The Information Content of Model‐Free Implied Volatility

This study examines the information content of model‐free implied volatility (MFIV) estimates with respect to the options and futures markets in Hong Kong. In this study, the volatility forecasting performance of MFIV is compared, using different prediction horizons, to IV estimates based on Black's futures option pricing model (BIV) and time‐series forecasts based on historical volatility (TS‐HV). The results show that the BIV prediction is unbiased for different horizon forecasts. MFIV outperforms TS‐HV forecasts and, most importantly, BIV subsumes the information content of both MFIV and TS‐HV forecasts. The results are largely maintained for next‐day forecasts but the forecasting quality of the two IV measures declines as expiration day approaches. The information contents of MFIV and TS‐HV forecasts are complementary. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 32:792‐806, 2012     

Return distributions and volatility forecasting in metal futures markets: Evidence from gold,silver, and copper

The characterization of return distributions and forecast of asset‐price variability play a critical role in the study of financial markets. This study estimates four measures of integrated volatility—daily absolute returns, realized volatility, realized bipower volatility, and integrated volatility via Fourier transformation (IVFT)—for gold, silver, and copper by using high‐frequency data for the period 1999 through 2008. The distributional properties are investigated by applying recently developed jump detection procedures and by constructing financial‐time return series. The predictive ability of a GARCH (1,1) forecasting model that uses various volatility measures is also examined. Three important findings are reported. First, the magnitude of the IVFT volatility estimate is the greatest among the four volatility measures. Second, the return distributions of the three markets are not normal. However, when returns are standardized by IVFT and realized volatility, the corresponding return distributions bear closer resemblance to a normal distribution. Notably, the application of financial‐time sampling technique is helpful in obtaining a normal distribution. Finally, the IVFT and realized volatility proxies produce the smallest forecasting errors, and increasing the time frequency of estimating integrated volatility does not necessarily improve forecast accuracy. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:55–80, 2011     

Stock return dynamics,option volume,and the information content of implied volatility

This article reports new empirical results on the information content of implied volatility, with respect to modeling and forecasting the volatility of individual firm returns. The 50 firms with the highest option volume on the Chicago Board Options Exchange between 1988 and 1995 are examined. First, the results indicate that the ability of implied volatility to subsume all relevant information about conditional variance depends on option trading volume. For the most active options in the sample, implied volatility reliably outperforms GARCH and subsumes all information in return shocks beyond the first lag. For these active options, implied volatility performs substantially better than indicated by the prior results of Lamoureux and Lastrapes ( 1993 ), despite significant methodological improvements in the time‐series volatility models in this study including the use of high‐frequency intraday return shocks. For the lower option‐volume firms in the sample, the performance of implied volatility deteriorates relative to time‐series volatility models. Finally, compared to a time‐series approach, the implied volatility of equity index options provides reliable incremental information about future firm‐level volatility. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:615–646, 2003     

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.     

The information content of implied volatility: Evidence from Australia

This study develops an implied volatility index for the Australian stock market, termed as the AVX, and assesses its information content. The AVX is constructed using S&P/ASX 200 index options with a constant time‐to‐maturity of three months. It is observed that the AVX has a significant negative and asymmetric relationship with S&P/ASX 200 returns. When evaluating the forecasting power of the AVX for future stock market volatility, it is found that the AVX contains important information both in‐sample and out‐of‐sample. In‐sample, the AVX significantly improves the fit of a GJR‐GARCH(1, 1) model. Out‐of‐sample, the AVX significantly outperforms the RiskMetrics approach and the GJR‐GARCH(1, 1) model, with its highest forecasting power at the one‐month forecasting horizon. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:134–155, 2010     

Does Index Futures Trading Reduce Volatility in the Chinese Stock Market? A Panel Data Evaluation Approach

This study investigates the effect of introducing index futures trading on the spot price volatility in the Chinese stock market. We employ a recently developed panel data policy evaluation approach (Hsiao, Ching, and Wan, 2011) to construct counterfactuals of the spot market volatility, based mainly on cross‐sectional correlations between the Chinese and international stock markets. This new method does not need to specify a particular regression or a time‐series model for the volatility process around the introduction date of index futures trading, and thus avoids the potential omitted variable bias caused by uncontrolled market factors in the existing literature. Our results provide empirical evidence that the introduction of index futures trading significantly reduces the volatility of the Chinese stock market, which is robust to different model selection criteria and various prediction approaches. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 33:1167–1190, 2013     

