Exchange traded funds: leverage and liquidity

This paper examines the differences between leveraged and unleveraged Exchange Traded Funds (ETFs), particularly for liquidity and volatility characteristics. The impact of leverage on intraday liquidity (spread and depth) is analysed in two periods – one of normal volatility and the other of abnormal/high volatility. There is a significant difference in spread and depth of leveraged and unleveraged ETFs in periods of both normal volatility and high volatility; however, this difference is more pronounced in higher volatility periods. In high volatility periods, liquidity typically diminishes in all ETFs, and this is even more so for the leveraged ETFs. When leveraged ETFs are segregated into multiples based on their power to replicate the underlying benchmark (i.e. multiples of ?3, ?2, ?1, 2, 3), the difference in spreads between normal and high volatility periods is typically larger. The double-leveraged ETF has the most significant difference between the positive and negative counter parts. However, the relationship in the progression of the multiples does not change linearly to correspond with the level of volatility. This may be due to the nonlinear relation between volume and volatility. We shed light on the magnification effect of financial leverage on microstructure of the ETFs.     

Short selling and exchange-traded funds returns: evidence from the London Stock Exchange

An exchange-traded fund (ETF) is a security that tracks a basket of stocks. An ETF investor gains immediate exposure to the basket, by taking either a long or short position on this instrument. Both hedgers and speculators can short ETFs, making the informational content of increases in ETF short interest difficult to interpret. Using high-frequency (daily) short-interest data for ETFs traded on the London Stock Exchange between June 2006 and April 2010, we examine the price impact on ETFs of increases in short interest. Contrary to most of the previous empirical evidence for individual stocks, we find that large increases in ETF short interest are associated with subsequent over-performance relative to a benchmark index and this pattern is most pronounced during pre-financial crisis period.     

An analysis of the spillover effects of exchange-traded funds

This article used the Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (GARCH-ARMA) and the exponentially Generalized Autoregressive Conditional Heteroscedasticity-Autoregressive Moving Average (EGARCH-ARMA) models to study the impact of the spillover and the leverage effects on returns and volatilities of stock index and Exchange Trade Fund (ETF) for developed and emerging markets. Previous unexpected returns for developed and emerging markets which have an opposite influence pattern on ETFs’ returns were identified. The spillover effects from returns are excellent for Hong Kong, followed by Singapore. Meanwhile, Taiwan's stock index return was recorded to have a strong negative impact on ETF return. Notably, this article shows that the spillover effects on stock index and ETF volatilities existed with bilateral influences. Despite a strong positive asymmetric volatility effect in Korea's ETF market, the leverage effect appears to play important roles in the explanation of both stock index and ETF returns.     

Where does return and volatility come from? The case of Asian ETFs

We analyze return and volatility of Asian iShares traded in the U.S. The difference in trading schedules between the U.S. and Asia offers a unique market setting that allows us to distinguish various return and volatility sources. We find Asian ETFs have higher overnight volatility than daytime volatility, explained by public information released during each local market's trading session. Local Asian markets also play an important role in determining each Asian ETF return. Nonetheless, returns for these funds are highly correlated with U.S. markets, indicative of the effects of investor sentiment and location of trade. Finally, returns in the U.S. market Granger-cause returns in all six Asian markets are analyzed.     

Overreaction of Exchange-Traded Funds During the Bubble of 1998-2002

This study of overreaction is motivated by the unique characteristics of exchange-traded funds (ETFs), which should contribute to market efficiency. Since ETFs represent portfolios of stocks, they may not be as susceptible to short-term overreaction as individual stocks. In addition, they can be traded throughout the day and can be sold short, which might further limit potential overreaction. Yet, the tradability of ETFs may allow unusual pressure on ETF prices that is not initiated by price movements of all the component stocks. We find substantial overreaction of ETFs during normal trading hours (9:30 a.m. to 4 p.m.) and after hours, which presents opportunities for feedback traders. Extreme price movements of ETFs occur more frequently after hours. Yet, the after-hours correction of extreme price movements that occurred that day is more pronounced than the day correction of extreme stock price movements that occurred in the previous after-hours period, even after controlling for ETF type and other potential confounding effects. The degree of overreaction is also more pronounced for international ETFs.     

