中国线材期货价格指数波动率预测能力分析

利用上海期货交易所线材期货15分钟高频价格数据构造已实现波动率估计序列,并以此作为参考标准,运用6种损失函数以及Diebold-Mariano检验法检验4类不同波动率模型对线材期货价格波动的样本外预测能力,显示,中国线材期货市场,基于高频数据的GJR(1,1)模型具有最为出色的波动率预测能力,而在某些损失函数标准下,HYGARCH(1,d,1)与GARCH(1,1)模型也体现出了较好的波动率预测能力。     

VIX futures and its closed‐form pricing through an affine GARCH model with realized variance

This paper studies the forecasting of volatility index (VIX) and the pricing of its futures by a generalized affine realized volatility model proposed by Christoffersen et al. This model is a weighted average of a GARCH and a pure realized variance (RV) model that incorporates each volatility component into the new dynamics. We rewrite the VIX in terms of both volatility components and then derive closed‐form formulas for the VIX forecasting and its futures pricing. Our empirical studies find that a unification of the GARCH and the RV in the modeling substantially improves the forecasting of this index and the pricing of its futures.     

股指期货与股票市场波动性关系的实证研究

以日本的N225指数期货、韩国KOSPI200指数期货和我国台湾地区证交所加权指数(TWSE)期货作为样本,通过GARCH模型的序列建模,从样本总体和分阶段子样本分别对其股指期货推出与股票市场波动性的关系进行实证检验。结果表明,台湾地区的股票市场引入股指期货后现货市场的波动性并未受到影响,而日本和韩国股票市场在引入股指期货之后其波动性加剧,但这种波动性的加剧仅仅是短期性的,长期内并无影响。     

Assessing the asymmetric volatility linkages of energy and agricultural commodity futures during low and high volatility regimes

This study investigated the volatility linkages between energy and agricultural futures, including possible causes for these comovements, such as external macroeconomic and financial shocks during low and high volatility regimes. A combination of Markov-switching regressions and quadrivariate VAR–DCC–GARCH and VAR–BEKK–GARCH modeling revealed that external shocks have an asymmetric effect on the relationship of these assets with higher cross-correlations reported during high volatility regimes. This comovement effect outweighs the substitution effect between energy and agricultural products. Furthermore, the quadrivariate VAR–BEKK–GARCH model provides strong evidence of a bidirectional price volatility spillover between the agricultural and energy markets during periods of high volatility. Overall, the results suggest that energy futures can be effectively used for hedging in a portfolio comprising agricultural futures (and vice versa), while a combination of macroeconomic and financial index futures can serve as an effective hedging tool in investment portfolios comprising both energy and agricultural commodities.     

Samuelson hypothesis,arbitrage activity,and futures term premiums

The Samuelson hypothesis asserts that futures volatility increases as maturity decreases. On the basis of 10 US commodity futures and by capturing the dynamics of the futures volatility terms structure with three factors, we show that in most markets the slope factor is strongly negative in certain periods and at best only weakly negative in other periods. High inventory levels are found to correspond to flatter volatility term structures in seven futures. This finding is consistent with the linkage between carry arbitrage and the Samuelson hypothesis. We also find that a flatter volatility term structure corresponds to lower absolute futures term premiums.     

VIX term structure and VIX futures pricing with realized volatility

Using an extended LHARG model proposed by Majewski et al. (2015, J Econ, 187, 521–531), we derive the closed-form pricing formulas for both the Chicago Board Options Exchange VIX term structure and VIX futures with different maturities. Our empirical results suggest that the quarterly and yearly components of lagged realized volatility should be added into the model to capture the long-term volatility dynamics. By using the realized volatility based on high-frequency data, the proposed model provides superior pricing performance compared with the classic Heston–Nandi GARCH model under a variance-dependent pricing kernel, both in-sample and out-of-sample. The improvement is more pronounced during high volatility periods.     

Volatility of volatility is (also) rough

Using high-frequency data for major volatility indexes, we compute the volatility of volatility and show that its logarithm follows a fractional Brownian motion with Hurst parameter smaller than 1/2 thereby extending to the volatility asset class the recent findings obtained for the equity index markets. The results confirm that the volatility of volatility is a rough process and it possesses the long memory property. We also show that the correlation between the volatility and the volatility of volatility is positive, consistent with observations in the volatility option market. Lastly, a robustness check using volatility futures confirms the findings.     

