Showing papers in "Journal of Futures Markets in 2016"

Do jumps matter for volatility forecasting?:Evidence from energy markets

Abstract: This paper characterizes the dynamics of jumps and analyzes their importance for volatility forecasting. Using high‐frequency data on four prominent energy markets, we perform a model‐free decomposition of realized variance into its continuous and discontinuous components. We find strong evidence of jumps in energy markets between 2007 and 2012. We then investigate the importance of jumps for volatility forecasting. To this end, we estimate and analyze the predictive ability of several Heterogenous Autoregressive (HAR) models that explicitly capture the dynamics of jumps. Conducting extensive in‐sample and out‐of‐sample analyses, we establish that explicitly modeling jumps does not significantly improve forecast accuracy. Our results are broadly consistent across our four energy markets, forecasting horizons, and loss functions.

Who Sets the Price of Gold? London or New York

Abstract: We investigate which of the two main centers of gold trading—the London spot market and the New York futures market—plays a more important role in setting the price of gold. Using intraday data during a 17‐year period, we find that although both markets contribute to price discovery, the New York futures play a larger role on average. This is striking given the volume of gold traded in New York is less than a tenth of the London spot volume, and illustrates the importance of market structure on the process of price discovery. We find considerable variation in price discovery shares both intraday and across years. The variation is related to the structure and liquidity of the markets, daylight hours, and macroeconomic announcements that affect the price of gold. We find that a major upgrade in the New York trading platform reduces the relative amount of noise in New York futures prices, reduces the impact of daylight hours on the location of price discovery, but does not greatly increase the speed with which information is reflected in prices. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:564–586, 2016

Forecasting Stock Return Volatility: A Comparison of GARCH, Implied Volatility, and Realized Volatility Models

Abstract: We investigate the information content of implied volatility forecasts for stock index return volatility. Using different autoregressive models, we examine whether implied volatility forecasts contain information for future volatility beyond that in GARCH and realized volatility models. Results show implied volatility follows a predictable pattern and confirm the existence of a contemporaneous relationship between implied volatility and index returns. Individually, implied volatility performs worse than alternate forecasts, however, a model that combines an asymmetric GARCH model with implied and realized volatility through (asymmetric) ARMA models is preferred model for forecasting volatility. This evidence is further supported by consideration of value-at-risk. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1127–1163, 2016

Spillovers and Directional Predictability with a Cross-Quantilogram Analysis: The Case of U.S. and Chinese Agricultural Futures

Abstract: This paper examines the daily, overnight, intraday, and rolling return spillovers of four key agricultural commodities—soybeans, wheat, corn, and sugar, between the U.S. and Chinese futures markets via a newly developed quantile dependence measure called quantilogram. The results reveal significant bi-directional dependence between the two markets across commodities which is greater in extreme quantiles and moderately stronger from the United States to China. These findings offer valuable insights into investors’ behavior, market integration, dissimilarity, and market efficiency in both countries. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1231–1255, 2016

Fundamentals, Derivatives Market Information and Oil Price Volatility

Abstract: We investigate price volatility in the West Texas Intermediate (WTI) and Brent crude oil markets between 2000 and 2014. We provide empirical evidence of a relationship between the term structure of option-implied volatilities and global macroeconomic conditions, physical market fundamentals (OPEC surplus output capacity, oil storage) and economy-wide financial uncertainty (captured by the equity VIX). Based on public data regarding trader positions in U.S. futures markets, the intensity of oil speculation is statistically insignificant. Unexpected disruptions in the crude oil space are associated with large regression residuals. Our findings suggest that derivatives (“paper”) market contain information on the magnitude and duration of major oil market disruptions.

