The realized volatility of FTSE‐100 futures prices

Five‐minute returns from FTSE‐100 index futures contracts are used to obtain accurate estimates of daily index volatility from January 1986 to December 1998. These realized volatility measures are used to obtain inferences about the distributional and autocorrelation properties of FTSE‐100 volatility. The distribution of volatility measured daily is similar to lognormal while the volatility time series has persistent positive autocorrelation that displays long‐memory effects. The distribution of daily returns standardized using the measures of realized volatility is shown to be close to normal, unlike the unconditional distribution. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:627–648, 2002     

Do emerging markets become more efficient as they develop? Long memory persistence in equity indices

It seems reasonable to expect financial market efficiency to be related to the economic development level. We study a 16 year sample, covering 22 countries. The Hurst–Mandelbrot–Wallis rescaled range is our efficiency measure, which we apply to returns and volatility. We find strong evidence of long memory persistence in volatility over time, which is unsurprising. However, unlike previous researchers, we could not find evidence of rescaled ranges trending down over time. However, we introduce an alternative measure of economic development, namely, whether FTSE (2011) classify an emerging market as ‘advanced’ or ‘secondary’. This measure shows greater efficiency in returns and volatility for ‘advanced’ emerging markets.     

Pricing Stock Options in a Jump‐Diffusion Model with Stochastic Volatility and Interest Rates: Applications of Fourier Inversion Methods

Fast closed form solutions for prices on European stock options are developed in a jump‐diffusion model with stochastic volatility and stochastic interest rates. The probability functions in the solutions are computed by using the Fourier inversion formula for distribution functions. The model is calibrated for the S and P 500 and is used to analyze several effects on option prices, including interest rate variability, the negative correlation between stock returns and volatility, and the negative correlation between stock returns and interest rates.     

股市收益和波动性长期记忆的国际比较——基于V/S的经验证据

现有研究运用经典和修正R/S分析探讨我国股票市场的长期记忆效应。本文运用更为稳健的V/S分析,对比研究上证股市和另外7个国家和地区的股票市场,分别诊断各股市日收益和周收益、及三种典型度量的收益波动的长期记忆效应。研究表明:股市日收益和周收益序列都不存在显著的长期记忆;三种典型度量的收益波动普遍存在显著的长期记忆;日收益波动比周收益波动的长期记忆更显著。     

Realized volatility and correlation in energy futures markets

Using high‐frequency returns, realized volatility and correlation of the NYMEX light, sweet crude oil, and Henry‐Hub natural gas futures contracts are examined. The unconditional distributions of daily returns and daily realized variances are non‐Gaussian, whereas the distributions of the standardized returns (normalized by the realized standard deviation) and the (logarithms of) realized standard deviations appear approximately Gaussian. The (logarithms of) standard deviations exhibit long‐memory, but the realized correlation between the two futures does not, implying rather weak inter‐market linkage in the long run. There is evidence of asymmetric volatility for natural gas but not for crude oil futures. Finally, realized crude oil futures volatility responds with an increase in the weeks immediately before the OPEC events recommending price increases. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:993–1011, 2008     

The Breakdown of Idiosyncratic Volatility Into Expected and Unexpected Components and Its Effects on Stock Returns in Brazil

Based on studies of idiosyncratic volatility developed in the recent literature, this study analyzes its relation with expected returns through the breakdown of idiosyncratic volatility in the Brazilian stock market and presents evidence of the importance of expected idiosyncratic volatility for asset pricing. We study the impact of the expected and unexpected components of idiosyncratic volatility on the returns of shares listed on the BOVESPA between 2004 and 2011. The results show a strong positive and significant relation between expected idiosyncratic volatility and returns. This evidence is highlighted when we use unexpected idiosyncratic volatility to control for unexpected returns. Additional robustness tests, controlling for size and momentum effects, also have positive and significant coefficients, corroborating previous findings.     

