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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.

The paper aims to determine if a country's Economic Freedom Index value has any relationship to the return of the related country specific exchange traded fund.

A total of 36 country specific exchange traded funds were selected for use in this study. The historical returns for 2011, the three‐year period ending in 2011, and the five‐year period ending in 2011 were recorded if available for each exchange traded fund. Each exchange traded fund (ETF) was placed into one of four groups based upon its country's overall Economic Freedom Index value. The range of Economic Index values for each group was the same ones used by the publishers of the Economic Freedom Index. The mean ETF return and standard deviation for 2011, three‐year, and five‐year periods were calculated for each of the four groups. The mean/standard deviation of the Economic Freedom Index and each of its components for 2011, the mean of the three‐year period, and the mean of the five‐year period were calculated for each of the four groups. The degree of statistical significance between the mean returns of the four groups was determined by using ANOVA. The correlation coefficients and the degree of statistical significance were calculated between each component of the index, between each component and the overall index value, and between the overall index value and the ETF returns.

The correlations between the components of the Economic Freedom Index generally tend to be positive and statistically significant. The correlations between the components of the Economic Freedom Index and the Economic Freedom Index tend to be positive and statistically significant. The correlation between the mean ETF returns of the various groups and the value of the mean Economic Freedom Index tends to be mixed. There appears to be no statistical significance of the difference between the mean ETF returns of each group and the mean overall score of the Economic Freedom Index for that group. For the year 2011 the level of significance was 0.103, for the three‐year period the level of significance was 0.541, and for the five‐year period the level of significance was 0.132. The differences within each group are more than the differences between the groups. The value of the Economic Freedom Index does not appear to correlate with the return of the country specific exchange traded fund.

The paper relates a country's environment for conducting business as represented by its Economic Freedom Index to the equity returns of firms in that country. The results of this study would be of interest to those individuals or institutions making investment decisions regarding country specific exchange traded funds. If a positive correlation exists between the index value and the return of the exchange traded fund, this information could improve the prediction of country specific exchange traded fund returns.

The purpose of this paper is to examine operating characteristics, risk and performance measures of all available vehicles for index investing in US bond funds during the 15‐year period from April, 1994 to March, 2009. The results shed light on the important issue of bond index mutual funds (BIMFs) and bond exchange‐traded funds (BETFs) performance compared with average of all bond mutual funds.

Data were obtained from Morningstar Principia. Operating characteristics include expense ratios, annual turnover rates, and tax cost ratios. Performance measures include average annual returns and return percentile rank in category, risks (measured by standard deviation) and risk‐adjusted returns (measured by the Sharpe ratio).

BIMFs and BETFs have significantly lower expense ratios and annual turnover rates than category averages. Their returns and risk‐adjusted returns are significantly higher than bond category averages.

Future studies will be able to benefit from a larger sample size, longer performance records, and the strength of bond index funds in foreign markets.

Both BIMFs and bond exchange‐traded mutual funds have significantly lower expense and annual turnover rates, making them preferred investment choices.

Efforts by active bond mutual fund managers to beat index benchmarks have largely failed. Investors should be wary of bond mutual fund managers touting their ability to beat the average or a bond index.

The advantage of investment in BIMFs and BETFs is clear.

The authors examine the factors that impact the growth of exchange traded funds (ETFs) from 1990 to 2020. The authors show the first-mover and winner-takes-all effects from top ETF issuers. Besides the longer history and larger asset under management (AUM), the ETFs being managed by top issuers have exhibited lower risks and higher trading volume. Delisted ETFs on the contrary has a shorter history, lower AUM, higher risks, and lower trading volume. For zombie ETFs, the authors find longer history, lower risks but lower AUM and trading volume, controlled for total expense ratio, return, volatility, Amihud (2002) illiquidity, bid-ask spread, turnover ratio, as well as year, issuer, asset class and region fixed effects. The authors further study the ETFs’ AUM and trading activities over the 2008 Global Financial Crisis (GFC) and COVID-19 pandemic crisis, and find that the GFC has a significant negative impact while the COVID-19 has a positive impact on the ETFs’ popularity. The significant increase in AUM of ETF relative to common stocks during the COVID-19 is associated with retail investors’ holdings, as the authors document a significant reduction of institutional holdings at the aggregate level.