Investor Attention and Macroeconomic News Announcements: Evidence from Stock Index Futures

Abstract: This paper examines the role of investor attention in scheduled macroeconomic announcements, using intraday data from the Chinese Stock Index futures market. Overall, investor attention, proxied by the Baidu Search Index, is significantly higher in the Consumer Price Index (CPI) than in other macroeconomic news. Consistently, only the CPI announcement has a substantial short‐term impact on the price, liquidity, and volatility of the CSI 300 index futures. In addition, the reactions of futures price to CPI announcements are stronger to bad CPI news, more sensitive in high‐inflation periods, and less pronounced on Fridays, consistent with our investor attention behavior findings. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:240–266, 2016

Analyzing Oil Futures with a Dynamic Nelson‐Siegel Model

Abstract: The dynamic Nelson–Siegel model is used to model the term structure of futures contracts on oil and obtain forecasts of prices of these contracts Three factors are extracted and modelled in a very flexible framework The outcome of this exercise is a class of models which describes the observed prices of futures contracts well and performs better than conventional benchmarks in realistic real‐time out‐of‐sample exercises © 2015 Wiley Periodicals, Inc Jrl Fut Mark 36:153–173, 2016

The Return–Volatility Relation in Commodity Futures Markets

Abstract: By employing a continuous time stochastic volatility model, we analyse the dynamic relation between price returns and volatility changes in the commodity futures markets. We use an extensive daily database of gold and crude oil futures and futures options to estimate the model that is well suited to assess the return–volatility relation for the entire term structure of futures prices. Our empirical results indicate a positive relation in the gold futures market and a negative relation in the crude oil futures market, especially over periods of high volatility principally driven by market-wide shocks. However, the opposite reaction occurs over quiet volatility periods when typically commodity-specific effects dominate. As leverage effect and volatility feedback effect do not adequately explain this reaction especially for the crude oil futures, we propose the convenience yield effect. We demonstrate that commodity futures markets in normal backwardation entail a positive relation, while futures markets in contango entail a negative relation.

On Intraday Relation Between the Vix and Its Futures

Abstract: We study the intraday dynamics of the VIX and VIX futures for the period January 2, 2008 to December 31, 2014 Considering first the results of a Vector Autoregression (VAR) using daily data, we observe that there is some evidence of causality from VIX futures to the VIX Estimating a VAR using our ultra-high frequency data, we find strong evidence for bi-directional Granger causality between the VIX and the VIX futures Overall, this effect appears to be stronger from VIX futures to the VIX than the other way around Impulse response functions and variance decompositions confirm the dominance of the VIX futures Lastly, we show that the causality from the VIX futures to the VIX has been increasing over our sample period, whereas the reverse causality has been decreasing We observe that the VIX futures have become increasingly more important in the pricing of volatility We further document that the VIX futures dominate the VIX more on days with negative returns, and on days with high values of the VIX, suggesting that those are the days when investors use VIX futures to hedge their positions rather than trading in the S&P500 index options © 2015 Wiley Periodicals, Inc Jrl Fut Mark

An International Comparison of Implied, Realized, and GARCH Volatility Forecasts

Abstract: We compare the predictive ability and economic value of implied, realized, and GARCH volatility models for 13 equity indices from 10 countries. Model ranking is similar across countries, but varies with the forecast horizon. At the daily horizon, the Heterogeneous Autoregressive model offers the most accurate predictions, whereas an implied volatility model that corrects for the volatility risk premium is superior at the monthly horizon. Widely used GARCH models have inferior performance in almost all cases considered. All methods perform significantly worse over the 2008–09 crisis period. Finally, implied volatility offers significant improvements against historical methods for international portfolio diversification. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

Tests on the Monotonicity Properties of KOSPI 200 Options Prices

Abstract: This study demonstrates that the basic properties predicted by one-dimensional diffusion option pricing models are often violated, even in a highly liquid and leading options market. We analyze a high-quality intraday dataset of KOSPI 200 index options, one of the most actively traded options markets in the world, and find that option prices often do not monotonically correlate with underlying prices. We also empirically show that option prices often do not change, despite changes in underlying prices, when options are heavily traded by individual investors, who are normally noisy and uninformed. Our evidence is partially consistent with the implications of demand-based option pricing models, which predict that investor demand can significantly influence option prices in the presence of limits to arbitrage. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:625–646, 2016

