The liquidity of active ETFs

Active exchange traded funds (ETFs) are less liquid than their underlying portfolios. We attribute this finding, which contrasts with that for passive ETFs, to uncertainty about the future holdings of active ETFs. In addition, while diversification generally reduces firm-specific information asymmetry and improves portfolio liquidity, it impairs the liquidity of active ETFs, consistently with the substitution effect between diversification and liquidity documented in the literature. We show that the gap between active ETF and underlying liquidity varies cross-sectionally and over time and can be explained by differences in size and volume between ETFs and their underlying portfolio, by ETF age, and by ETF pricing errors.     

The effect of ETFs on financial markets: a literature review

Exchange-traded funds (ETFs) belong to the fastest growing investment products worldwide. Within 15 years, total assets invested in ETFs have twenty-folded, reaching over $3.7 trillion at the end of 2018. Increasing demand for passive investments, coupled with high liquidity and low transaction costs, are key advantages of ETFs compared to their closest substitutes such as traditional index funds. Besides the continuous growth of ETFs, the Flash Crash in 2010 triggered detailed investigations by regulators on how ETFs affect the financial market. This literature review provides a broad overview of recent academic studies analyzing the effect of ETFs on liquidity, price discovery, volatility, and comovement of the underlying securities.

     

ETF Competition and Market Quality

This paper examines competition between exchange traded funds (ETFs) that hold nearly identical portfolios of securities. We provide evidence that incumbent‐fund liquidity is negatively affected when a new ETF is added to an asset class. The degradation in liquidity is even more severe whenever both funds follow the same benchmark. We also document a decline in primary‐market activity for the incumbent ETFs after the arrival of new competitors. Furthermore, increasing the number of funds in an asset class does not put downward pressure on fund management fees. Thus, the deterioration in market quality may not be offset by decreasing costs of fund ownership.     

Mutual Fund Liquidity Costs

One dollar in purchases or redemptions generates an average cost of $0.006 for US equity mutual funds during the period 1997‐2009, approximately 70% lower than prior estimates derived from older data. However, large cross‐sectional differences exist between funds. Many funds have costs near zero, but funds that hold relatively illiquid equities, have relatively concentrated portfolios, and manage relatively large amounts of assets have average liquidity costs significantly greater than the full sample average. Furthermore, despite a large difference in underlying asset liquidity, US bond funds and US equity funds have similar average liquidity costs.     

Funding liquidity and equity liquidity in the subprime crisis period: Evidence from the ETF market

Using index and financial exchange-traded funds (ETFs), this study explores the relation between funding liquidity and equity liquidity during the subprime crisis period. Our empirical results show that a higher degree of funding illiquidity leads to an increase in bid–ask spread and a reduction in both market depth and net buying imbalance. Such findings indicate that an increase in funding liquidity can improve equity liquidity, with a stronger effect for the financial ETFs than for the index ETFs. Our study provides a better overall understanding of the effect of the liquidity–supplier funding constraint during the subprime crisis period.     

The role of institutional investors in propagating the crisis of 2007–2008

Using novel data on investors' bond portfolios, we study the contagion of the crisis from securitized bonds to corporate bonds. When securitized bonds became “toxic” in August 2007, mutual funds retained the now illiquid securitized bonds and sold corporate bonds. Funds with negative flows or high liquidity needs liquidated more than others. Yield spreads increased more for corporate bonds whose pre-crisis bondholders were more heavily exposed to securitized bonds, compared to same-issuer bonds held by unexposed investors. The findings suggest that liquidity-constrained investors with exposure to securitized bonds played a role in propagating the crisis from securitized to corporate bonds.     

ETF Premiums and Liquidity Segmentation

Exchange traded funds (ETFs) provide a means for investors to access assets indirectly that may be accessible at a high cost otherwise. I show that liquidity segmentation can explain the tendency for ETFs to trade at a premium to net asset value (NAV) as well as the life‐cycle pattern in premiums. ETFs with larger NAV tracking error standard deviations (TESDs) tend to trade at higher premiums and the liquidity benefits offered by foreign ETFs and fixed income ETFs are revealed to be the most valuable to investors. Further tests validate that TESD has the desirable properties of a liquidity segmentation measure.     

