Tail risk in emerging markets of Southeastern Europe

This article examines the left-tail behaviour of returns on stocks in Southeastern Europe (SEE). We apply conditional extreme value theory (EVT) approach on daily returns of six stock market indices from SEE between 2004 and 2013. Predictive performance of value-at-risk (VaR) and expected shortfall (ES) based on EVT is compared against several alternatives, such as historical simulation and analytical approach based on GARCH with a single conditional distribution. Model backtesting with daily returns shows that EVT-based models provide more reliable VaR and ES forecasts than the alternative models in all six markets. Unlike the alternatives, the EVT-based models cannot be rejected as VaR confidence level is increased. This emphasizes the importance of extreme events in SEE markets and indicates that the ability of a model to capture volatility clustering accurately is not sufficient for a correct assessment of risk in these markets.     

Quantile serial dependence in crude oil markets: evidence from improved quantilogram analysis with quantile wild bootstrapping

We examine the quantile serial dependence in crude oil prices based on the Linton and Whang’s quantile-based portmanteau test which we improved by means of quantile wild bootstrapping (QWB). Through Monte Carlo simulation, we find that the quantile wild bootstrap-based portmanteau test performs better than the bound testing procedure suggested by Linton and Whang. We apply the improved test to examine the efficiency of two crude oil markets – WTI and Brent. We also examine if the dependence is stable via rolling sample tests. Our results show that both WTI and Brent are serially dependent in all, except the median quantiles. These findings suggest that it may be misleading to examine the efficiency of crude oil markets in terms of mean (or median) returns only. These crude oil markets are relatively more serially dependent in non-median ranges.     

Covariance breakdowns and connectedness of crude oil futures markets with non-synchronous data

ABSTRACT

This article identifies the breakdowns in the covariance of three benchmark crude oil futures markets (WTI, Brent and Dubai) and investigates the changes of market connectedness across the breakdown periods. As the crude oil futures are traded in different regions, this article eliminates the non-synchronous trading data by employing the Vector Moving Average structure and the Bayesian data augmentation approach, which keeps the integrity of original data without changing its properties. The results show that there are significant breaks in the covariance structure of crude oil futures markets. The breakdown periods are consistent with the periods when the market volatilities are at high level and the returns are volatile. The changes of market connectedness are independent of the covariance states, which supports the globalization hypothesis for the crude oil market. The results also suggest that there is more information flow out of the WTI than to the WTI during the sample period, particularly during the breakdown periods in 2008–2009.     

Responses of international stock markets to oil price surges: a regime-switching perspective

We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries. Our model accounts for the joint effects of the West Texas Intermediate (WTI) and Brent oil markets and simultaneously captures asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behaviour, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price surges than during the bull market phases. Whether the effects of oil shocks are positive or negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.     

Energy portfolio risk management using time-varying extreme value copula methods

This work is concerned with the statistical modeling of the dependence structure between three energy commodity markets (WTI crude oil, natural gas and heating oil) using the concept of copulas and proposes a method for estimating the Value at risk (VaR) of energy portfolio based on the combination of time series models with models of the extreme value theory before fitting a copula. Each return series is modeled by AR-(FI) GARCH univariate model. Then, we fit the GPD distribution to the tails of the residuals to model marginal residuals distributions. The extreme value copula to the iid residuals is fitted and we simulate from it to construct N portfolios and estimate VaR. As a first step, the method is applied to a two-dimensional energy portfolio. In second step, we extend method in trivariate context to measure VaR of three-dimensional energy portfolio. Dependences between residuals are modeled using a trivariate nested Gumbel copulas. Methods proposed are compared with various univariate and multivariate conventional VaR methods. The reported results demonstrate that GARCH-t, conditional EVT and FIGARCH extreme value copula methods produce acceptable estimates of risk both for standard and more extreme VaR quantiles. Generally, copula methods are less accurate compared with their predictive performances in the case of portfolio composed of exchange market indices.     

An investigation into the dynamic relationship between international and China’s crude oil prices

This article studies the dynamic relationship between international (WTI, Brent and Dubai) and domestic (Da Qing) crude oil prices in China using threshold cointegration method. We find evidence of a long-run equilibrium relationship between each pair of international and Da Qing oil prices, favouring the market integration hypothesis. We also estimate asymmetric adjustments under the momentum threshold autoregressive (M-TAR) specification in a TVECM, and the results show that adjustments to eliminate disequilibrium happen faster when oil price spread increases than when it decreases. The long-run and short-run Granger causality tests support the notion that China has influence on the international oil markets. The results imply that China should open up its domestic and imported oil markets, and also establish a well-functioning crude oil futures market, as they are essential for arbitrage and hedging strategies.     