Crude Oil and Agricultural Futures: An Analysis of Correlation Dynamics

Abstract: Correlations between oil and agricultural commodities have varied over previous decades, impacted by renewable fuels policy and turbulent economic conditions. We estimate smooth transition conditional correlation models for 12 agricultural commodities and WTI crude oil. While a structural change in correlations occurred concurrently with the introduction of biofuel policy, oil and food price levels are also key influences. High correlation between biofuel feedstocks and oil is more likely to occur when food and oil price levels are high. Correlation with oil returns is strong for biofuel feedstocks, unlike with other agricultural futures, suggesting limited contagion from energy to food markets.

Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?

Abstract: It is still an unanswered question how much trading activity is needed for efficient price discovery in commodity futures markets. For this purpose, we investigate the price discovery process of two thinly traded agricultural futures contracts traded at the European Exchange in Frankfurt. Our empirical results show that the trading volume threshold which is necessary to facilitate efficient price discovery is very low. As our findings are based on constant and time-varying vector error correction models, we also show that neglecting time-variation in the parameters can lead to misleading results. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark

Monetary Policy and Stock Prices: Does the “Fed Put” Work When It Is Most Needed?

Abstract: Most studies of the effect of monetary policy on asset prices use the event study methodology with daily data. The resulting estimates suffer from bias due to omitted variables and endogeneity of policy decisions. We provide evidence that this bias becomes so large during the 2007–2008 financial crisis that it reverses the sign of the estimated stock market response to monetary news, leading to an erroneous conclusion that interest rate cuts are bad news for stocks. We also examine the stock market reaction to monetary policy during the zero lower bound period. The results show a significant bias in daily event study estimates of the stock market response to news about the future path of monetary policy. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1210–1230, 2016

Information Flow, Trading Activity and Commodity Futures Volatility

Abstract: Based on unique news data relating to gold and crude oil, we investigate how news volume and sentiment, shocks in trading activity, market depth and trader positions unrelated to information flow covary with realized volatility. Positive shocks to the rate of news arrival, and negative shocks to news sentiment exhibit the largest effects. After controlling for the level of news flow and cross-correlations, net trader positions play only a minor role. These findings are at odds with those of [Wang (2002a). The Journal of Futures Markets, 22, 427–450; Wang (2002b). The Financial Review, 37, 295–316], but are consistent with the previous literature which doesn't find a strong link between volatility and trader positions. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:88–104, 2016

Convenience Yields and Risk Premiums in the EU‐ETS—Evidence from the Kyoto Commitment Period

Abstract: We examine convenience yields and risk premiums in the EU‐wide CO 2 emissions trading scheme (EU‐ETS) during the first Kyoto commitment period (2008–2012). We find that the market has changed from initial backwardation to contango with significantly negative convenience yields in futures contracts. We further examine the impact of interest rate levels in the Eurozone, the increasing level of surplus allowances and banking, as well as returns, variance, or skewness in the EU‐ETS spot market. Our findings suggest that the drop in risk‐free rates during and after the financial crisis has impacted on the deviation from the cost‐of‐carry relationship for emission allowances (EUA) futures contracts. Our results also illustrate a negative relationship between convenience yields and the increasing level of inventory during the first Kyoto commitment period, providing an explanation for the high negative convenience yields. Finally, we find that market participants are willing to pay an additional risk premium in the futures market for a hedge against increased volatility in EUA prices. Overall, our results contribute to the literature on the determinants and empirical properties of convenience yields and risk premiums for this relatively new class of assets. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:587–611, 2016

The Prevalence, Sources, and Effects of Herding

Abstract: We test the prevalence, sources and effects of herding among large speculative traders in thirty U.S. futures markets over 2004–2009. We find significant herding levels within the large trader category of managed money traders (hedge funds) who are known to have similar performance evaluation measures. Our results support for the notion that greater public information takes away incentives to herd. The number of traders and floor‐based markets are positively associated with herding, while trading volume and electronic trading are negatively related to herding. Notably, we find little evidence that herding by managed money traders serves to destabilize prices in futures markets. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:671–694, 2016