The effect of liquidity and arbitrage on the price efficiency of Chinese ETFs

We study the potential factors that determine the large and persistent price deviations in Chinese equity exchange-traded funds (ETFs). Our results suggest that ETF liquidity and arbitrage activity are positively correlated with ETF price efficiency, and the relation is more pronounced with higher institutional ownership. We also evaluate the effect of two exogenous shocks in the Chinese market. Using a policy change that added market makers to ETFs on the Shenzhen Stock Exchange (SZSE) and Shanghai Stock Exchange (SSE), we find that market makers improve price efficiency and that the impact is stronger for ETFs with lower liquidity. We also exploit a change in trading rules on the SZSE and show that the relaxation of arbitrage restrictions improves price efficiency. Altogether, these findings provide evidence that lack of liquidity, due to the unique market structure and regulations of the Chinese market, contributes to price inefficiency of Chinese ETFs.     

An analysis of credit risk spreads for high yield bonds

The overall growth and volatility in the high yield (HY) bond market has provided a viable source of capital and an interesting investment asset class. The result has been strong interest in the HY bond credit risk spread (CRS) because this series is very volatile and has a significant impact on the availability of capital to issuers and the rates of return and risk results for investors. Given these trends in the HY bond market, our study has two purposes. The first is to examine statistical properties of the CRS series for the aggregate HY bond market and the three rated components. The second purpose is to interpret the influence that a set of variables are expected to have on future CRSs and, therefore, HY bond performance. In summary, the statistical analysis indicates a significant business cycle effect, but does not show a monetary policy impact. Additionally, the study finds significant differences in characteristics among bonds with alternative ratings. The analysis of specific variables highlights the strong influence of direct and indirect measures of default risk, capital market risk factors, a specific measure of monetary policy, and an impact from liquidity within the HY bond market. There was also evidence of segmentation within the HY bond market because the empirical results indicate that we should consider separate models across rating classes that employed different variables as well as coefficients that were significantly different for the same variables.     

Historic Changes in the High Yield Bond Market

In a history that now stretches about four decades, the high yield (HY) market has experienced growth in issuance and out‐standings that is remarkable both for its level (about 13% per annum, with HY bonds now accounting for about 25% of the total corporate bond market) and its cyclicality and sensitivity to the broad economy. The HY market has also experienced a notable shift away from B‐rated bonds and toward both lower‐risk Ba‐rated bonds and, to a lesser extent, more risky Caa‐rated bonds. Consistent with this development, studies of the performance of HY bonds show Ba‐rated bonds experiencing not only lower risk, but also higher returns than Caa‐rated bonds, which have produced surprisingly low average returns along with exceptionally high volatility. At the same time, studies of the correlation of HY bond returns with returns on other major asset classes report that all classes of HY bonds (but particularly the riskier B‐ and Caa‐rated bonds) have consistently stronger relationships with common stocks (especially small‐cap stocks) than with Treasuries and investment‐grade bonds. Analysis of the volatility of HY bond returns over time shows that during periods of stability in the economy and financial markets, the volatility of HY bond returns has been very similar to that of investment‐grade bonds. But during periods of political or economic uncertainty, the volatility of HY bonds has become two or three times that of investment‐grade bonds, approaching the volatility of common stocks. The main driver of the significant increase in the risk of the aggregate HY bond market during periods of uncertainty has been Caa‐rated bonds, whose risk pattern has been remarkably similar to that of small‐cap common stocks. Analysis of the credit risk spread (or CRS) series for both the composite HY bond market and each of its rating categories shows markedly non‐normal distributions with significant positive “skewness”—that is, periods of exceptionally high spreads (that are not counterbalanced by periods of exceptionally low spreads). The authors also report a consistently strong relationship of the CRS series with default rates and the general state of the economy, with major peaks occurring during or shortly after economic recessions. Near the end of 2008, however, there was a clear break in this relationship when the CRS reached an historic peak of 2,000 basis points, or more than five standard deviations above its long‐term mean, while the default rate (at 4%) was below its long‐term average. The authors offer two explanations for this break in CRS‐default rate relationship: the jump in the CRS caused by the extreme flight to quality and drop in liquidity for all risky securities during the second half of 2008; and the use of covenant‐lite securities and other sources of financial flexibility that appear to have enabled many HY issuers to defer defaults (if not avoid them entirely).     

