Intraday volatility and periodicity in the Malaysian stock returns

Many empirical studies using high-frequency intraday data from a variety of markets indicate that PGARCH models give superior return volatility forecasts than those produced from standard GARCH models. This paper investigates into modelling approaches of four versions of PGARCH models of high-frequency data of Bursa Malaysia, in particular where the intraday volatility of double U-shaped pattern. It is examined through half-hourly dummy variables, quarterly-hourly dummy variables, Fourier Functional Form (FFF) based variables and spline-based variables. The non-periodic GARCH models, i.e., GARCH, EGARCH and TARCH are used for comparison of performance of best fit. The analysis show that among the four versions of PGARCH models, the half-dummy and the spline-based versions perform the best. EGARCH produced consistently superior results to other GARCH specifications.     

Conditional volatility persistence and volatility spillovers in the foreign exchange market

I investigate the magnitudes and determinants of volatility spillovers in the foreign exchange (FX) market, using realized measures of volatility and heterogeneous autoregressive (HAR) models. I confirm both meteor shower effects (i.e., inter-regional volatility spillovers) and heat wave effects (i.e., intra-regional volatility spillovers) in the FX market. Furthermore, I find that conditional volatility persistence is the dominant channel linking the changing market states of each region to future volatility and its spillovers. Market state variables contribute to more than half of the explanatory power in predicting conditional volatility persistence, with the model that calibrates volatility persistence and spillovers conditionally on market states performing statistically and economically better. The utilization of market state variables significantly extends our understanding of the economic mechanisms of volatility persistence and spillovers and sheds new light on econometric techniques for volatility modeling and forecasting.     

Return and volatility spillovers between currency and bond markets in India

This paper examines the return and volatility spillovers between the foreign exchange and bond markets of India using a bivariate asymmetric BEKK-GARCH (1,1) model for the period 4 April 2005 to 31 March 2017. We find the evidence of bidirectional return and volatility spillovers with asymmetric effects between these two markets. The spillovers are evidenced even during the periods when foreign portfolio investments in the Indian bond markets were relatively low suggests the existence of strong inter-linkages between both the markets.     

Testing for volatility spillover between the British pound and the euro

This paper examines volatility spillover between two nominal U.S. dollar exchange rates: the British pound and the euro. Using the residual cross-correlation approach, we observe that the euro Granger-causes the British pound in variance, whereas the British pound does not Granger-cause the euro in variance. Our findings support unidirectional volatility spillover from the euro to the British pound; thus, the euro volatility has a one-sided impact on the British pound volatility. Moreover, the findings suggest that euro traders succeed in the efficient processing of information derived from the British pound.     

Financial crises and the dynamics of the spillovers between the U.S. and BRICS stock markets

We examine the spillover dynamics between the U.S. and BRICS stock markets using the multivariate DECO-GJR-GARCH model and spillover index method. We identify time variations in volatility equicorrelation and significant dynamic spillovers between these stock markets, as well as an increased impact of uncertainty on spillovers. Spillovers between markets intensify after the inception of the global financial crisis and subsequent European sovereign debt crisis. We also find, following the commencement of the crisis periods, that the U.S., Brazilian, and Chinese markets are net volatility transmitters, whereas the Russian, Indian, and South African markets are net recipients. These results shed new light on the information transmission channels between the U.S. and BRICS stock markets.     

Price and volatility spillovers between exchange rates and stock indexes for the pre- and post-euro period

In this paper we explore the nature of the mean, volatility and causality transmission mechanism between stock and foreign exchange markets for the United States and some major European markets for the periods pre- and post-euro. The asymmetric volatility transmission is described by an extended Multivariate Exponential Generalized Autoregressive Conditionally Heteroskedastic (EGARCH) model. The results support the asymmetric and long-range persistence volatility spillover effect and show strong evidence of causality in the mean and variance between foreign exchange rate and stock price for both pre- and post-euro periods. However, the stock price has a more significant effect on foreign exchange rate for the two subsamples. These results are robust to the cross-correlation function test suggested by Cheung and Ng. The implication is particularly important for international portfolio managers when devising hedging and diversification strategies for their portfolios.     

Trading volume and stock market volatility: The Polish case

Relying on the mixture of distributions hypothesis (MDH), this paper investigates the relationship between daily returns and trading volume for 20 Polish stocks. Our empirical results show that in the majority of cases volatility persistence tends to disappear when trading volume is included in the conditional variance equation, which is in agreement with the findings of studies on developed stock markets. However, we cannot confirm the testable implications of the MDH in all cases, which indicates that future research on the causes and modeling of Polish stock market volatility is necessary.     

