Estimation of Asymmetric Stochastic Volatility Models: Application to Daily Average Prices of Energy Products

Energy supply and demand, and as a consequence energy prices, are likely to represent one of the biggest challenges of the 21st century. Commodity markets exhibit increased volatility when there is little or no underutilized supply capability to meet natural fluctuations in demand. In the case of energy markets, the large capital requirements and significant lead times associated with energy production and delivery make them more susceptible to the imbalances in supply capability and demand. Energy price volatility has destructive impact on market agents, and this impact is intensified when the prices exhibit asymmetric volatility. This article pursues two aspects of the issue. First we consider general aspects, especially the asymmetric pattern of volatility of daily returns of different types of energy products. Then, we analyze the behaviour of daily returns by using traditional models of volatility that include AGARCH, TGARCH, EGARCH, and ARSV strategies, as well as a threshold asymmetric autoregressive stochastic volatility (TA-ARSV) model that we propose. The energy products considered in this analysis are probably the most relevant energy products for the economic activity of the nations and the economic relations between countries: Crude Oil (OPEC reference basket and London Brent index), Gasoline, Natural Gas, Butane, and Propane. We use spot prices and the time reference ranges from 1986–1993 to 2009 depending on the product.     

Conditional correlations and volatility spillovers between crude oil and stock index returns

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti, and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC.     

Spillovers and directional predictability between international energy commodities and their implications for optimal portfolio and hedging

This study sheds a new light on the dependence and the directional predictability between eight major energy price returns, using the Cross-Quantilogram (CQ) and the Partial CQ (PCQ) analysis. The energy prices cover the time series for the U.S. natural gas and seven internationally traded crude oil types. The results reveal a significant directional predictability running from most of energy commodities returns to the OPEC basket and the very light Tapis crude oil returns. However, the quantile predictability in both directions is enabled only for the relations between the light Brent and the light WTI, and between the OPEC basket and the Malaysian Tapis. The time-varying predictability analysis reveals that there is a significant upper quantile dependence between these international energy commodities. Finally, we find that the TAPIS can be a good hedging vehicle for other energy markets. These findings may be instructive for both policymakers (in terms of financial stability) and market participants (in terms of performance).     

Co-movement of oil and stock prices in the GCC region: A wavelet analysis

This paper examines the short term and long term dependencies between stock market returns and OPEC basket oil returns for the six Gulf Cooperation Council (GCC) countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) and two non-oil producing countries in the region (Egypt and Jordan), over the period 2002–2011. We utilize the wavelet coherency methodology in our empirical analyses. The empirical evidence indicates lack of market dependencies in the short term in these countries, indicating that oil and stock returns are not strongly linked in this interval. However, we show that oil returns and the stock markets returns co-move over the long term. The results also suggest that the long term dependencies are much stronger for OPEC oil returns and Jordan stock market returns relative to OPEC oil returns and Egypt stock market returns, implying a variation in the dependencies between oil prices and stock markets across countries. We further note an increasing strength in the market dependencies after 2007, signifying enhanced diversification benefit for investors in the short term relative to the long term.     

基于分形理论的原油期货高频交易风险测度研究

为了捕捉原油期货高频波动规律,采用WTI原油期货五分钟数据,基于分形理论分别构建GED分布和Skew-t分布的FIGARCH、FIAPARCH和HYGARCH模型,分析其波动特征并对风险进行测度。结果显示：三种模型均较好地刻画出WTI原油期货波动的长记忆特征;基于Skew-t分布的HYGARCH模型在度量原油期货高频交易风险时尤为精确;多头与空头头寸的VaR呈现非对称性;套期保值者或高频交易者可依据模型预测波动率,防止短期波动率过大导致保证金不足而被强制平仓。高频交易在提高市场流动性和拓宽市场深度方面具有一定的作用,因此,在风险可控的条件下,政府应该鼓励高频交易,促进我国衍生品市场繁荣发展,并增强衍生品市场稳定性和国际竞争力。     

Evidence of information transmission across currency futures markets using frequency domain tests

In this article, I examine the returns and volatility spillovers in the currency futures market incorporating the recently developed frequency domain tests. Such analysis allows differentiating between permanent (long-run) and transitory (short-run) linkages among the currency futures markets by investigating the causality dynamics at low and high frequencies respectively. I detect significant informational linkages between USD, EUR, GBP and JPY futures contracts in the Indian currency futures market. Evidence of innovations from USD futures market to other markets is the most significant for returns spillover and for volatility spillover, EUR is found to be the most significant compared to other currency futures contracts. The results would have implications for the market participants and policymakers.     

