Search results

Prior literature has shown that, theoretically, holding-period returns of a leveraged exchange-traded fund (LETF) are generally negatively affected by the volatility of the underlying benchmark’s daily returns, particularly for long holding periods. However, recent empirical studies simulate LETFs’ returns using historical benchmark returns and report results that are not entirely consistent with the theoretical predictions, leading to the possibility that the distribution of real-world returns may have certain characteristics that influence the outcomes. In this paper, the authors examine how asymmetric volatility affects LETFs’ performance and provide detailed explanations for the behavior of the performance of LETFs under different market conditions.

The authors conduct simulation analyses on a +3x LETF and a −3x LETF based on historical S&P 500 stock index returns, with asymmetric volatility incorporated into the model.

By incorporating the asymmetric volatility effect, the simulation results suggest that, contrary to the theoretical predictions, higher volatility does not always lead to more negative impact on LETFs’ performance. Rather, the performance depends on the market conditions under which high volatility occurs. The findings therefore help reconcile prior theoretical predictions with reported empirical findings.

The analysis adds to the literature by incorporating the asymmetric volatility effect of stock returns in studying LETFs’ performance. The authors also provide detailed explanations for the behavior of LETFs’ returns and compounding effect under different market conditions, thus providing contexts to prior empirical results.

The purpose of this paper is to provide a brief review of three strands of the literature on exchange‐traded funds.

The paper starts with a review of the history of the growth of exchange‐traded funds and their characteristics. The paper then examines the key factors and findings of the existing studies on, respectively, the pricing efficiency, the tracking ability/performance, and the impact on underlying securities of exchange‐traded funds.

Although there has been a substantial amount of research conducted to advance our knowledge on the trading, management, and effect of exchange‐traded funds, the findings are still far from conclusive in addressing a number of research questions.

Investors and other market participants will find this review informative in enhancing the understanding of exchange‐traded funds.

By highlighting the general theme of the related research findings, the paper provides a systematic review of the existing literature that future researchers can utilize in developing their research agenda.

In response to common criticisms on the appropriateness of mean-variance in asset allocation decisions involving hedge funds, we offer a mean-Gini framework as an alternative. The mean-Gini framework does not require the usual normality assumption concerning return distributions. We also evaluate empirically the differences in allocation outcomes between the two frameworks using historical data. The differences turn out to be significant. The evidence thus confirms the inappropriateness of the mean-variance framework and enhances the attractiveness of mean-Gini for this asset class.

The aim of this paper is to examine the informational efficiency of prices of all exchange traded funds (ETFs) that are actively traded on the NYSE Arca, based on methodology developed by Chordia et al.

The authors estimate the speed of convergence to market efficiency based on short‐horizon return predictability from past order flows of 273 ETFs that were traded every day on the NYSE Arca during the first six months of 2008, and compare the resulting price formation process to that of shares traded on the NYSE and NYSE Arca.

Despite the significant differences in trading costs, volatility, and informational effects between ETFs and regular stocks, the paper documents that price adjustments to new information for ETFs occur in about 30 minutes, which is comparable to price adjustments for traditional stocks traded on Arca. In multivariate setting, the paper further shows that the speed of convergence to market efficiency of ETFs is not only significantly driven by volume, but also by the probability of informed trading.

The findings provide direct answers and insights to questions posed in a recent SEC concept release document. The analysis of the speed of convergence provides a feasible measure to assess how efficiently prices of ETFs respond to new information.

The authors are first to utilize the short‐horizon return predictability from historical order flow approach to evaluate the price formation process of ETFs and to provide evidence on the determinants of its efficiency.

Leveraged and inverse ETFs (hereafter leveraged ETFs) have received much press coverage of late due to issues with their performance. Managers and the media have focused investors' attention on the impact of compounding, when the funds are held for more than one day. The aim of this paper is to lay out a framework for assessing the performance of leveraged ETFs.

The authors propose a simple way to disentangle the effect of compounding and that of the management of the fund and the trading premiums/discounts, all of which affect investors' bottom line. The former is influenced by the effectiveness and the costs of the manager's (synthetic) replication strategy and the use of leverage. The latter reflects liquidity and the efficiency of the market.

The paper finds that tracking errors were not caused by the effects of compounding alone. Depending on the fund, the impact of management factors can outweigh the impact of compounding, and substantial premiums/discounts caused by reduced liquidity during the financial crisis further distorted performance.