Active mutual funds: Beware of smart beta ETFs!

Smart beta ETFs have gained tremendous prevalence among investors in recent years. This study provides empirical evidence that a proportion of this fast-paced growth can be attributed to the investor migration from closet factor active mutual funds to smart beta ETFs. Using a sample of US domestic equity active mutual funds and smart beta ETFs from 2000 to 2019, we find that smart beta ETFs offer factor exposures at lower fees and therefore higher risk-adjusted returns than closet factor funds. The investors notice the benefits of smart beta ETFs and replace closet factor funds with these ETFs. Closet factor funds are at higher risks of being replaced when investors are sophisticated, when the market share of smart beta ETFs increases, and after 2012. Our findings illustrate the dynamic changes in investor preference towards investment products that bring similar or greater benefits at a lower price.     

A Comparative Analysis of the Investment Characteristics of Alternative Gold Assets

Employing daily data over the period 1987–2010, we examine the diversifying, hedging and safe haven properties of gold bullion, gold stocks, gold mutual funds, and gold exchange traded funds (ETFs). First, with regard to gold bullion, we document a clear and strong hedging role over a mere diversifying capability. Second, our results highlight that gold stocks, gold mutual funds, and gold ETFs tend to be diversifiers. Third, both gold bullion and gold ETFs show support for the safe haven property. However, gold stocks and gold mutual funds display very little evidence of the safe haven characteristic. Consequently, investors who are keen on securing the safe haven features of gold investment cannot generally rely on gold stocks or mutual funds. Instead, they need to take positions directly in bullion or gold ETFs.     

Active management, fund size, and bond mutual fund returns

Conventional wisdom holds that bonds are relatively homogenous investments compared to equities. Consequently, factors that explain variation in returns among bond mutual funds may differ in magnitude from those for equity mutual funds. In this study, a time-series cross-sectional analysis is employed to investigate the relationship between a bond fund's risk-adjusted return and specific fund attributes. Results indicate that a bond fund's past performance does not predict future performance and that bond fund managers are generally ineffective at increasing risk-adjusted returns. However, unlike equity mutual funds, bond mutual funds do appear to enjoy economies of scale.     

The timing ability and global performance of Tunisian mutual fund managers: A multivariate GARCH approach

It is well-established in the financial literature that the global performance of mutual fund managers is the result of two skills: selectivity and market timing. This paper examines whether the multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) approach improves our perception of the global performance of fund managers compared with the unconditional approach and the conditional approach based on instruments. We find strong evidence that the multivariate GARCH method makes mutual fund performance looks better relative to the existent approaches, but this improvement in the global performance does not mean necessarily that mutual funds outperform traditional benchmarks. Indeed, mixed mutual funds yield neutral performance relative to benchmarks, whereas bond mutual funds generate significant positive global coefficients. The strong performance of bond fund managers comes from their ability to pick profitable bonds, not from their ability to time the market. Also, the empirical tests highlight that the best (worst) bond funds in the past remain at the top (bottom) of the ranking in the following years. These findings suggest that the Tunisian bond market presents strong opportunities for sophisticated investors.     

Quantify the quantitative easing: Impact on bonds and corporate debt issuance

This paper studies the impact of the European Central Bank’s (ECB) Corporate Sector Purchase Programme (CSPP) announcement on prices, liquidity, and debt issuance in the European corporate bond market using a data set on bond transactions from Euroclear. I find that the quantitative easing (QE) programme increased prices and liquidity of bonds eligible to be purchased substantially. Bond yields dropped on average by 30 basis points (bps) (8%) after the CSPP announcement. Tri-party repo turnover rose by 8.15 million USD (29%), and bilateral turnover went up by 7.05 million USD (72%). Bid-ask spreads also showed significant liquidity improvement in eligible bonds. QE was successful in boosting corporate debt issuance. Firms issued 2.19 billion EUR (25%) more in QE-eligible debt after the CSPP announcement, compared to other types of debt. Surprisingly, corporates used the attracted funds mostly to increase dividends. These effects were more pronounced for longer-maturity, lower-rated bonds, and for more credit-constrained, lower-rated firms.     