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     

Asymmetric pricing of implied systematic volatility in the cross‐section of expected returns

Assuming a symmetric relation between returns and innovations in implied market volatility, Ang, A., Hodrick, R., Xing, Y., and Zhang, X. (2006) find that sensitivities to changes in implied market volatility have a cross‐sectional effect on firm returns. Dennis, P., Mayhew, S., and Stivers, C. (2006), however, find an asymmetric relation between firm‐level returns and implied market volatility innovations. We incorporate this asymmetry into the cross‐sectional relation between sensitivity to volatility innovations and returns. Using both portfolio sorting and firm‐level regressions, we find that sensitivity to VIX innovations is negatively related to returns when volatility is rising, but is unrelated when it is falling. The negative relation is robust to controls for other variables, suggesting only the increase in implied market volatility is a priced risk factor. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:34–54, 2011     

Market volatility and the demand for hedging in stock index futures

This study examines the relation between stock market volatility and the demand for hedging in S&P 500 stock index futures contracts. Open interest is used as a proxy for hedging demand. The analysis employs unique data that identify separately the open interest of large hedgers, large speculators, and smaller traders. Volatility estimates are decomposed into expected and unexpected components, to assess whether traders’ reactions to volatility depend upon its predictability. Results indicate that daily open interest for hedgers increases when unexpected volatility increases. Increases in unexpected volatility may cause hedgers to raise their estimates of future expected volatility, and hence increase their demand for hedging. Open interest of speculators is not related to expected volatility, and is only weakly related to unexpected volatility. The increase in the participation of hedgers in periods of higher volatility is significantly larger than the increase in the participation of speculators. The results suggest that increases in stock market volatility increase the demand for hedging. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20: 105–125, 2000     

Risk substitution in cryptocurrencies: Evidence from BRICS announcements

We investigate the impact of BRICS regulatory announcements on cryptocurrency volatilities and returns. Results evidence risk substitutions after announcements moving from ETH, XRP and LTC to BTC and vice versa, with BTC having volatility reactions to regulatory announcements that differ from those of other cryptocurrencies. Bootstrap quantile regression indicates a stronger detrimental impact of announcements when BTC is currently manifesting lower volatility and higher daily returns. Robustness checks confirm our findings, as well as evidence that the cryptocurrencies in our sample are considerably more reactive to BRICS announcements than US Fed announcements, suggesting important linkages between emerging markets and cryptocurrencies.     

Intraday Volatility in Interest‐Rate and Foreign‐Exchange Markets: ARCH,Announcement, and Seasonality Effects

We explore the determinants of intraday volatility in interest‐rate and foreign‐exchange markets, focusing on the importance and interaction of three types of information in predicting intraday volatility: (a) knowledge of recent past volatilities (i.e., ARCH or Autoregressive Conditional Heteroskedasticity effects); (b) prior knowledge of when major scheduled macroeconomic announcements, such as the employment report or Producer Price Index, will be released; and (c) knowledge of seasonality patterns. We find that all three information sets have significant incremental predictive power, but macroeconomic announcements are the most important determinants of periods of very high intraday volatility (particularly in the interest‐rate markets). We show that because the three information sets are not independent, it is necessary to simultaneously consider all three to accurately measure intraday volatility patterns. For instance, we find that most of the previously documented time‐of‐day and day‐of‐the‐week volatility patterns in these markets are due to the tendency for macroeconomic announcements to occur on particular days and at particular times. Indeed, the familiar U‐shape completely disappears in the foreign‐exchange market. We also find that estimates of ARCH effects are considerably altered when we account for announcement effects and return periodicity; specifically, estimates of volatility persistence are sharply reduced. Separately, our results show that high volatility persists longer after shocks due to unscheduled announcements than after equivalent shocks due to scheduled announcements, indicating that market participants digest information much more quickly if they are prepared to receive it. However, contrary to results from equity markets, we find no evidence of a meaningful difference in volatility persistence after positive or negative price shocks. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21: 517–552, 2001     

Cross‐market correlations and transmission of information

We investigate characteristics of cross‐market correlations using daily data from U.S. stock, bond, money, and currency futures markets using a new multivariate GARCH model that permits direct hypothesis testing on conditional correlations. We find evidence that arrival of information in a market affects subsequent cross‐market conditional correlations in the sample period following the stock market crash of 1987, but there is little evidence of such a relationship in the precrash period. In the postcrash period, we also find evidence that the prime rate of interest affects daily correlations between futures returns. Furthermore, we find that conditional correlations between currency futures and other markets decline steeply a few months before the crash and revert to normal dynamics after the crash. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:1059–1082, 2002     

Timing the Market with a Combination of Moving Averages

A combination of simple moving average trading strategies with several window lengths delivers a greater average return and skewness as well as a lower variance and kurtosis compared with buying and holding the underlying asset using daily returns of value‐weighted US decile portfolios sorted by market size, book‐to‐market, momentum, and standard deviation as well as more than 1000 individual US stocks. The combination moving average (CMA) strategy generates risk‐adjusted returns of 2% to 16% per year before transaction costs. The performance of the CMA strategy is driven largely by the volatility of stock returns and resembles the payoffs of an at‐the‐money protective put on the underlying buy‐and‐hold return. Conditional factor models with macroeconomic variables, especially the market dividend yield, short‐term interest rates, and market conditions, can explain some of the abnormal returns. Standard market timing tests reveal ample evidence regarding the timing ability of the CMA strategy.     