The incremental value of a futures hedge using realized volatility

A number of prior studies have developed a variety of multivariate volatility models to describe the joint distribution of spot and futures, and have applied the results to form the optimal futures hedge. In this study, the authors propose a new class of multivariate volatility models encompassing realized volatility (RV) estimates to estimate the risk‐minimizing hedge ratio, and compare the hedging performance of the proposed models with those generated by return‐based models. In an out‐of‐sample context with a daily rebalancing approach, based on an extensive set of statistical and economic performance measures, the empirical results show that improvement can be substantial when switching from daily to intraday. This essentially comes from the advantage that the intraday‐based RV potentially can provide more accurate daily covariance matrix estimates than RV utilizing daily prices. Finally, this study also analyzes the effect of hedge horizon on hedge ratio and hedging effectiveness for both the in‐sample and the out‐of‐sample data. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:874–896, 2010     

Predicting financial volatility: High‐frequency time‐series forecasts vis‐à‐vis implied volatility

Recent evidence suggests option implied volatilities provide better forecasts of financial volatility than time‐series models based on historical daily returns. In this study both the measurement and the forecasting of financial volatility is improved using high‐frequency data and long memory modeling, the latest proposed method to model volatility. This is the first study to extract results for three separate asset classes, equity, foreign exchange, and commodities. The results for the S&P 500, YEN/USD, and Light, Sweet Crude Oil provide a robust indication that volatility forecasts based on historical intraday returns do provide good volatility forecasts that can compete with and even outperform implied volatility. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:1005–1028, 2004     

The limits to stock index arbitrage: Examining S&P 500 futures and SPDRS

This study examines factors affecting stock index spot versus futures pricing and arbitrage opportunities by using the S&P 500 cash index and the S&P 500 Standard and Poor's Depository Receipt (SPDR) Exchange‐Traded Fund (ETF) as “underlying cash assets.” Potential limits to arbitrage when using the cash index are the staleness of the underlying cash index, trading costs, liquidity (volume) issues of the underlying assets, the existence of sufficient time to execute profitable arbitrage transactions, short sale restrictions, and the extent to which volatility affects mispricing. Alternatively, using the SPDR ETF as the underlying asset mitigates staleness and trading cost problems as well as the effects of volatility associated with the staleness of the cash index. Minute‐by‐minute prices are compared over different volatility levels to determine how these factors affect the limits of S&P 500 futures arbitrage. Employing the SPDR as the cash asset examines whether a liquid tradable single asset with low trading costs can be used for pricing and arbitrage purposes. The analysis examines how long mispricing lasts, the impact of volatility on mispricing, and whether sufficient volume exists to implement arbitrage. The minute‐by‐minute liquidity of the futures market is examined using a new transaction volume futures database. The results show that mispricings exist regardless of the choice of the underlying cash asset, with more negative mispricings for the SPDR relative to the S&P 500 cash index. Furthermore, mispricings are more frequent in high‐ and mid‐volatility months than in low‐volatility months and are associated with higher volume during high‐volatility months. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:1182–1205, 2008     

基于高频数据的ARCH类模型波动预测比较分析

Realized Volatility是在高频数据的研究基础上发展起来的度量波动率的新方法。本文以上证综合指数的高频数据为研究对象,采用滚动式样本外一步预测的方法对5种ARCH类模型进行了模型预测能力的比较研究。主要结论有:(1)Realized Volatility作为解释变量加入GARCH模型后能够提高波动预测精度。(2)GARCH-RV的波动预测值为Realized Volatility的无偏估计量。(3)沪市存在波动非对称性与很长的持续性。     

Measuring and forecasting S&P 500 index‐futures volatility using high‐frequency data