Optimization agricultural production under financial risk of water constraint in the Jordan Valley

Using high-frequency data the co-movements among crude oil prices are analysed in order to address the question of regionalization of the world crude oil market. Time-series econometrics in the form of error-correction modelling is applied for daily crude oil price data covering the time period 1988 to 2004 and in this framework topics like weak and strong exogeneity among three major oil prices – represented by Brent, OPEC and Texas (WTI) – are addressed. The empirical results are that causality is most likely bi-directional among these crude oil prices – and hence rejecting a regionalization hypothesis of the global oil market – and also an influence from the OPEC oil price towards Bent and WTI, which are usually claimed to have a benchmark role.     

Impact of macroeconomic factors and country risk ratings on GCC stock markets: evidence from a dynamic panel threshold model with regime switching

This study examines the non-linear relationship between stock markets in GCC countries and their country risk ratings as well as with major macroeconomic factors. Based on a dynamic panel threshold model with two and four regimes, the results provide evidence of short-term asymmetry between first-lagged GCC stock returns and the performance of GCC stock markets. In addition, only the financial risk (FR) rating has a significant positive effect on the performance of GCC stock markets according to the prevailing regimes for the GCC lagged returns and the Brent oil market. Among the macroeconomic factors, improvements in the global stock markets, the MSCI Global Islamic Index, and the oil price increased the performance of GCC stock markets, whereas increases in the gold price, the 3-month U.S. Treasury bill rate, and the U.S. Treasury bond rate reduced the performance of the GCC stock markets. These results have important implications for investors, policymakers, and portfolio managers.     

Causality patterns for Brent,WTI, and Argus oil prices

Causality patterns are analysed for daily Brent, West Texas Intermediate (WTI), and Argus Sour Crude Index (Argus) oil prices, Argus is the reference price for exports from Saudi Arabia, Kuwait and Iraq. Nonparametric Granger causality testing uncovers bi-directional causal links between Brent and WTI prices at multiple lags. Unidirectional causality from both Brent to Argus and WTI to Argus is also documented. If the current Saudi Arabia attempt to increase market share is successful, variations in Argus prices may start preceding movements in Brent and WTI, also.     

Crude Oil Futures as an Indicator of Market Changes: A Graphical Analysis

This study investigates the changing relationship between price and volume traded of short- and long-maturity NYMEX light sweet crude oil futures contracts and major changes in the physical crude oil market during the last decade. Monthly series for the #1-month to 84-month out maturity contracts are generated from daily price and volume data for NYMEX West Texas Intermediate (WTI) futures contracts for the period from January 2000 to the middle of 2009. 3-D graphical analysis of the futures prices, contract volumes, maturity dates, and time is used to demonstrate the changing trading volume pattern and evolution of the shape of futures price term structure across various contract maturities in different market regimes. The study observes the impacts of both May 2004, when excess production capacity reached nearly zero, and September 2006, when electronic trading was implemented on the NYMEX WTI futures markets. This analysis will be used to determine if futures contract information can provide an early indication of market regime shifts and improve short-run crude oil spot price forecast models.     

基于ARIMA与GARCH模型的国际油价预测比较分析

在分析影响油价波动因素的基础上,利用1986年1月至2010年12月的WTI国际原油价格月度数据,分别建立ARIMA和GARCH模型对油价进行预测。并通过对2011年1月至2012年4月WTI原油价格进行外推预测,检验模型的预测效果。比较分析发现,在短期预测中,ARIMA和GARCH模型对油价的预测均比较准确,但当油价由于受到重大事件的影响而有较大波动时,模型的预测精度下降;在长期预测中,GARCH模型的预测效果优于ARIMA模型;整体来看,GARCH模型预测的精度高于ARIMA模型。因此,在国际油价预测中,用GARCH模型是比较合适的。     

我国期货价格风险管理研究——基于VaR方法与GARCH-t模型的视角

本文利用我国商品期货及金融期货2010年9月份合约数据采用VaR方法对其收益率序列的波动性进行了检验。研究结果发现:首先,应用GARCH-t模型的方法对期货商品的价格风险进行管理具有显著的有效性和适用性,特别是在95%的置信水平下对收益率波动性的拟合效果最佳,同时该方法对期货商品正收益率的拟合效果比负收益率更好。其次,我国股指期货正式推出后,收益率波动性较模拟交易时期显著变小,表明改进后的交易制度及政府监管等措施可能限制了市场上的过度投机行为。最后,农副产品期货的风险暴露程度比股指、金属和能源化工等期货品种要小。     

Realized volatility transmission: The role of jumps and leverage effects

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.     