Cross‐market spillovers with ‘volatility surprise’

This article adopts the asymmetric DCC with one exogenous variable (ADCCX) model developed by Vargas (2008), by updating the concept of ‘volatility surprise’ to capture cross-market relationships. Current methods for measuring spillovers do not focus on volatility interactions, and neglect cross-effects between the conditional variances. This paper aims to fill this gap. The dataset includes four aggregate indices representing equities, bonds, foreign exchange rates and commodities from 1983 to 2013. The results provide strong evidence of spillover effects coming from the ‘volatility surprise’ component across markets. Against the background of the recent financial crisis, the aim is to contribute to the literature on the interdependencies of financial markets, both in conditional means and (co)variances. In addition, asset management implications are derived.     

The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises

This paper examines return and volatility spillovers between the Turkish stock market with international stock, exchange rate and commodity markets. Our aim is not only to examine spillover behaviour with a large emerging market but also to examine cross—asset spillovers and how they vary across two periods of financial market crisis; the dotcom crash and the liquidity-induced financial crisis. This is to be compared with existing work that typically focuses on industrialised countries or single asset markets only. Using the spillover index methodology we uncover an interesting distinction between these two periods of markets stress. Over the dotcom period spillovers are largely between the same asset class, notably two exchange rate series and two international stock markets series. However, in the period including the financial crisis, spillovers both increase and cross asset types and suggest a much greater degree of market interdependence. Understanding this changing nature in spillovers is key for investors, regulators and academics involved in theoretical model development.     

The euro and pound volatility dynamics: An investigation from conditional jump process

This paper investigates the variations of the volatility of euro and pound after the introduction of euro. A GARJI model is employed to analyze the impact of the news arrivals on the exchange rate volatility. The results are robust to the data-splitting schemes and indicate: (1) the conditional variance of euro is larger than that of pound. (2) The stability of euro exchange rates has made progress in recent years, which is accomplished by the decreases in the jump innovations. This paper supports the arguments on the determinants of exchange rate stability claimed by Mundell (1998) and Mussa (2000).     

R&D, knowledge spillovers and stock volatility

Firms improve their know‐how not only by innovations (producing new knowledge), but also by knowledge spillovers (learning from others). The objective of this study is to test for two major hypotheses developed from a theoretical model explaining the relationship between R&D, knowledge spillovers and stock volatility. Analytically, the model suggests that asymmetric information caused by R&D activities with uncertain future output increases stock volatility, even though dividends and consumptions remain unchanged. However, interfirm knowledge spillovers have a negative impact on stock volatility by reducing the degree of asymmetric information. Both hypotheses are supported by empirical evidence from this study.     

The determination and international transmission of stock market volatility

This paper extends the literature on low-frequency analysis of the causes and transmission of stock market volatility. It uses end-monthly data on stock market returns, interest rates, exchange rates, inflation, and industrial production for five countries (Britain, France, Germany, Japan, and the US) from July 1973 to December 1994. Efficient portfolios of world, European, and Japanese/US equity are first constructed, the existence of multivariate cointegrating relationships between them is demonstrated, and the transmission of conditional volatility between them is described. The transmission of conditional volatility from world equity markets and national business cycle variables to national stock markets is then modeled. Among the main findings are: first, world equity market volatility is caused mostly by volatility in Japanese/US markets and transmitted to European markets, and second, changes in the volatility of inflation are associated with changes of the opposite sign in stock market volatility in all markets where a significant effect is found to exist. To the extent that the volatility of inflation is positively related to its level, this implies that low inflation tends to be associated with high stock market volatility.     

Structural effects and spillovers in HSIF, HSI and S&P500 volatility

We adopt a BEKK-GARCH framework and employ a systematic approach to jointly examine structural breaks in the Hong Kong cash index and index futures volatility and volatility spillovers from the S&P 500 cash and futures. Multiple switching dummy variables are included in the variance equations to test for any structural changes in the autoregressive volatility structure due to the events that have taken place in the Hong Kong market. Abolishment of the up-tick rule, increase of initial margins and electronic trading of the Hang Seng Index Futures (HSIF) are found to have significant impact when US market spillovers are excluded from a restricted model. Volatility spillovers from the US market are found to have a significant impact and account for some mis-specification in the restricted model.     