In the 24‐hr foreign exchange market, Andersen and Bollerslev measure and forecast volatility using intraday returns rather than daily returns. Trading in equity markets only occurs during part of the day, and volatility during nontrading hours may differ from the volatility during trading hours. This paper compares various measures and forecasts of volatility in equity markets. In the absence of overnight trading it is shown that the daily volatility is best measured by the sum of intraday squared 5‐min returns, excluding the overnight return. In the absence of overnight trading, the best daily forecast of volatility is produced by modeling overnight volatility differently from intraday volatility. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:497–518, 2002     

Reversing the lead,or a series of unfortunate events? NYMEX,ICE, and Amaranth

A number of studies compare the efficiency and transparency of floor trading with automated/electronic trading systems in the competition for order flow. Although most of these studies find that electronic systems lead price discovery, a few studies highlight the weaknesses of electronic trading in highly volatile market conditions. A series of unusual events in 2006, sparking extreme volatility in natural gas futures trading, provide an ideal setting to revisit the resilience of trading system price leadership in the face of high volatility. We estimate time‐varying Hasbrouck‐style information shares to investigate the intertemporal and cross‐sectional dynamics in price discovery. The results strongly suggest that the information share is time‐dependent and contract‐dependent. Floor trading dominates price discovery in the less liquid longer‐maturity contracts, whereas electronic trading dominates price discovery in the most liquid spot‐month contract. We find that the floor trading information share increases significantly with realized volatility. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:1130–1160, 2009     

Volatility,global information,and market conditions: a study in futures markets

This study examined the behavior of return volatility in relation to the timing of information flow under different market conditions influenced by trading volume and market depth. We emphasized information flow during trading and nontrading periods that may represent domestic and offshore information in the global trading of currencies. Test results show that volatility was negatively related to market depth; that is, deeper markets had relatively less return volatility. Additionally, the effect that market depth had on volatility was superseded by information within trading volume. Test results focusing on the timing of information flow reveal that in low‐volume markets, the volatility of nontrading‐period returns exceeded the volatility of trading‐period returns. However, when trading volume was high, this pattern was reversed and conformed to the observations of earlier articles. Our findings proved to be robust across time, different currency markets, and different measures of return volatility. We also observed a trend toward greater integration between foreign and U.S. financial markets; the U.S. market increasingly emphasized information from nontrading periods to supplement information arriving during trading periods. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:173–196, 2001     

RISK HORIZON AND REBALANCING HORIZON IN PORTFOLIO RISK MEASUREMENT

This paper analyzes portfolio risk and volatility in the presence of constraints on portfolio rebalancing frequency. This investigation is motivated by the incremental risk charge (IRC) introduced by the Basel Committee on Banking Supervision. In contrast to the standard market risk measure based on a 10‐day value‐at‐risk calculated at 99% confidence, the IRC considers more extreme losses and is measured over a 1‐year horizon. More importantly, whereas 10‐day VaR is ordinarily calculated with a portfolio’s holdings held fixed, the IRC assumes a portfolio is managed dynamically to a target level of risk, with constraints on rebalancing frequency. The IRC uses discrete rebalancing intervals (e.g., monthly or quarterly) as a rough measure of potential illiquidity in underlying assets. We analyze the effect of these rebalancing intervals on the portfolio’s profit and loss distribution over a risk‐measurement horizon. We derive limiting results, as the rebalancing frequency increases, for the difference between discretely and continuously rebalanced portfolios; we use these to approximate the loss distribution for the discretely rebalanced portfolio relative to the continuously rebalanced portfolio. Our analysis leads to explicit measures of the impact of discrete rebalancing under a simple model of asset dynamics.     

The impact of net buying pressure on index options prices

This study examines whether the demand for options, as measured by the net buying pressure of index options, explains the implied volatility structure created by options prices. We decompose the buying pressure into the direction‐motivated (i.e., delta‐informed) and the volatility‐motivated (i.e., vega‐informed) demand for options. After controlling for options traders' hedging demand, we find that both delta‐ and vega‐informed trading play significant roles in explaining changes in implied volatility. Foreign institutions are more directionally informed in index options trading than their domestic counterparts are. Domestic investors effectively implement volatility trading using put options.     