Estimation of Market Information Shares: A Comparison

Abstract: This note investigates via Monte Carlo simulation the finite-sample performance of two identification schemes that provide unique measures of Hasbrouck-type information share in price discovery. The Lien and Shrestha (2009) method is based on factorization of the full correlation matrix and the Grammig and Peter (2013) method is based on different correlations of price innovations in the tails and in the center of the distributions. We find that the GP method performs poorly under the chosen data generation processes. The LS method provides at most marginal improvement over the method based upon the upper/lower bound midpoint of the Hasbrouck measure. The results, therefore, support the common practice of the midpoint approach. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

Estimation and Hedging Effectiveness of Time-Varying Hedge Ratio: Nonparametric Approaches

Abstract: Many studies have estimated the optimal time-varying hedge ratio using futures, with most employing a bivariate generalized autoregressive conditional heteroscedasticity (BGARCH) model or a random coefficient model to estimate the time-varying hedge ratio. However, it has been argued that when the variability of the estimated time-varying hedge ratio is large, this ratio's hedging performance is not as good as that of the unconditional (constant) hedge ratio. This study proposes a nonparametric estimation approach to estimate and evaluate the optimal conditional hedge ratio. This method produces a time-varying hedge ratio with less volatility than those obtained from the BGARCH and random coefficient models. We evaluate the hedging performance of the various models using soybean oil, corn, S&P 500, and Hang Seng futures indices. The empirical results support the proposed nonparametric approach in terms of both in-sample and out-of-sample performance. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark

Asymmetric Effects of Volatility Risk on Stock Returns: Evidence from VIX and VIX Futures

Abstract: First, to separate different market conditions, this study focuses on how VIX spot (VIX), VIX futures (VXF), and their basis (VIX-VXF) perform different roles in asset pricing. Secondly, this study decomposes the VIX index into two parts, volatility calculated from out-of-the-money call options and volatility calculated from out-of-the-money put options. The analysis shows that out-of-the-money put options capture more useful information in predicting future stock returns.

Quantile Estimation of Optimal Hedge Ratio

Abstract: In this study, we analyze the dependence of hedging effectiveness on the realization of spot return by introducing the concept of a quantile hedge ratio. We estimate quantile hedge ratios for 20 different commodities at 15 quantiles. For daily data, we find that the quantile hedge ratio varies with the spot return distribution, displaying an inverted‐U relationship such that the quantile hedge ratios are generally smaller at the upper and lower tails of the spot distribution. The severity of these characteristics differs across commodities. However, for weekly and four‐weekly data, these characteristics are less prominent. Thus, the conventional hedge ratio would be appropriate for longer horizons, but not for shorter horizons. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:194–214, 2016

Components of the Bid–Ask Spread and Variance: A Unified Approach

Abstract: We develop a structural model for the price formation and liquidity supply of an asset. Ourmodel facilitates decompositions of both the bid–ask spread and the return variance intocomponents related ...

Spot and Futures Markets Linkages: Does Contango Differ from Backwardation?

Abstract: Recent research has concluded that spot and futures copper returns are more closely correlated during periods of contango than of backwardation It is argued speculation and investor demand in futures markets should affect spot prices to a much lesser extent during backwardation, due to an infeasible inter‐temporal arbitrage This article expands this line of research by analyzing daily spot and 3‐, 15‐, and 27‐month futures contract prices for industrial metals traded on the London Metal Exchange over a period of more than two decades Estimates of convenience yields are provided, along with tests for Granger causality between futures and spot returns after accounting for cointegration, and tests for statistical differences between correlations of contemporaneous spot and futures returns during periods of contango and backwardation After various robustness checks, the evidence supporting a stronger linkage between spot and futures markets in contango is weak © 2015 Wiley Periodicals, Inc Jrl Fut Mark 36:375–396, 2016

