of the U.S. government, they are free of default risk. Thus, their yields are risk-free rates of return, which allows the most recently issued U.S. Treasury securities to be used as a benchmark to price other fixed-income instruments. This article analyzes the time series properties of interest rates on U.S. Treasury benchmarks and related debt instruments by modelling the conditional mean and conditional volatility for weekly yields on 12 Treasury Bills and other debt instruments for the period January 8, 1982 to August 20, 2004. The conditional correlations between all pairs of debt instruments are also calculated. These estimates are of interest as they enable an assessment of the implications of modelling conditional volatility on forecasting performance. The estimated conditional correlation coefficients indicate whether there is specialization, diversification, or independence in the debt instrument shocks. Constant conditional correlation estimates of the standardized shocks indicate that the shocks to the first differences in the debt instrument yields are generally high and always positively correlated. In general, the primary purpose in holding a portfolio of Treasury Bills and other debt instruments should be to specialize on instruments that provide the largest returns. Tests for Stochastic Dominance are generally consistent with these findings, but find somewhat surprising rankings between debt instruments, with implications for portfolio composition. Thirty year treasuries, Aaa bonds, and mortgages tend to dominate the other instruments, at least to the second order. [ABSTRACT FROM AUTHOR]

Various univariate and multivariate models of volatility have been used to evaluate market risk, asymmetric shocks, thresholds, leverage effects, and Value-at-Risk in economics and finance. This article is concerned with market risk, and develops a constant conditional correlation vector ARMA-asymmetric GARCH (VARMA-AGARCH) model, as an extension of the widely used univariate asymmetric (or threshold) GJR model of Glosten et al. (1992), and establishes its underlying structure, including the unique, strictly stationary, and ergodic solution of the model, its causal expansion, and convenient sufficient conditions for the existence of moments. Alternative empirically verifiable sufficient conditions for the consistency and asymptotic normality of the quasi-maximum likelihood estimator are established under non-normality of the standardized shocks. [ABSTRACT FROM AUTHOR]

This paper models daily air passenger arrivals and their volatility for the Balearic and Canary Islands, Spain. Due to climatic conditions, tourism seasonality is clear in the Balearics, with an increasing number of arrivals during the winter months. In the Canary Islands, the seasonal pattern is different, with decreasing numbers in recent years. Three univariate conditional volatility models are estimated for both the Balearics and the Canaries, concentrating on empirical issues relating to short- and long-run persistence, as well as the symmetric and asymmetric effects of positive and negative shocks of equal magnitude on volatility. [ABSTRACT FROM AUTHOR]

Using returns of 4,916 stocks from 22 developed countries and 15 developing countries, this study examines the relative magnitude of conditional volatility and the international market systematic risk of stock prices in countries at different developmental stages and in various geographical areas. Consistent with the finding of Bekaert et al. (2008), the results of non-parametric Mann-Whitney tests suggest that the stock prices in emerging markets are riskier than the ones in developed countries, measured by both conditional volatility and global beta. Our empirical findings also support the geographical variation in stock risks. Specifically, the equity values in Southeast Asia, South Europe, and Latin America are more volatile than the rest of the world. Similar results can be found in the country-level tests. The time-series analysis suggests that the stock returns in high risk countries tend to be less volatile but the conditional volatility of stock return in less risky countries leans to increase. [ABSTRACT FROM AUTHOR]

This paper analyzes empirically the relationship between money market uncertainty and unexpected deviations in retail interest rates in a sample of ten OECD countries. We find that, with the exception of the United States, money market uncertainty has only a modest impact on the conditional volatility of retail interest rates. Even for the United States, we find that the effects of money market uncertainty are spread out over time. Our results also indicate that money market uncertainty tends to be passed on to retail rates to a lesser extent in countries where banking relationships play a substantial role. [ABSTRACT FROM AUTHOR]

The diversifying power of inflation-linked (IL) bonds relative to traditional asset classes has changed significantly. In this paper, we study the dynamics of conditional volatilities and correlations for three asset classes, IL bonds, nominal bonds and equities, in the USA and Europe. Using a DCC-MVGARCH for the period 1997–2007, we highlight the change that took place in 2003. Although IL bonds once had definite diversification power, they are now highly correlated with nominal bonds and have reached similar volatility levels. As a result, the two asset classes are practically substitutable. This seems to be due to more stable inflation expectations and to a more liquid IL bond market. Although diversification was a valuable reason for introducing IL bonds in a global portfolio before 2003, this is no longer the case. Dynamic portfolio optimisation using our estimates of conditional correlations and volatilities clearly demonstrates that the optimal weight of IL bonds in a portfolio decreased sharply in 2003 in favour of nominal bonds and equities. [ABSTRACT FROM AUTHOR]