The authors propose a framework for practitioners to evaluate the performance of leveraged ETFs. This framework highlights a very topical issue, that of the impact of synthetic replication, which all leveraged ETFs use. Financial regulators such as the SEC and the Financial Stability Board have all taken issue with synthetically replicated ETFs. In leveraged ETFs, this issue is masked by the effects of compounding. The framework the authors propose allows investors to disentangle the two effects.

Real estate investment has been generally accepted as a value-adding proposition for a portfolio investor. Such an impression is not only shared by investment professionals and financial advisors but also appears to be supported by an overwhelming amount of research in the academic literature. The benefits of adding real estate as an asset class to a well-diversified portfolio are usually attributed to the respectable risk-return profile of real estate investment together with the relatively low correlation between its returns and the returns of other financial assets. By using the regime-switching technique on an extensive historical dataset, we attempt to look for the statistical evidence for such a claim. Unfortunately, the empirical support for the claim is neither strong nor universal. We find that any statistically significant improvement in risk-adjusted return is very much limited to the bullish environment of the real estate market. In general, the diversification benefit is not found to be statistically significant unless investors are relatively risk averse. We also document a regime-switching behavior of real estate returns similar to those found in other financial assets. There are two distinct states of the real estate market. The low-return (high-return) state is characterized by its high (low) volatility and its high (low) correlations with the stock market returns. We find this kind of dynamic risk characteristics to play a crucial role in dictating the diversification benefit from real estate investment.

The purpose of this study is to extend the work of DeFusco, Ivanov and Karels by examining pricing deviation of DIA, SPY and QQQQ on intradaily basis.

The DIA is designed to be one hundredth of the DJIA, the SPY is designed to be one tenth of the S&P 500 and QQQQ is designed to be one fortieth of the NASDAQ 100. This feature of ETFs requires the estimation of the difference between the proportional level of the index and the price of the ETF, which is the ETF pricing deviation.

The paper finds that the DIA, SPY and QQQQ pricing deviations are 0.0429, −0.0743 and 0.4298, respectively. The findings indicate that the prices of DIA and QQQQ are on average lower than the underlying indexes. SPY is the exception having a price which is higher than the theoretical price of the S&P 500 index. The author finds that this is due to the increased demand for the SPY. Additionally, the paper provides an explanation for the large change (increase) in the pricing deviation of QQQQ after December 1, 2004 which DeFusco, Ivanov and Karels could not explain. On December 1, 2004 QQQQ trading was consolidated on NASDAQ. The paper finds negative growth in the volume of QQQQ after December 1, 2004 indicating decrease in popularity of this ETF. The decrease in popularity of QQQQ might explain the increase in its pricing deviation.

The paper uses high frequency data in the analysis of pricing deviation which might be artificially deflating standard errors and thus inflating the t‐test significance values.

The paper contributes to the ongoing search in the finance literature of precision ETF performance metrics.

The purpose of this paper is to investigate the extent to which introduction of ETFs reduces short‐sale constraints in their constituent stocks.

First, the introduction of ETFs increases short interest for stocks that they hold. Second, the increase in short interest is highest for the stocks that were most short‐sale constrained. Third, subsequent additions of a stock to an ETF will have a lesser impact on short interest than the first time additions. Finally, using matched control sample and regression analysis approaches, the authors make sure that their results are robust to determinants of short‐selling activity which extant research has found to be relevant.

When a stock is included in an ETF for the first time, the paper finds that the average monthly short‐selling activity of the stock in the six months following ETF‐inclusion is, on average, 33 percent higher than that in six months prior to the inclusion. This effect is the strongest for stocks that are most short‐sale constrained. The analysis of subsequent additions of stocks to ETFs reveals that the effect of increased short‐selling activity is significantly attenuated when compared to the first‐time additions. All of the findings are robust to the matched sample comparisons and multiple regression analysis that account for determinants of short‐selling activity.

This paper shows that: the introduction of ETFs helps relax short‐sale constraints in the market; that the extent to which a stock's outstanding shares are held by one or more ETFs serves as a proxy for the degree to which stocks are short‐sale constrained; and implies that the introduction of ETFs makes the prices of the funds' underlying securities more efficient.

Using a market model of international equity returns, which fully incorporates the regime switching and heteroskedasticity effects, we conduct an empirical study on the asymmetric behavior of 31 emerging equity markets across the different regimes of both the global and the local markets. Asymmetric correlation is found to be much weaker than that among developed markets as documented in the recent studies. There is little evidence of performance enhancement by possessing information on asymmetric correlation in international asset allocation strategies involving emerging markets.