The impact of industrial incidents on stock market volatility

We examine stock market volatility attributed to industrial incidents involving publicly traded US companies, with contributing factors identified as company violations and safety errors, equipment failure, human error and vandalism. Incidents identified as safety violations elicited the highest costs in terms of equity price reductions, but the volatility effects of these incidents tend to mitigate within two weeks. Incidents caused by vandalism experience the sharpest volatility increases, but reduce within two days. Volatility associated with incidents caused by equipment failure tends to persist for almost four weeks. Injuries cost publicly traded companies $14 million each while fatalities lead to equity market capitalisation reductions of between $465 and $720 million. These results shed light on the equity market's role as a driver for enhanced compliance with health and safety regulation and with industry good practice.     

The influence of intraday seasonality on volatility transmission pattern

Using data on a five-minute interval basis, this article analyses the effects of intraday seasonality on volatility transmission between the spot and futures markets of the CAC40, DAX30 and FTSE100. Remarkable differences in the impulse response analysis and in the dynamic and directional measurement of volatility spillovers are encountered depending on whether the intraday periodic component is considered. Thus, the convenience of removing intraday seasonality seems to be critical to reduce the risk of spurious causality when employing high-frequency data in volatility transmission. Moreover, the impact of market microstructure noise seems negligible when using an optimal frequency of observations.     

Oil price shocks and volatility spillovers in the Nigerian sovereign bond market

This paper investigates volatility spillover in the Nigerian sovereign bond market arising from oil price shocks, using Vector Autoregressive Moving Average ‐ Asymmetric Generalized Autoregressive Conditional Heteroscedasticity (VARMA‐AGARCH) model. The paper covers the period March 22, 2011 to April 14, 2016 and makes use of the daily data of the Nigerian Sovereign Bond, Brent oil and West Texas Intermediate (WTI), respectively. We endogenously and sequentially detect structural break points using the test of Bai and Perron (2003) framework. In order to accurately estimate the model, we modify it by incorporating the break points into the VARMA‐AGARCH model, a process which if ignored would lead to model misspecification. The results obtained demonstrate a significant cross‐market volatility transmission between oil and sovereign bond market with ample sensitivity to structural breaks. The study also computes optimum weight portfolio and hedge ratio both with and without structural breaks and results equally indicate sensitivity to structural breaks.     

A neural network enhanced volatility component model

Volatility prediction, a central issue in financial econometrics, attracts increasing attention in the data science literature as advances in computational methods enable us to develop models with great forecasting precision. In this paper, we draw upon both strands of the literature and develop a novel two-component volatility model. The realized volatility is decomposed by a nonparametric filter into long- and short-run components, which are modeled by an artificial neural network and an ARMA process, respectively. We use intraday data on four major exchange rates and a Chinese stock index to construct daily realized volatility and perform out-of-sample evaluation of volatility forecasts generated by our model and well-established alternatives. Empirical results show that our model outperforms alternative models across all statistical metrics and over different forecasting horizons. Furthermore, volatility forecasts from our model offer economic gain to a mean-variance utility investor with higher portfolio returns and Sharpe ratio.     

An investigation of return and volatility linkages among equity markets: A study of selected European and emerging countries

This paper investigates the linkages among equity returns (based on exchange traded funds, ETF) and transmission of volatilities in the following countries: Germany, Austria, Poland, Russia and Turkey. Multivariate Autoregressive Moving Averages (MARMA) and the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) methodologies are utilized. The findings include the existence of significant co-movement of returns among countries in the sample. Also, Turkish and Russian markets were found to be more volatile than Austria, Germany and Poland. However, volatilities in Russia and Turkey do not persist very long. Finally, there is strong evidence of volatility spillovers. All of the countries in the sample, with the exception of Turkey, experience volatility spillovers from other markets. The presence of spillovers among return series and persistence of volatilities are useful to investors interested in diversifying their portfolios and to traders/fund managers who are interested in maximizing returns.     

Forecasting stock market volatility and the informational efficiency of the DAX-index options market

Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated to determine if they are more appropriate for predicting future return volatility. Employing German DAX-index return data it is found that past returns do not contain useful information beyond the volatility expectations already reflected in option prices. This supports the efficient market hypothesis for the DAX-index options market.     

Day of the week effect on foreign exchange market volatility: Evidence from Turkey

This paper assesses the day of the week effect of the daily depreciation of the Turkish lira (TL) against the US dollar (USD) and its volatility. The empirical evidence from Turkey presented here suggests that Thursdays are associated with higher and Mondays with lower depreciation rates compared to those of Wednesdays. Moreover, Mondays and Tuesdays are associated with higher volatility than Wednesdays.