We examine the dynamic behavior of Equity Real Estate Investment Trust (EREIT) volatility in a GARCH context 1972–2006 using monthly EREIT returns, and comparing volatility performance for “early” Equity REITs 1972–1992 with that of “modern” EREITs 1993–2006. Consistent with findings for conventional firms, we find that EREIT conditional volatility is time-varying, persistent, and predictable. There is a positive relationship between expected return and expected risk in EREIT stocks pre-1993, but the relationship disappears after 1993. We find no evidence that negative shocks affect EREIT volatility differently from positive ones in either time period. Different from reported results for conventional firms, we find that changes in the conditional volatility of fundamental macroeconomic variables have strong explanatory value for future changes in EREIT volatility. Finally, comparing EREIT volatility performance with volatility in the Russell 2000 Index, a proxy for small stocks, we find that EREIT volatility behaves differently from that of small stocks in many respects, indicating that risks in the small stock index cannot effectively proxy for risks in the EREIT market. [ABSTRACT FROM AUTHOR]

• We theoretically present the desirable robustness feature of the GAS model • Systematically designed simulation evidence is provided • GAS consistently outperforms the GARCH models when outliers exist • GAS provides more accurate forecasts for the WTI crude oil over 2017-2020 This paper discusses the inherent robustness of the generalized autoregressive score (GAS) model, such that consistent estimators can still be obtained when large outliers do exist. A recent example includes the historical-writing negative price of the West Texas Intermediate (WTI) crude oil future in early-2020. Via simulation studies, we demonstrate that GAS can produce much more robust estimates than the popular GARCH model. Empirical analysis using the WTI returns over 2017–2020 further supports the superiority of GAS over GARCH models. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Economia e Administração is the property of INSPER Instituto de Ensino e Pesquisa 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.)

Jin and Frechette (2004) examined the degree to which agricultural price volatilities exhibited evidence of fractional integration and concluded it was important to consider both long-run and short-run memory when modeling conditional variances. The purpose of this note is to revisit the issue using new methods and techniques which generally reaffirm the view that return volatilities are fractionally integrated and conditionally heteroskedastic, with many exhibiting significant leverage effects, a result not previously reported. [ABSTRACT FROM AUTHOR]

Abstract: A new high frequency data set is used to estimate the impact of the Fed on the level and volatility of stock prices while accounting for endogeneity and omitted variable biases and potential asymmetries. Results show that after addressing these issues, the effect of policy shocks on the level and volatility of stock returns is higher than previously reported. GARCH findings indicate that the volatility impact is tent-shaped, spiking during policy announcements and declining before and after the release. The level and conditional volatility of stock returns is found to respond asymmetrically to the type of policy shocks (timing versus future path of monetary policy) and the type of policy action (easing versus tightening). [Copyright &y& Elsevier]

According to literature, the long-maturity forward rates have information about the structure of the expected short-term returns. This paper finds that the conditional volatility factor also has information for predicting the term premium in the six-month expected returns with different maturities. That is, including conditional volatility allows capturing a risk factor consistent with the agent's expectations. A slow mean-reverting process is also found across different maturities, which is the case of the governmental fixed income securities. In fact, the power of forecasting changes from a six-month to a three-year forward period, at six-month steps according to the mean-reverting tendency which also implied that its predictive power improves at longer forecasting horizons. On the other hand, it presents evidence about the Colombian markets crash in May 2006, which generated special conditions that impacted the market's behavior and the agent's risk tolerance. [ABSTRACT FROM AUTHOR]

This paper studies the volatility implications of the introduction of derivatives on stock market volatility in India using the S&P CNX Nifty Index as a benchmark. To account for non-constant error variance in the return series, a GARCH model is fitted by incorporating futures and options dummy variables in the conditional variance equation. We find clustering and persistence of volatility before and after derivatives, while listing seems to have no stabilisation or destabilisation effects on market volatility. The post-derivatives period shows that the sensitivity of the index returns to market returns and any day-of-the-week effects have disappeared. That is, the nature of the volatility patterns has altered during the post-derivatives period. [ABSTRACT FROM AUTHOR]

Using daily returns on a set of hedge fund indices, we study (i) the properties of the indices' conditional density functions and (ii) the presence of asymmetries in conditional correlations between hedge fund indices and other investments and between hedge fund indices themselves. We use the SNP approach to obtain estimates of conditional densities of hedge fund returns and then proceed to examine their properties. In general, a nonparametric GARCH(1,1) model appears to provide the best fit for all strategies. We find that the conditional third and fourth moments are significantly affected by changes in the current volatility of returns on hedge fund indices. We examine changes in the conditional probability of tail events and report significant changes in the probability of extreme events when the conditioning information changes. These results have important implications for models of hedge fund risk that rely on probability of tail events. We formally test for the presence of asymmetries in conditional correlations to determine if there is contagion between hedge funds and other investments and between various hedge fund indices in extreme down markets versus extreme up markets. We generally do not find strong evidence in support of asymmetric correlations. [ABSTRACT FROM AUTHOR]