Forecasting realized volatility of crude oil futures with equity market uncertainty

This paper examines whether the equity market uncertainty (EMU) index contains incremental information for forecasting the realized volatility of crude oil futures. We use 5-min high-frequency transaction data for WTI crude oil futures and develop six heterogeneous autoregressive (HAR) models based on classical HAR-type models. The empirical results suggest that EMU contains more incremental information than the economic policy uncertainty (EPU) for forecasting the realized volatility of crude oil futures. More importantly, we argue that EMU is a non negligible additional predictive variable that can significantly improve the 1-day ahead predictive accuracy of all six HAR-type models, and improve the 1-week ahead forecasting performance of the HAR-RV, HAR-RV-J, HAR-RSV, HAR-RV-SJ models. These findings highlight a strong short-term and a weak mid-term predictive ability of EMU in the crude oil futures market.     

Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect

The empirical results of the risk-return relationship are mixed for both mature and merging markets. In this paper, we develop a new volatility model to revisit the risk-return relation of the aggregate stock market index by extending the Realized GARCH model of Hansen et al. (2012) with the Wang and Yang (2013) framework, in which the overall risk-return relation is decomposed into a risk premium and a volatility feedback effect. An empirical analysis of three major Chinese stock indices reveals positive risk premium and negative volatility feedback effect, and those findings are stable across different markets and sub-samples. However, their relative magnitudes differ between markets and varies through time.     

Measuring asymmetry and persistence in conditional volatility in real output: evidence from three East Asian tigers using a multivariate GARCH approach

We search for evidence of conditional volatility in the quarterly real Gross Domestic Product (GDP) growth rates of three East Asian tigers: Singapore, Hong Kong and Taiwan. The widely accepted Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH)-type model is used to capture the existence of asymmetric volatility and the potential structural break points in the volatility. We find evidence of asymmetry and persistence in the volatility of GDP growth rates. It is noted that the structural breakpoints of volatility correspond reasonably well to the historical economic and political events in these economies. Policy implications from our findings are discussed.     

Long memory in the volatility of China stock returns

In this paper, we empirically examine the volatility process of China's stock market returns using daily and weekly Shanghai and Shenzhen stock indices during January 1990 to August 2008. To investigate the property of the process, we used the FIGARCH (fractionally integrated GARCH) model including GARCH and IGARCH processes as special cases. Since the FIGARCH model allows fractional integration order, it can detect hyperbolically decaying volatility processes which cannot be explained by previous models with integer integration order. Our results show that the Shanghai and Shenzhen stock indices exhibit long-term dependencies. The long memory properties of the Shanghai and Shenzhen stock markets do not seem to be spuriously induced without exception.     

Exchange rate volatility and US commodity trade with the rest of the world

Exchange rate volatility is argued to affect the trade flows negatively and positively. Indeed, empirical studies that have addressed the issue have supported both effects. These studies have used aggregate trade flows data either between one country and the rest of the world or between two countries at the bilateral level. Studies that have disaggregated trade data by industry are rare. Thus, we extend the literature by looking at the experiences of 66 American industries that trade with the rest of the world using monthly data. In most cases, trade flows are not affected by GARCH‐based volatility of the real effective exchange rate of the dollar.     

Trading volume and returns relationship in SET50 index futures market

This study investigates the relationship between trading volume and returns in SET50 index Futures market in the period from April 2006 to December 2008 using 653 observations. From previous studies, we include three methodologies namely the GARCH model, the Generalized Method of Moments （GMM） to estimate systems of equations and the Granger causality test to investigate the relationship more thoroughly. In addition, we introduce the lagged volume as a new explanatory variable in the GARCH model. Overall, the results show the significant contemporaneous and dynamic relationships between trading volume and returns volatility which support the sequential information arrival hypothesis and imply some degree of market inefficiency. The results from this study also show that past information of trading volume can be used to improve the prediction of price volatility. Therefore, regulators and traders could include past information of trading volume of SET50 index futures in tracking and monitoring the market volatility level and the investment risk in order to make a timely decision.     

Jumps and volatility dynamics in agricultural commodity spot prices

The spot commodities market exhibits both extreme volatility and price spikes, which lead to heavy-tailed distributions of price change and autocorrelation. This article uses various Lévy jump models to capture these features in a panel of agricultural commodities observed between January 1990 and February 2014. The results show that Levy jump models outperform the continuous Gaussian model. Our results prove that assuming a constant volatility or even a deterministic volatility and drift structure of agricultural commodity spot prices is not realistic and is less efficient than the stochastic assumption. The findings demonstrate an interesting correlation between volatility and jumps for a given commodity i, but no relationship between the volatility of commodity i and the probability of jumps of commodity j.     

Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.     