沪深300指数期货与现货的相互引导关系研究

沪深300指数期货是中国证券市场上目前唯一的一款股指期货产品,通过Granger因果检验、向量误差修正模型、脉冲响应与方差分解等计量方法对其日交易数据的实证研究表明:沪深300指数期货、现货市场价格是协整的,且二者存在双向引导关系;沪深300指数期货市场对长期均衡偏离的调整力度更强,调整速度更快,对信息反应的效率更高,但在短期波动影响中,指数期货、现货市场总方差中来自期货市场的平均贡献为47.52%,来自现货市场的平均贡献为52.48%,指数现货市场对新信息融入的贡献度更高,其冲击对期货、现货市场的影响也更强烈、更持久。     

Performance and diversification benefits of foreign-equity ETFs in emerging markets

This study provides a comprehensive review of the risk-return characteristics, performance and international diversification benefits of an uncharted fast-growing segment of the global exchange-traded fund (ETF) market by examining 17 foreign-equity ETFs traded in 6 emerging markets. The results indicate that the sample ETFs domiciled in these economies perform poorly providing relatively low returns while exposing emerging market investors to substantial total and systematic risks. In addition, these ETFs are found to be more sensitive to downside risk, making them relatively more vulnerable to market downturns. Although the foreign-equity ETFs are designed to provide investors with full international diversification benefits, we find that they are significantly affected by their local market conditions and sentiments, making them ineffective international diversification tools.     

Small trades and volatility increases after stock splits

In this paper, we examine the trading activity and return volatility pattern before and after splits. Unlike previous studies, we employ high-frequency transaction data and more powerful asymptotical tests on the impact of split on volatility. Furthermore, we examine the relationship between volatility and volume using different volatility measures and controlling for the effects of autocorrelation and trading costs. We find that small trades increase significantly after stock splits and the increase in return volatility is strongly related to the increase in small trades after stock splits. The results support our contention that the post-split volatility increase is driven primarily by the trading activity of smaller noise investors. Test results are robust to different measures of trading activity and return volatility.     

Disagreement and the risk-return relation

Disagreement is an important behavioral factor in financial market, and this paper investigates the impact of disagreement on the risk-return relation. We construct disagreement of crowded trades (DCT) index to measure disagreement, and discover that DCT has a significant impact on the risk-return relation. Furthermore, DCT change has a time-varying effect on the risk-return relation. When DCT change is negative, the risk-return relation is significant and negative; when DCT change is positive, the risk-return relation is significantly positive. When we use different conditional variance models and different market portfolios, such results are still robust. Moreover, our empirical results have important practical implications for asset allocation decisions.     

Short-term investment and equilibrium multiplicity

I study the effects of the heterogeneity of traders’ horizons in a 2-period NREE model where all traders are risk averse. Owing to risk premia, short-termism generates multiple equilibria. In particular two distinct patterns arise. Along the “low trading intensity equilibrium,” short termists anticipate a thinner second period market and, owing to risk aversion, scale back their trades. This reduces both risk sharing and information impounding into prices, enforcing a high returns’ volatility-low price informativeness equilibrium. Along the “high trading intensity equilibrium,” the opposite happens and a low volatility-high price informativeness equilibrium arises. Thus, in the presence of short-term behavior and traders’ risk aversion, periods of high volatility are a signal of poor price informativeness.     

Prediction of volatility based on realized-GARCH-kernel-type models: Evidence from China and the U.S.

We propose three Realized-GARCH-Kernel-type models which do not make the distribution assumptions on the return disturbance terms. We use this type of model to predict the return volatilities of the 50ETF in China and the S&P500 index in the U.S. The semiparametric kernel density estimator of our models, which captures the skewness, asymmetry and fat-tail of financial assets, performs well both statistically and economically. Our models have more predictive power than other eight comparable volatility models that need to pre-specify the distribution of the disturbance terms. Our results are robust to eight measures of realized volatility. Using option straddle strategies, we show that our models generate larger trading profits and greater Sharpe ratios than the other competing models.     

OTC trades and liquidity in the European carbon market more than meets the eye

ABSTRACT

This study investigates whether the previously reported price impact of OTC trades in the EU ETS can be attributed to their distinctively larger size (liquidity related) or to their discretionary feature (information related). The findings suggest that OTC trades induce volatility shocks that are higher in magnitude and faster resolved than those of solely high trading-intensity trades, which appears to be driven mainly by their presence, rather than by their size. An analysis of intraday price premia reveals that they are strategically placed by interacting with the organized market whenever their price and volatility impact is lower.     

The intraday relation between return volatility, transactions, and volume

In this article, we examine the relation between return volatility, average trade size, and the frequency of transactions using transaction data. Consistent with Jones, Kaul, and Lipson (1994)(. Review of Financial Studies, 7, 631–651), our results show that the frequency of trades has a high explanatory power for return volatility. However, contrary to their finding, we find that average trade size contains nontrivial information for return volatility. The positive relation between return volatility and average trade size is more significant for actively traded stocks. Furthermore, return volatility exhibits significant intraday variations. It is found that the effect of trade frequency on return volatility is much stronger in the opening trading period.     

Do different time horizons in the volatility of the US stock market significantly affect the China ETF market?