中国开放式基金收益及其波动性的周内效应研究

了解基金收益及其波动性是否存在周内效应对投资者非常重要,投资者可以利用收益及其波动性的变动信息调整投资组合,增加投资收益。运用均值方程含有虚拟变量的GARCH(1,1)模型和条件方差方程含有虚拟变量的修正的GARCH(1,1)模型,我们分别对2003年6月1日至2005年8月18日期间中国开放式基金收益的周内效应和收益波动性的周内效应进行实证研究,结果显示,在研究期间内样本基金收益及收益的波动性在周三这一天显著不同于其他交易日,即存在“周三效应”。     

Military regimes and stock market performance

We examine whether military regimes harm stock market performance by investigating stock returns in ten emerging markets under military and civilian rule. We find no evidence of military regimes having a significantly negative impact on stock returns. In the case of Thailand and Pakistan, we find a significant positive military return premium. These returns cannot be explained by economic cycles, stock market cycles, or returns volatility. Our findings are robust to worldwide stock market movements, tests for spurious regression bias and randomization-bootstrap tests. Our results contradict the common view that military rule has a negative impact on stock market performance.     

Asymmetrical reaction to US stock-return news: evidence from major stock markets based on a double-threshold model

This paper examines the hypothesis that both stock returns and volatility are asymmetrical functions of past information from the US market. By employing a double-threshold GARCH model to investigate six major index-return series, we find strong evidence supporting the asymmetrical hypothesis of stock returns. Specifically, negative news from the US market will cause a larger decline in a national stock return than an equal magnitude of good news. This holds true for the volatility series. The variance appears to be more volatile when bad news impacts the market than when good news does.     

FX Market Returns and Their Relationship to Investor Fear

This note examines the relationship between changes in levels of investor fear (measured by the implied volatility index) and foreign exchange market returns. Our empirical results indicate a negative relationship between daily returns on high‐interest rate (investing) currencies and changes in the implied volatility index, while the association is positive for low‐interest rate (funding) currencies. That is, investing (funding) currencies tends to depreciate (appreciate) when investor fear increases. A sequential breakpoint test identifies a significant change in this relationship in the period following the 2008 collapse of Lehman Brothers, and another in 2012 following the resolution of the European sovereign debt crisis, which suggests that the relationship is linked to financial system liquidity. During the crisis period, currency returns are much more sensitive to changes in investor fear, and this is particularly so for funding currencies that are perceived to present a safe‐haven. The results have important implications for international finance, and those looking to speculate via the carry trade.     

Clustering in the futures market: Evidence from S&P 500 futures contracts

We document trade price clustering in the futures markets. We find clustering at prices of x.00 and x.50 for S&P 500 futures contracts. While trade price clustering is evident throughout time to maturity of these contracts, there is a dramatic change when the S&P 500 futures contract is designated a front‐month contract (decrease in clustering) and a back‐month contract (increase in clustering). We find that trade price clustering is a positive function of volatility and a negative function of volume or open interest. In addition, we find a high degree of clustering in the daily opening and closing prices, but a lower degree of clustering in the settlement prices. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:413–428, 2004     

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     

Did Investors Herd during the Financial Crisis? Evidence from the US Financial Industry

We examine the herding behavior of investors in the US financial industry, especially commercial banks, S&Ls, investment and insurance firms during global financial crisis of 2008 towards own sub‐sector and market consensus using augmented cross sectional absolute deviation of returns (CSAD) model. After distinguishing between fundamental and non‐fundamental information, we find a greater influence of global financial crisis on spurious herding for commercial and investment banks, and such herding increases in the down market and with conditional volatility of returns, but adverse herding is prevalent among investors during normal period in response to fundamental information. We also find that herding intensity on fundamental information is relatively high with market consensus for all financial institutions except insurance firms in high volatility regime, and intentional herding is only significant and limited to S&Ls and investment banks in high volatility regime. Our findings suggest limited spillover effects of herding when investors face non‐fundamental information.