Impact of network investor sentiment and news arrival on jumps

This paper studied the influence of news announcements and network investor sentiment on Chinese stock index and index futures market jumps. A machine learning text analysis algorithm was employed to measure investor forum sentiment. It was found that news arrivals were an important reason for jump occurrences, jumps were significantly associated with network investor sentiment, and while occasionally the news and network investor sentiment resulted in simultaneous market jumps, they appeared to be relatively independent. The network investor sentiment time-lag and asymmetric effects were also tested, from which it was found that network investor sentiment had a significant asymmetric effect on the jumps, but time-lag effects had little influence. News announcements and the top 25% of the extreme network sentiments were found to explain more than 50% of the jumps, with extreme sentiments tending to increase the volatility of the news-related jumps and persistently influencing returns after the news-related jumps.     

Oil price uncertainty and movements in the US government bond risk premia

In this paper, we analyze the predictability of the movements of bond premia of US Treasury due to oil price uncertainty over the monthly period 1953:06 to 2016:12. For our purpose, we use a higher order nonparametric causality-in-quantiles framework, which in turn, allows us to test for predictability over the entire conditional distribution of not only bond returns, but also its volatility, by controlling for misspecification due to uncaptured nonlinearity and structural breaks, which we show to exist in our data. We find that oil uncertainty not only predicts (increases) US bond returns, but also its volatility, with the effect on the latter being stronger. In addition, oil uncertainty tends to have a stronger impact on the shortest and longest maturities (2- and 5-year), and relatively weaker impact on bonds with medium-term (3- and 4-year) maturities. Our results are robust to alternative measures of oil market uncertainty and bond market volatility.     

Options and earnings announcements: an empirical study for the European Options Exchange

In this paper we give an introduction in option pricing theory and explicitly specify the Black-Scholes model. Although market participants use this and similar models to price options, they violate one of the fundamental assumptions of the model. They do not set a constant value for the volatility of the underlying asset over time, but change the volatility even during a day. By means of event study methodology we investigate the volatility of the underlying asset and the volatility implicit in option prices around earnings announcements by firms. We find that the volatility in option prices increases before the announcement date and drops sharply afterwards. The volatility of the underlying stocks is higher only at the announcement dates and we do not observe a higher volatility around these dates. Hence, the constant volatility of the underlying asset, which is one of the assumptions in the Black-Scholes model, does not hold. However, the market seems to correctly anticipate the change in volatility, by correcting option prices.     

Dynamic spillover and connectedness between oil futures and European bonds

This paper examines the spillovers and connectedness between crude oil futures and European bond markets (EBMs) having different maturities. We also analyze the hedging effectiveness of crude oil futures-bond portfolios in tranquil and turbulent periods. Using the spillovers index of Diebold and Yilmaz (2012, 2014), we show evidence of time-varying spillovers between markets under investigations, which varies between 65% and 83%. Moreover, three-month, six-month, one-year, three-year and thirty-year bonds and crude oil futures are net receivers of risk from other markets, whereas the remaining bonds are net contributors of risk to the other markets. Crude oil futures receive more risk from long-term than short-term bonds. Moreover, the magnitude of risk transmission is low for the pre-crisis and economic recovery periods. Crude oil futures market contributes significantly to the risk of other markets during the oil crisis and Brexit period. A portfolio risk analysis shows that that most investments should be in oil rather than bonds (except the short-term bonds). The hedge ratio is sensitive to market conditions, where the cost of hedging increases during GFC and ESDC period. Finally, a crude oil futures-bond portfolio offers the best hedging effectiveness during the COVID-19 pandemic period.     