This article investigates the linear, nonlinear and time-varying Granger causality between different time horizons in the volatility of US stock market and the China Exchange-Traded Fund (ETF) market. We find evidence of linear causality from the US stock market to the China ETF market, with a bilateral nonlinear causal relationship in the longer term. Bootstrap rolling causality analysis indicates high rejection rates of a noncausal relationship running from the US stock market to the China EFT market. The causality linkage from the China ETF market to the US stock market was determined to be time-horizon-dependent, and the null hypothesis rejection rate of non-Granger causality increased in the longer term.     

Realized volatility transmission: The role of jumps and leverage effects

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.     

TRADER TYPE EFFECTS ON THE VOLATILITY‐VOLUME RELATIONSHIP EVIDENCE FROM THE KOSPI 200 INDEX FUTURES MARKET

We investigate whether the trading activity generated by investors with different access to information and trading motives has positive or negative impact on index futures volatility. Surprises in non‐member institutional, individual and foreign investors' trading volume are positively associated with volatility in most of the cases. For member institutional investors, unexpected trading volume is positively related to volatility. Long‐run changes in the trading activity also affect volatility differently across trader types. Finally, allowing for time‐to‐maturity effects, surprises in open interest are associated with more volatility towards contract expiration, contrary to the negative effect we find during normal times.     

Optimal gasoline hedging strategies using futures contracts and exchange-traded funds

This article employs a variety of econometric models (including OLS, VEC/VAR, DCC GARCH and a class of copula-based GARCH models) to estimate optimal hedge ratios for gasoline spot prices using gasoline exchange-traded funds (ETFs) and gasoline futures contracts. We then compare their performance using four different measures from the perspective of both their hedging objectives and trading position using four different measures: variance reduction measure, utility-based measure and two tail-based measures (value at risk and expected shortfall). The impact of the 2008 financial market crisis on hedging performance is also investigated. Our findings indicate that, in terms of variance reduction, the static models (OLS and VEC/VAR) are found to be the best hedging strategies. However, more sophisticated time-varying hedging strategies could outperform the static hedging models when the other measures are used. In addition, ETF hedging is a more effective hedging strategy than futures hedging during the high-volatility (crisis) period, but this is not always the case during the normal time (post-crisis) period.     

Coordination and correlation in Markov rational belief equilibria

Summary This paper studies the effect of correlation in the rational beliefs of agents on the volatility of asset prices. We use the technique of generating variables to study stable and non-stationary processes needed to characterize rational beliefs. We then examine how the stochastic interaction among such variables affects the behavior of a wide class of Rational Belief Equilibria (RBE). The paper demonstrates how to construct a consistent price state space and then shows the existence of RBE for any economy for which such price state space is constructed. Next, the results are used to study the volatility of asset prices via numerical simulation of a two agents model. If beliefs of agents are uniformly dispersed and independent, we would expect heterogeneity of beliefs to have a limited impact on the fluctuations of asset prices. On the other hand, our results show that correlation across agents can have a complex and dramatic effect on the volatility of prices and thus can be the dominant factor in the fluctuation of asset prices. The mechanism generating this effect works through the clustering of beliefs in states of different levels of agreement. In states of agreement the conditional forecasts of the agents tend to fluctuatetogether inducing more volatile asset prices. In states of disagreement the conditional forecasts fluctuatein diverse directions tending to cancel each other's effect on market demand and resulting in reduced price volatility.This research was supported, in part, by the Fondazione Eni Enrico Mattei of Milan, Italy, and by the Research Incentive Fund of Stanford University. The authors thank Carsten K. Nielsen and Ho-Mou Wu for valuable discussions on an earlier draft. Carsten K. Nielsen also made an important contribution to the development of Section 3.     

A three-objective social welfare function for cost–benefit analysis

This article applies quantile regression to assess the factors that influence the risk of incurring high trading costs. Using data on the equity trades of the world's second largest pension fund in the first quarter of 2002, we show that trade timing, momentum, volatility and the type of broker intermediation are the major determinants of the risk of incurring high trading costs. Such risk is increased substantially by either high or low momentum and by strong volatility. Moreover, agency trades are substantially more risky in terms of trading costs than similar principal trades. Finally, we show that the quantile regression model succeeds well in forecasting future trading costs.     

Intraday price information flows between the CSI300 and futures market: an application of wavelet analysis

This study investigates linear and nonlinear price information flows between the Chinese Stock Index 300 (CSI300) and futures market using high-frequency data and their wavelet transformed series for three regimes for which stock short-selling restrictions in China are different. Empirical results generally indicate information feedback between these two markets regardless of assumptions of linear and nonlinear causality and regimes for original series and wavelet transformed data at different scales.