Heston‐Type Stochastic Volatility with a Markov Switching Regime

Abstract: We construct a Heston-type stochastic volatility model with a Markov switching regime to price a plain-vanilla stock option. A semi-analytic solution, which contains a matrix ODE is obtained and numerically calculated. Our model is flexible enough to provide a wide variety of volatility surfaces for the same volatility level but different regimes. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark

Stochastic Skew and Target Volatility Options

Abstract: Target volatility options (TVO) are a new class of derivatives whose payoff depends on some measure of volatility. These options allow investors to take a joint exposure to the evolution of the underlying asset, as well as to its realized volatility. In equity options markets the slope of the skew is largely independent of the volatility level. A single‐factor Heston based volatility model can generate steep skew or flat skew at a given volatility level but cannot generate both for a given parameterization. Since the payoff corresponding to TVO is a function of the joint evolution of the underlying asset and its realized variance, the consideration of stochastic skew is a relevant question for the valuation of TVO. In this sense, this article studies the effect of considering a multifactor stochastic volatility specification in the valuation of the TVO as well as forward‐start TVO. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:174–193, 2016

Empirical Properties, Information Flow, and Trading Strategies of China's Soybean Crush Spread

Abstract: This study examines the empirical properties of soybean, soymeal, and soyoil futures prices at China's Dalian Commodity Exchange. We find that the three series are cointegrated, and that the cointegration relationship is characterized by significant seasonality and consistent time trends. Further, employing a new trivariate VAR-GARCH model, we find evidence of one-way information flow from the soymeal and soyoil markets to the soybean market, but bidirectional information flow and volatility spillover between the soymeal and soyoil markets. Trading simulations based on the mean-reverting tendencies of the cointegration relationship and 5-day averages of the commonly-used spread both generate positive returns. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark

Hedge Ratio Prediction with Noisy and Asynchronous High‐Frequency Data

Abstract: A growing body of literature has focused on the design of covariance estimators for identifying when high‐frequency asset prices are asynchronous and contaminated by microstructure noise. This paper presents a comparison of the prediction ability of covariance estimators within a high‐frequency‐based multivariate volatility model for hedge ratio prediction. Empirical results show that the noise‐free predictions are superior to those contaminated by the noise, with the utility gains being particularly substantial for hedgers with pronounced risk aversion. The results demonstrate the importance of removing microstructure noise and asynchronous trading from covariance estimation to achieve accurate hedge ratio prediction. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:295–314, 2016

Futures Price Response to Crop Reports in Grain Markets

Abstract: The purpose of this study is to investigate the impact of crop reports from U.S. and Brazil on corn and soybean futures markets over the period 2004–2014. A TARCH model with dummy variables to measure the impact of crop reports is used. Results indicate that U.S. reports consistently affect corn and soybean futures price volatility, while Brazilian crop reports' impact on volatility is of smaller magnitude. Further, these impacts are generally found to be stronger when crop reports are released in the months preceding the beginning of harvest. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark

Fat‐Finger Trade and Market Quality: The First Evidence From China

Abstract: More trading is algorithmic or computer generated, and in markets where it is allowed, high frequency. However, what happens when there is an algorithmic trading error? This study attempts to answer that question by examining the August 16, 2013, fat-finger trade in Chinese equity and equity futures markets. We find that both markets were excessively volatile, illiquid, and positively skewed. Moreover, we document that index returns are predictable for a short time, indicating that the fat-finger event induced an inefficient market. Our results highlight the importance of market surveillance and regulation to lessen the damage of future fat-finger events. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:1014–1025, 2016

Empirical Performance of Commodity Pricing Models: When is it Worthwhile to Use a Stochastic Volatility Specification?

Abstract: We compare the empirical pricing performance of three models: a constant volatility model, a two‐factor stochastic volatility model, and a one‐factor stochastic volatility model with a model‐free implied variance specification. Results of applying these models to oil, copper, and gold derivatives are consistent for all commodities and highlight the relative benefits of the different models implying that in choosing the best model to implement in a real situation, careful consideration must be given to the tradeoffs between effort and precision. We believe our results are not only new, but also relevant for practitioners. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:457–487, 2016