The role of oil futures intraday information on predicting US stock market volatility

This study investigates the role of oil futures price information on forecasting the US stock market volatility using the HAR framework. In-sample results indicate that oil futures intraday information is helpful to increase the predictability. Moreover, compared to the benchmark model, the proposed models improve their predictive ability with the help of oil futures realized volatility. In particular, the multivariate HAR model outperforms the univariate model. Accordingly, considering the contemporaneous connection is useful to predict the US stock market volatility. Furthermore, these findings are consistent across a variety of robust checks.     

Crack spread hedging: accounting for time‐varying volatility spillovers in the energy futures markets

Crude oil, heating oil, and unleaded gasoline futures contracts are simultaneously analysed for their effectiveness in reducing price volatility for an energy trader. A conceptual model is developed for a trader hedging the ‘crack spread’. Various hedge ratio estimation techniques are compared to a Multivariate GARCH model that directly incorporates the time to maturity effect often found in futures markets. Modelling of the time‐variation in hedge ratios via the Multivariate GARCH methodology, and thus taking into account volatility spillovers between markets is shown to result in significant reductions in uncertainty even while accounting for trading costs. Copyright © 2002 John Wiley & Sons, Ltd.     

Sovereign rating changes—Do they provide new information for stock markets?

The purpose of this paper is to examine the impact of sovereign rating changes on international financial markets using a comprehensive database of 42 countries, covering the major regions in the world over the period 1995–2003. In general, we find that rating agencies provide stock and foreign exchange markets with new tradable information. Specifically, rating upgrades (downgrades) significantly increased (decreased) USD denominated stock market returns and decreased (increased) volatility. Whereas the mean response is contributed evenly by the local currency stock returns and exchange rate changes that make up the USD returns, only the foreign exchange volatility was behind the USD denominated return volatility. In addition, we find significant asymmetric effects of rating announcements. The market responses – both return and volatility – are more pronounced in the cases of downgrades, foreign currency debt, emerging market debt, and during crisis periods. This study has important policy implications for international investors’ asset allocation plans and for regulatory bodies such as the Basel Committee who increasingly rely upon Moody's, Standard and Poor's and Fitch's ratings for their regulatory regimes.     

Risk spillovers and hedge strategies between global crude oil markets and stock markets: Do regime switching processes combining long memory and asymmetry matter?

This paper investigates risk spillovers and hedge strategies between global crude oil markets and stock markets. In the paper, we propose a multivariate long memory and asymmetry GARCH framework that integrates state-dependent regime switching in the mean process with multivariate long memory and asymmetry GARCH in the variance process. Our results first show that there are linear risk spillovers running from the US stock markets to the WTI oil market in the short term. However, the linear risk spillover effect running from the oil market to the US stock market can only exist in the long term. In addition, there is a bidirectional linear risk spillover effect between the European stock markets and the Brent oil market in the short and long terms. Furthermore, there is no linear risk spillover effect between the Dubai oil market and the Chinese stock market. Second, the nonlinear risk spillovers running from the WTI oil market to the US stock market can be found in the tranquil regime. Moreover, there is also a nonlinear risk spillover effect running from the European stock markets to the Brent oil market in the tranquil regime. In addition, the nonlinear risk spillover effect running from the Brent oil markets to the European stock market can be found in the crisis regime. Furthermore, there is bidirectional nonlinear Granger causality between the Dubai crude oil market and the Chinese stock market in the tranquil regime. Finally, dynamic hedge effectiveness shows that the regime switching process combined with long memory and asymmetry behavior seems to be a plausible and feasible way to conduct hedge strategies between the global crude oil markets and stock markets.     

Forecasting oil futures market volatility in a financialized world: Why speculative activities matter

We analyze the relation between volatility and speculative activities in the crude oil futures market and provide short-term forecasts accordingly. By incorporating trading volume and opening interest (speculative ratio) into the volatility dynamics, we document the subtle interaction between the two measures of which the volatility-averse behavior of speculative activities plays a considerable role in the market. Moreover, by accounting for structural changes, we find significant evidence that this behavior currently becomes weaker than in the past, which implies the oil futures market is less informative and/or less risk-averse in recent time period. Our forecasts based on these features perform very well under the predictive preferences that are consistent with the volatility-averse behavior in the oil futures market. We provide discussions and policy inferences.     