Price and volatility dynamics between securitized real estate spot and futures markets

This study is among the first to examine the price, volatility and covariance dynamics between securitized real estate spot and futures markets. It provides a distinctive and yet complementary perspective on the predictability of real estate spot return and spot volatility based on the information from the spot market alone. The results show that for the EPRA/NAREIT Europe index, the spot market tends to lead its futures market in the long run during the sample period, which can be attributed to a rather illiquid real estate futures market in sharp contrast with a voluminous spot market. Furthermore, we find the V-shaped asymmetric effect of the basis on the futures market volatility, which represents the primary channel of strong volatility transmission between securitized real estate spot and futures markets during the whole sample and the post-crisis period. This sheds light on the hedging effectiveness for the REIT index.     

An econometric analysis of the effects of market liberalization on price dynamics and price volatility

The paper investigates price dynamics under market liberalization, with a focus on the effects of lowering price floors. We analyze price dynamics by specifying and estimating a dynamic Tobit model under time-varying volatility, where the market price is censored by a government-set support price. The model is applied to the U.S. butter market over the last three decades. The econometric results show how the price support program affects both expected prices and the volatility of prices. It is found that the censoring effects of a price support program can be significant and large even if the price support is set relatively low.

The impact of public and semi-public information on cotton futures market

This study estimated the impact of all major public and semi-public reports on the cotton futures market from 1995 through 2012. The estimation was based on the event study approach with the events measured by the release of five major reports: Export Sales, Crop Progress, World Agricultural Supply and Demand Estimates (WASDE) and Prospective Plantings (public reports from US Department of Agriculture) and Cotton This Month (semi-public report from International Cotton Advisory Committee). The best-fitting IGARCH(1,1)-t model that accounted for the day-of-week, seasonality and stock levels was used to measure the report effects on daily nearby cotton close-to-close futures returns. Prospective Plantings and WASDE reports appeared to be the most important sources of information in the cotton markets moving the conditional standard deviation of returns by an average of 14.4 and 9.6 percentage points, respectively. However, significant market reaction was not found for the other three reports. Our analysis revealed that, in the presence of clustering, ignoring the impact of other reports would have resulted in about 18% overestimation of WASDE impact.     

Intraday return and volatility relationships between the Ibex 35 spot and futures markets

This paper analyses the intraday lead-lag relationships between returns and volatilities in the Ibex 35 spot and futures markets. Using hourly data, we jointly analyze the interactions between markets, estimating a bivariate error correction model with GARCH perturbations which captures stochastically the presence of an intraday U-shaped curve for both spot and futures market volatility. Our findings show a bidirectional causal relationship between market volatilities, with a positive feedback. This two-way transmission of volatility is consistent with market prices evolving according to a long-run equilibrium relationship, and shocks affecting both markets in the same direction. Our empirical results also support a unidirectional cross interaction from futures to spot market returns. This pattern suggests that the futures market leads the spot market in order to incorporate the arrival of new information.     

Environmental rights on the futures markets an application to the dutch manure market

A study was carried out to analyze futures markets for tradable rights after a cash market was initiated. Furthermore, some indication was given on the size of such a futures market to provide insight into its viability. Futures markets can play a role in solving environmental problems, by making the market for pollution rights (i.e. P₂O₅ rights) and agro rights (milk rights, sugar rights and P₂O₅ rights) more effective and transparent. Moreover, the market for tradable rights would be able to meet the users' need for hedging. This paper investigated the possibility of introducing a futures markets for tradable P₂O₅ rights and the commodity manure. Because there is already a cash market for manure, although not well developed yet, and there will be a cash market for P₂O₅ rights, a futures market is a logical sequel. The futures market can play a role in implementing agricultural policy efficiently and with respect to manure and P₂O₅ rights can be an economically efficient solution to environmental problems.We acknowledge the financial support of the ATA (Agricultural Futures Market Amsterdam).     

Endogenous uncertainty and market volatility

We advance the theory that the distribution of beliefs in the market is the most important propagation mechanism of economic volatility. Our model is based on the theory of Rational Beliefs (RB) and Rational Belief Equilibrium (RBE) developed by Kurz (1994, 1997). We argue that the diverse market puzzles which are examined, such as the equity premium puzzle, are all driven by the structure of market expectations. In support of our view, we present an RBE model with which we study financial markets. The model is able to simulate the correct order of magnitude of: (i) the long term mean and standard deviation of the price\dividend ratio; (ii) the long term mean and standard deviation of the risky rate of return on equities; (iii) the long term mean and standard deviation of the riskless rate; (iv) the long term mean equity premium. In addition, the model predicts (v) the GARCH property of risky asset returns; (vi) the observed pattern of the predictability of long returns on assets, and (vii) the Forward Discount Bias in foreign exchange markets. The common economic explanation for these phenomena is the existence of heterogenous agents with diverse but correlated beliefs such that some agents are optimistic and some pessimistic about future capital gains. The model has a unique parameterization under which the model makes all the above predictions simultaneously. The parameterization requires the optimists to be in the majority but the rationality of belief conditions of the RBE require the pessimists to have a higher intensity level. In simple terms, the large equity premium and the low equilibrium riskless rate are the result of the fact that at any moment of time there are agents who hold extreme pessimistic beliefs and they have a relatively stronger impact on the market. The paper also studies the effect of correlation of beliefs among investors. It shows that the main effect of such correlation is on the dynamic patterns of asset prices and returns and is hence important for studying such phenomena as stochastic volatility. Received: May 16, 2000; revised version: November 15, 2000     