Stock index futures trading and volatility in international equity markets

This article examines stock market volatility before and after the introduction of equity‐index futures trading in twenty‐five countries, using various models that account for asynchronous data, conditional heteroskedasticity, asymmetric volatility responses, and the joint dynamics of each country's index with the world‐market portfolio. We found that futures trading is related to an increase in conditional volatility in the United States and Japan, but in nearly every other country, we found either no significant effect or a volatility‐dampening effect. This result appears to be robust to model specification and is corroborated by further analysis of the relationship between volatility, trading volume, and open interest in stock futures. An increase in conditional covariance between country‐specific and world returns at the time of futures listing is also documented. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:661–685, 2000     

Subjective Probability Density Functions from FX Option Prices: Predictive Power and Performance on a Carry Trade Strategy

In this article, we extracted the risk‐neutral densities (RNDs) and subjective probability density functions of the US Dollar/Brazilian Real (USD/BRL) exchange rate and evaluated its performance in predicting the future realizations of the USD/BRL exchange rate. The RNDs were estimated using two structural models and three nonstructural models. In the first category, we included the Variance Gamma‐OU model and the CGMY Gamma‐OU model. In the second category, we included the density functional based on confluent hypergeometric function model, the mixture of lognormal distributions model, and the smoothed implied volatility smile. The density functional based on confluent hypergeometric function and the CGMY Gamma‐OU produced 1‐month term densities (RND and subjective probability density function) with the highest forecasting power of the 1‐month USD/BRL exchange rate. Finally, we applied the CGMY Gamma‐OU model to extract a sample of subjective cumulative probabilities of 1‐month USD/BRL movements, and used them as explanatory variables in predictive time series models, whose dependent variable was the 1‐month carry trade return. Its predictive power was then tested and confirmed in three trading strategies that over performed the standard carry trade strategy in terms of annualized cumulative returns.     

隐含波动率的信息含量及其在我国的应用

国内现有关于波动率的研究多集中于时间序列模型,忽略了另一类预测波动率的方法即隐含波动率法。文章在回顾、评述了国内关于波动率的研究后,对国外关于隐含波动率的研究进行了梳理,为在我国大陆地区发展股指期权市场、通过提高期权市场的效率,以运用隐含波动率法更好地预测波动率提供了理论基础和政策建议。     

Volume and Volatility Surrounding Quarterly Redesignation of the Lead S&P 500 Futures Contract

During the last weeks before each quarterly expiration of Standard & Poor's (S&P) 500 futures, the bulk of trading volume begins to shift away from the next‐to‐expire (nearby or lead) contract toward the second‐to‐expire (next out) contract. At some point, the exchange formally redesignates the next out as the new lead contract, and the next out replaces the nearby in the futures pit location designated for the lead contract. This event invariably results in a dramatic increase (decrease) in trading activity in the next out (nearby) contract. This shift in relative trading volumes is due to the microstructure of the futures exchange rather than new information or underlying volatility conditions. The event thus offers us an opportunity to examine how volatility responds to noninformation‐based exogenous changes in volume. This study examines the volatility behavior of nearby and next out S&P 500 futures contracts on the 10 days surrounding quarterly redesignation of the lead contract. Our model measures possible changes in (a) the level of volatility and/or (b) the association between volume and volatility after redesignation of the lead contract. Results indicate that when we account for the association between volume and volatility, the higher volume lead contract consistently experiences a lower level of volatility. This outcome supports the view that the larger population of liquidity providers who trade the more active lead contract fosters greater market depth and lower volatility. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:1119–1149, 2001     

Business Forecasting of Double‐trend Time Series: An Improved PLS‐based Time‐varying Weight Combination Approach

Business forecasting with double‐trend time series (long‐term trends and seasonal volatility) has been challenging due to its complexity. Neither a single time series model nor a fixed‐weight combination approach can fully capture the comprehensive information. We address this issue by proposing an improved partial least squares (PLS) based time‐varying weight combination approach. The proposed method can handle the relations both between the single models involved and between single models and time ordering with time‐varying weights. The test on 20 simulated datasets demonstrates the better and more robust performance of the method. We also apply it to three real datasets. The results show that our approach represents a significant improvement over the existing methods in terms of data fitness and prediction accuracy. Copyright © 2017 ASAC. Published by John Wiley & Sons, Ltd.