Economic policy uncertainty,oil price volatility and stock market returns: Evidence from a nonlinear model

This paper investigates the nonlinear relationship between economic policy uncertainty, oil price volatility and stock market returns for 25 countries by applying the panel smooth transition regression model. We find that oil price volatility has a negative effect on stock returns, and this effect increases with economic policy uncertainty. Furthermore, there is pronounced heterogeneity in responses. First, oil-exporting countries whose economies depend more on oil prices respond more strongly to oil price volatility than oil-importing countries. Second, stock returns of developing countries are more susceptible to oil price volatility than that of developed countries. Third, crisis plays a crucial role in the relation between oil price volatility and stock returns.     

The asymmetric effect of crude oil prices on stock prices in major international financial markets

The aim of this paper is to explore the potential asymmetric impacts of positive and negative shocks in crude oil prices on stock prices in six major international financial markets which include China, Hong Kong, America, Japan, Britain, and Germany. We test for these asymmetric effects on 8 major international financial markets indices over the 2007M01–2020M03 periods. Our independent measures include the prices of Brent crude oil futures and West Texas Intermediate (WTI) futures. We use the nonlinear ARDL (NARDL) model proposed by Shin et al. (2014), which can capture both short- and long-run nonlinearities through positive and negative partial sum decompositions of the explanatory variables. This research finds that positive and negative fluctuations of oil price have asymmetric effects on stock price index in four financial markets, but the performance of the asymmetry is different. Specifically, the impacts of volatility in oil prices on two indices of Chinese stock prices are different, and the asymmetric effects of oil price volatility on stock price indices in China and other financial markets are significantly different.     

Market reactions to trade friction between China and the United States: Evidence from the soybean futures market

In March 2018, the US used an immense trade deficit as an excuse to provoke trade friction with China. This study uses the EGARCH model and event study methods to study the impact of the major risk event of Sino-US trade friction on soybean futures markets in China and the United States. Results indicate that the Sino-US trade friction weakened the return spillover effect between the soybean futures markets in China and the US, and significantly increased market volatilities. As the scale of additional tariffs increased, the volatility of the Chinese soybean futures market declined; however, the volatility of the US soybean futures market did not weaken. In addition, expanding the sources of soybean imports helped ease the impact of tariffs on China’s soybean futures market, while the decline in US soybean exports to China intensified the volatility of the US soybean futures market. In addition, while the release of multiple tariff increases has had a short-term impact on the returns of soybean futures markets, the impact of trade friction has gradually decreased.     

Trading and non-trading period realized market volatility: Does it matter for forecasting the volatility of US stocks?

We study the potential merits of using trading and non-trading period market volatilities to model and forecast the stock volatility over the next one to 22 days. We demonstrate the role of overnight volatility information by estimating heterogeneous autoregressive (HAR) model specifications with and without a trading period market risk factor using ten years of high-frequency data for the 431 constituents of the S&P 500 index. The stocks’ own overnight squared returns perform poorly across stocks and forecast horizons, as well as in the asset allocation exercise. In contrast, we find overwhelming evidence that the market-level volatility, proxied by S&P Mini futures, matters significantly for improving the model fit and volatility forecasting accuracy. The greatest model fit and forecast improvements are found for short-term forecast horizons of up to five trading days, and for the non-trading period market-level volatility. The documented increase in forecast accuracy is found to be associated with the stocks’ sensitivity to the market risk factor. Finally, we show that both the trading and non-trading period market realized volatilities are relevant in an asset allocation context, as they increase the average returns, Sharpe ratios and certainty equivalent returns of a mean–variance investor.     

Index futures trading and stock price volatility: Evidence from Denmark and France

This study uses an EGARCH methodology to investigate the impact of index futures trading on the price volatility of two European stock markets. The results show that index futures trading has changed the distribution of stock returns in Denmark and France, however, it has not increased stock price volatility. There is evidence that futures trading has dampened stock price fluctuations in France. The results further show that stocks in Denmark and France exhibit strong volatility persistence and asymmetry, especially during the post-futures period.