Supply uncertainty of the bond investor base and the leverage of the firm

We examine the effect of the bond capital supply uncertainty of institutional investors (e.g., mutual bond funds and insurance companies) on the leverage of the firm using a novel data set. Our main finding is that the supply uncertainty of the firm's bond investor base — measured as (i) the average portfolio turnover, or (ii) the average flow volatility of investors holding the firm's bonds, or (iii) the prevalence of mutual funds among the firm's bondholders as opposed to insurance companies — has a negative and significant effect on the leverage of the firm. The supply uncertainty of the firm's bond investor base also has a negative and significant effect on the firm's probability of issuing bonds, and a positive and significant effect on the firm's probability of issuing equity and borrowing from banks. We take a multi-pronged approach to address potential endogeneity issues, including use of geography-based instruments and firm fixed effects, subsample analyses, and a placebo test. Our results highlight the fragility of access to the bond market for companies that depend on mutual funds with high turnover/ flow volatility as primary bond investors.     

The effect of investor service costs on mutual fund performance

We examine the effect of investor service costs on mutual fund performance. Benchmarking passive funds against ETFs managed by the same fund company with the same investment objectives, we show that passive funds on average underperform ETFs by 42 bps in annualized net returns, of which about 90% can be attributed to investor service costs. Further benchmarking active funds against passive funds, we show that active funds on average outperform passive funds by 31 bps in annualized gross returns. However, the higher expense ratios charged by active funds lead to about 28 bps of underperformance in annualized net fund returns.     

The efficiency of international information flow: Evidence from the ETF and CEF prices

While similar in their trading and organization, closed-end funds (CEFs) and exchange-traded funds (ETFs) differ in their liquidity and ease of arbitrage. We compare their price transmission dynamics using a sample of funds that invest in foreign securities and are most likely to show the deficiencies in the manner in which they process information. Our analysis shows that ETF returns are more closely related to their portfolio returns than are CEF returns. However, both fund types underreact to portfolio returns but overreact to domestic stock market returns. A simple trading strategy using these results is profitable with roundtrip trading costs less than 1.38% for CEFs and 0.71% for ETFs.     

What Drives ETF Flows?

The value of exchange traded fund (ETF) assets has increased from $66 billion in 2000 to almost a trillion dollars in 2010. We use this massive expansion in ETF assets to study what drives ETF flows. Using a data set of over 500 ETFs from 2001 to 2010, we show that ETF investors chase returns in the same way as mutual fund investors. While there is an active debate about whether return chasing by mutual fund investors represents the pursuit of superior talent, the existence of return chasing in this passively managed environment should not represent a search for skilled managers. We also show that ETF flows increase following high volume, small spreads, and high price/net asset value ratios. Finally, we find little evidence of superior market timing in ETF flows. Our results suggest that return chasing in both mutual funds and ETFs is more likely the result of naïve extrapolation bias on the part of investors that has contributed to the growth of the ETF industry.     

Unskilled fund managers: Replicating active fund performance with few ETFs

This paper uses Exchange Traded Funds (ETFs) instead of risk factors as benchmarks to examine active mutual fund performance distribution. While transaction costs are included in the ETF returns, that is not true regarding risk factors, making it more challenging to characterize extraordinary performances via alphas. Assessments are based on the estimation of the skilled funds proportion defined by Barras et al. (2010). After evaluating several ETF combinations, we conclude that sets of 3 to 5 ETFs replicate most levels of active fund performance. Finally, we propose specific ETF selection algorithms, whereby we estimate that 95% of active management funds fail to generate value for their investors. Alphas calculated with ETFs are higher than those using risk factors, and the difference is similar to the transaction costs required for investing in risk factor portfolios (Frazzini et al. (2012)).