Bad volatility is not always bad: evidence from the commodity markets

ABSTRACT

Using exchange-traded fund (ETF) options data, we examine the predictive power of variance risk premium on returns of four commodities: crude oil, natural gas, gold and silver. We also analyze the predictive power of upside and downside variance risk premiums using a decomposition model conditional on the direction of the underlying market movement. We find that both the undecomposed and decomposed variance risk premiums are able to predict commodity prices. The decomposed variance risk premiums, however, outperform the undecomposed premium. The importance of upside and downside variance risk premiums differs across markets, related to hedging demand. In energy markets, both upside and downside premiums have strong predictive power, while in precious metal markets, only the upside premium is predictive.     

Can GARCH-class models capture long memory in WTI crude oil markets?

This paper investigates the issue whether GARCH-type models can well capture the long memory widely existed in the volatility of WTI crude oil returns. In this frame, we model the volatility of spot and futures returns employing several GARCH-class models. Then, using two non-parametric methods, detrended fluctuation analysis (DFA) and rescaled range analysis (R/S), we compare the long memory properties of conditional volatility series obtained from GARCH-class models to that of actual volatility series. Our results show that GARCH-class models can well capture the long memory properties for the time scale larger than a year. However, for the time scale smaller than a year, the GARCH-class models are misspecified.     

Dynamic relationships between crude oil prices and socially responsible investing in Brazil: evidence for linear and non-linear causality

Recent years have witnessed an increasing interest in socially responsible investing (SRI), reflecting investors’ growing awareness of social, environmental, ethical and corporate governance issues. At the same time, the effect of oil price shocks on stock price returns has become a prominent issue due to surges in energy prices. Using the Brazilian corporate sustainability index (ISE) as a benchmark for socially responsible investments in the Brazilian stock market, the present study extends the understandings on the impact of oil prices on stock price behaviour, focusing on a new class of assets: those from socially responsible firms. To this end, apart from conventional linear causality approaches, we apply a nonparametric test by Diks and Panchenko (DP) on daily data spanning from January 2008 to December 2015 to test for non-linear causality, before and after controlling for conditional heteroscedasticity. Our findings show that, in spite of their efforts to become more socially responsible, firms that have adhered to the ISE in recent years are influenced by crude oil spot prices, especially the WTI crude. In line with previous studies, we also provide consistent evidence that the Brazilian stock market, as a whole, is associated with the international crude oil market.     

Relationship between oil price and exchange rate by FDA and copula

This article investigates the relationship between daily crude oil prices and exchange rates. Functional data analysis is used to show the clustering pattern of exchange rates and oil prices over the time period through high dimensional visualizations. We select exchange rates for important currencies related to crude oil prices by using the objective Bayesian variable selection method. The selected sample data exhibits non-normal distribution with fat tails and skewness. Under the non-normality of the return series, we use copula functions that do not require to assume the bivariate normality to consider marginal distribution. In particular, our study applies the popular and powerful statistical methods such as Gaussian copula partial correlations and Gaussian copula marginal regression. We find evidence of significant dependence for all considered pairs, except for the Mexican peso-Brent. Our empirical results also show that the rise in the West Texas Intermediate (WTI) oil price returns is associated with a depreciation of the US dollar.     

Value at risk estimation by threshold stochastic volatility model

This article proposes a threshold stochastic volatility model that generates volatility forecasts specifically designed for value at risk (VaR) estimation. The method incorporates extreme downside shocks by modelling left-tail returns separately from other returns. Left-tail returns are generated with a t-distributional process based on the historically observed conditional excess kurtosis. This specification allows VaR estimates to be generated with extreme downside impacts, yet remains empirically widely applicable. This article applies the model to daily returns of seven major stock indices over a 22-year period and compares its forecasts to those of several other forecasting methods. Based on back-testing outcomes and likelihood ratio tests, the new model provides reliable estimates and outperforms others.     

我国畜产品市场价格风险度量与分析

提出了利用VaR度量农产品现货市场风险的定量方法,并以我国鸡蛋、活鸡、牛肉、羊肉和猪肉五种畜产品的市场风险度量为例进行实证分析,研究结果表明,正态分布并不是拟合我国畜产品市场风险的最优分布模型,利用VaR度量农产品市场风险的方法切实可行。     

Price transmission and local market power: empirical evidence from the Austrian gasoline market

We analyse the impact of local market power on price margins and different dimensions of price adjustment dynamics (speed and asymmetry of price transmission) using data for a large number of individual gasoline stations in Austria. Specific attention is paid to threshold effects in price adjustment. Our results clearly suggest that the speed of price transmission between the Brent crude oil index and retail diesel prices is higher in a more competitive environment. While evidence on the relationship between local market power and asymmetries in the speed of price adjustment is mixed, our findings regarding asymmetries in price thresholds are clear: in regions where competition from neighbouring rivals is weak and/or consumers’ price elasticity of demand is low (stations located on the highway), positive thresholds significantly exceed negative ones, which corresponds to the ‘rockets and feathers phenomenon’. As expected, we observe that prices are lower in more competitive local markets.