Nominal and real volatility as determinants of FDI

This article examines the role of country-specific sources of output and interest rate or exchange rate volatility in driving Foreign Direct Investment (FDI) activities. Building on a dataset with bilateral FDI flows among 24 Organization for Economic Co-operation and Development (OECD) economies over the period 1985–2007, we find that nominal and real volatility strongly deter foreign investments. Output and exchange rate volatility matter in particular for the decision whether to invest in a foreign country in the first place. Interest rate volatility mainly influences the amount of foreign investments.     

基于波动效应与价格发现的期指仿真交易研究

采用修正的GARCH模型和向量误差修正模型（VEC）将股指期货推出后现货市场波动性的变化和股指期货与现货市场的价格发现功能结合起来进行对比研究发现,期指仿真交易的推出对于现货市场效率的改进确实存在正面的影响。其引入在短期内加大了现货市场的波动,但这一波动正是市场信息流动加速的反映,因而提高了市场信息的传递效率。研究同时也表明,期货价格领先于现货价格,存在由期货市场到现货市场长期的单向因果关系,说明期货价格具有引导现货价格向均衡方向调整的功能,从而在经验上支持了股指期货市场的开放政策。     

Forecasting the aggregate stock market volatility in a data-rich world

ABSTRACT

In this article, we utilize the basic lasso and elastic net models to revisit the predictive performance of aggregate stock market volatility in a data-rich world. Motivated by the existing literature, we determine several candidate predictors that have 22 technical indicators and 14 macroeconomic and financial variables. Our out-of-sample results reveal several noteworthy findings. First, few macroeconomic and financial variables and most of technical indicators have superior performance relative to the benchmark model. Second, combination forecasts are able to significantly beat the benchmark and some signal predictors Third, the lasso and elastic models with all predictors can generate more accurate forecasts than the benchmark and some other predictors in both the statistical and economic sense. Fourth, the lasso and elastic models exhibit higher forecast accuracy during periods of expansions and recessions. Finally, our findings are robust to several tests, such as different forecasting windows, forecasting models, and forecasting evaluations.     

Modelling the volatility of the tanker freight market based on improved empirical mode decomposition

In this article, a method based on empirical mode decomposition (EMD) and BEKK–Multivariate GARCH (MVGARCH) is developed to analyse the volatility of the tanker freight market. First, the initial time series of tanker freight rates is decomposed into several independent intrinsic mode functions (IMFs). Next, the IMFs are composed as three components by an improved EMD: the long-term trend time series that represents the benchmark freight rates of the tanker freight market, the high-frequency time series that reflects the short-term supply–demand relation and the low-frequency time series caused by extreme events. Based on the results of EMD, the volatility spillover effects between the freight rates of Aframax, Suezmax and Very Large Crude Carrier (VLCC) markets are tested by the BEKK–MVGARCH model. The results indicate that there are volatility spillover effects between the reconstructed components, although the volatility spillover effects between the original freight series are not significant. The improved EMD method contributes to the retention of the economic characteristics of the original time series, thereby providing a vital approach for tanker freight market analysis. Furthermore, the potential volatility spillover among different sub-markets can be investigated through the integration of EMD and the BEKK–MVGARCH.     

Economic policy uncertainty and the Chinese stock market volatility: new evidence

This study investigates the impacts of the economic policy uncertainty (EPU) indexes of China and the G7 countries on Chinese stock market volatility and further constructs a new diffusion index based on these indexes using principal component analysis (PCA) to achieve enhanced predictive ability. The in-sample results indicate that the EPU indexes of China and some of the G7 countries show a significantly negative impact on future volatility. Moreover, our constructed diffusion index also has a significantly negative impact. Furthermore, the out-of-sample results show that this diffusion index exhibits a significantly higher forecast accuracy than the EPU itself and combination forecasts. Finally, various robustness checks are consistent with our main conclusions. Overall, we construct a new and useful indicator that can substantially increase forecast accuracy with respect to the Chinese stock market.