Forecasting bitcoin volatility: Evidence from the options market

This paper studies a large number of bitcoin (BTC) options traded on the options exchange Deribit. We use the trades to calculate implied volatility (IV) and analyze if volatility forecasts can be improved using such information. IV is less accurate than AutoRegressive–Moving-Average or Heterogeneous Auto-Regressive model forecasts in predicting short-term BTC volatility (1 day ahead), but superior in predicting long-term volatility (7, 10, 15 days ahead). Furthermore, a combination of IV and model-based forecasts provides the highest accuracy for all forecasting horizons revealing that the BTC options market contains unique information.     

Economic uncertainty,trading activity,and commodity futures volatility

This paper investigates the dynamics of commodity futures volatility. I derive the variance decomposition for the futures basis and show unexpected excess returns result from new information about expected future interest rates, convenience yields, and risk premia. Measures of uncertainty in economic conditions have significant predictive power for realized volatility of commodity futures returns, after controlling for lagged volatility, returns, commodity index trading, hedging pressure, and other trading activity, even during the so-called “index financialization” period. During this period, hedge fund performance predicts volatility in grain commodities, which are affected by the US ethanol mandate.     

Can night trading reduce price volatility? Evidence from China's corn and corn starch futures markets

Since 2013, China's futures exchanges have implemented night trading for agricultural futures to reduce the overnight risk and price jump of futures products by extending trading hours. This study uses difference-in-differences (DID) to examine the impacts of night trading on daytime price volatility in corn and corn starch futures markets. On the basis of tick-by-tick data for these futures, we find that night trading has significantly reduced daytime volatility and contributed to price volatility stability in the corresponding futures market. Moreover, we make DID estimations for separate daytime sessions and find that the reduction of the daytime volatility takes place mainly during the first trading session. Robustness and placebo tests further support our main conclusions. Our results provide valuable guidance for futures exchanges and regulators seeking to formulate night trading policies for futures and options.     

Implied volatility forecasts in the grains complex

This article finds that the implied volatilities of corn, soybean, and wheat futures options 4 weeks before option expiration have significant predictive power for the underlying futures contract return volatilities through option expiration from January 1988 through September 1999. These implied volatilities also encompass the information in out‐of‐sample seasonal Glosten, Jagannathan, and Runkle (GJR;1993) volatility forecasts. Evidence also demonstrates that when corn‐implied volatility rises relative to out‐of‐sample seasonal GJR volatility forecasts, implied volatility substantially overpredicts realized volatility. However, simulations of trading rules that involve selling corn option straddles when corn‐implied volatility is high relative to out‐of‐sample GJR volatility forecasts indicate that none of the trading rules would have been significantly profitable. This finding suggests that these options are not necessarily overpriced. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:959–981, 2002     

Natural gas prices and the gas storage report: Public news and volatility in energy futures markets

This study examines the short‐term volatility of natural gas prices through an examination of the intraday prices of the nearby natural gas futures contract traded on the New York Mercantile Exchange. The influence on volatility of what many regard as a key element of the information set influencing the natural gas market is investigated. Specifically, we examine the impact on natural gas futures price volatility of the Weekly American Gas Storage Survey report compiled and issued by the American Gas Association during the period January 1, 1999 through May 3, 2002 and the subsequent weekly report compiled and issued by the U.S. Energy Information Administration after May 6, 2002. We find that the weekly gas storage report announcement was responsible for considerable volatility at the time of its release and that volatility up to 30 minutes following the announcement was also higher than normal. Aside from these results, we document pronounced price volatility in this market both at the beginning of the day and at the end of the day and offer explanations for such behavior. Our results are robust to the manner in which the mean percentage change in the futures price is estimated and to correlation of these changes both within the day and across days. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:283–313, 2004     

我国期货市场的波动性与有效性--基于三大交易市场的实证分析

通过对中国三大期货市场的铜、黄豆和小麦三种主要期货品种收益率的分布与波动性的实证分析 ,论证了其时间序列存在ARCH效应 ;运用GARCH模型对这三种期货品种进行了拟合分析和统计检验 ,检验结果表明这三个期货品种的波动性均具有很高的持续性 ,但大连黄豆的波动持续性弱于上海铜和郑州小麦 ,其波动性受各种外部冲击的影响较大 ;通过GARCH( 1 ,1 )的市场有效性检验 ,论证了中国期货市场尚未达到弱式有效 ,市场风险较大。     

The market quality of commodity futures markets

To study the market quality of commodity futures markets, we construct a commodity futures market quality index from the perspective of liquidity, efficiency, and volatility. Based on the market quality index, the Chinese commodity futures market operates steadily. The metal futures market is more efficient and stable than the market for agricultural futures. The Chinese commodity futures market is less liquid and more volatile than the U.S. market. We examine the determinants of market quality and find that macroeconomic variables and futures market contracts are significantly related to the market quality of Chinese commodity futures.     

Flow toxicity of high-frequency trading and its impact on price volatility: Evidence from the KOSPI 200 futures market

We examine the relation between high-frequency trading, flow toxicity, and short-term volatility during both normal and stressful periods. Using transaction data for the Korea Composite Stock Price Index 200 (KOSPI 200) futures, we find the Volume-Synchronized Probability of Informed Trading (VPIN) useful in measuring flow toxicity as it predicts short-term volatility effectively. We further show that high-frequency trading is negatively related to VPIN and short-term volatility during normal times but has a positive association during stressful periods. Finally, we advocate the use of bulk-volume classification (BVC) by presenting evidence that the initiator identified by BVC trades at more favorable prices than the true trade initiator.     

Causality in the VIX futures market

This study examines the price‐discovery function and information efficiency of a fast growing volatility futures market: the Chicago Board of Option Exchange VIX futures market. A linear Engle–Granger cointegration test with an error correction mechanism (ECM) shows that during the full sample period, VIX futures prices lead spot VIX index, which implies that the VIX futures market has some price‐discovery function. But a modified Baek and Brock nonlinear Granger test detects bi‐directional causality between VIX and VIX futures prices, suggesting that both spot and futures prices react simultaneously to new information. Quarter‐by‐quarter investigations show that, on average, the estimated parameters are not significantly different from zero, thus providing further evidence supporting information efficiency in the VIX futures market. © 2011 Wiley Periodicals, Inc. Jrl Fut Mark     

The information content of implied volatility in agricultural commodity markets

In this article we compare the incremental information content of lagged implied volatility to GARCH models of conditional volatility for a collection of agricultural commodities traded on the New York Board of Trade. We also assess the relevance of the additional information provided by the implied volatility in a risk management framework. It is first shown that past squared returns only marginally improve the information content provided by the lagged implied volatility. Secondly, value‐at‐risk (VaR) models that rely exclusively on lagged implied volatility perform as well as VaR models where the conditional variance is modelled according to GARCH type processes. These results indicate that the implied volatility for options on futures contracts in agricultural commodity markets provides relevant volatility information that can be used as an input to VaR models. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:441–454, 2003     

The short‐time behavior of VIX‐implied volatilities in a multifactor stochastic volatility framework

We consider a modeling setup where the volatility index (VIX) dynamics are explicitly computable as a smooth transformation of a purely diffusive, multidimensional Markov process. The framework is general enough to embed many popular stochastic volatility models. We develop closed‐form expansions and sharp error bounds for VIX futures, options, and implied volatilities. In particular, we derive exact asymptotic results for VIX‐implied volatilities, and their sensitivities, in the joint limit of short time‐to‐maturity and small log‐moneyness. The expansions obtained are explicit based on elementary functions and they neatly uncover how the VIX skew depends on the specific choice of the volatility and the vol‐of‐vol processes. Our results are based on perturbation techniques applied to the infinitesimal generator of the underlying process. This methodology has previously been adopted to derive approximations of equity (SPX) options. However, the generalizations needed to cover the case of VIX options are by no means straightforward as the dynamics of the underlying VIX futures are not explicitly known. To illustrate the accuracy of our technique, we provide numerical implementations for a selection of model specifications.     

Volatility forecasts embedded in the prices of crude-oil options

This paper evaluates the ability of alternative option-implied volatility measures to forecast crude-oil return volatility. We find that a corridor implied volatility measure that aggregates information from a narrow range of option contracts consistently outperforms forecasts obtained by the popular Black–Scholes and model-free volatility expectations, as well as those generated by a realized volatility model. This measure ranks favorably in regression-based tests, delivers the lowest forecast errors under different loss functions, and generates economically significant gains in volatility timing exercises. Our results also show that the Chicago Board Options Exchange's “oil-VIX” index performs poorly, as it routinely produces the least accurate forecasts.     

Volatility and jump risk in option returns

We examine the importance of volatility and jump risk in the time-series prediction of S&P 500 index option returns. The empirical analysis provides a different result between call and put option returns. Both volatility and jump risk are important predictors of put option returns. In contrast, only volatility risk is consistently significant in the prediction of call option returns over the sample period. The empirical results support the theory that there is option risk premium associated with volatility and jump risk, and reflect the asymmetry property of S&P 500 index distribution.