The purpose of this paper is to consider the implicit effect of the underlying foreign currency exposure on the performance characteristics of country exchange traded funds.

To arrive at an overall estimation of the exchange-traded fund (ETF)’s tracking error, the mean of the three measures of tracking error was calculated for both the hedged (r_LC) and unhedged (r_NAV) return series. Since tracking error does not capture all the risk inherent in a country index fund, the study extends the analysis using the Sortino and Modified Sharpe ratios.

The decision to hedge currency risk should not be taken on the sole basis of historical volatilities. The investor must also factor in transactions costs, the possible roll of futures contracts and prevailing interest rate differentials. If the rate on the foreign currency is greater than the dollar (euro) rate, the investor will pay for the hedge. If the rate on the foreign currency is less than the dollar (euro) rate, the investor will gain on the trade. Given that hedging entails additional costs, in cases where the neutralization of currency volatility only reduces risk modestly, it would be advisable to leave the exchange rate risk unhedged. We propose two metrics for ETF investors deciding whether to hedge a country ETF’s underlying currency risk.

The results highlight a key finding: while the majority of country funds accurately track the performance of the underlying foreign index when measured in the local currency, returns in the fund currency can be much more volatile. In breaking down the sources of country fund volatility, the paper demonstrates the impact of the underlying currency movements on overall fund risk. In cases where the currency impact has a significant impact on fund tracking errors, an index-oriented investor benefits from neutralizing the exchange rate effect. Additionally, as the Sortino and Modified Sharpe measures suggest that the underlying currency exposure offers in most cases a better risk-adjusted return for country exchange-traded funds (ETFs) in the listing currency, we also calculate the risk minimizing foreign currency exposure for each fund and propose a decision rule based on the net currency variance to decide whether to hedge the ETF’s currency risk. The optimal hedge ratio indicates that US-based investors should only partially hedge the underlying currency risk while European-based investors are better off fully hedging currency risk.

In the build-up of an investment decision, the existence of both active and passive investment vehicles triggers a puzzle for investors. Indeed the confrontation between active and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a bone of contention since the inception of these investment structures. Accordingly, the objective of this chapter is to distinctly underscore whether an investor should be concerned in choosing between active and diverse passive investment structures.

The survivorship bias-free dataset consists of 776 equity funds which are domiciled either in America or Europe, and are likewise exposed to the equity markets of the same regions. In addition to geographical segmentation, equity funds are also categorised by structure and management type, specifically actively managed mutual funds, index mutual funds and passive exchange traded funds (‘ETFs’). This classification leads to the analysis of monthly net asset values (‘NAV’) of 12 distinct equally weighted portfolios, with a time horizon ranging from January 2004 to December 2014. Accordingly, the risk-adjusted performance of the equally weighted equity funds’ portfolios is examined by the application of mainstream single-factor and multi-factor asset pricing models namely Capital Asset Pricing Model (Fama, 1968; Fama & Macbeth, 1973; Lintner, 1965; Mossin, 1966; Sharpe, 1964; Treynor, 1961), Fama French Three-Factor (1993) and Carhart Four-Factor (1997).

Solely examination of monthly NAVs for a 10-year horizon suggests that active management is equivalent to index replication in terms of risk-adjusted returns. This prompts investors to be neutral gross of fees, yet when considering all transaction costs it is a distinct story. The relatively heftier fees charged by active management, predominantly initial fees, appear to revoke any outperformance in excess of the market portfolio, ensuing in a Fool’s Errand Hypothesis. Moreover, both active and index mutual funds’ performance may indeed be lower if financial advisors or distributors of equity funds charge additional fees over and above the fund houses’ expense ratios, putting the latter investment vehicles at a significant handicap vis-à-vis passive low-cost ETFs. This chapter urges investors to concentrate on expense ratios and other transaction costs rather than solely past returns, by accessing the cheapest available vehicle for each investment objective. Put simply, the general investor should retreat from portfolio management and instead access the market portfolio using low-cost index replication structures via an execution-only approach.

The battle among actively managed and index replication equity funds in terms of risk-adjusted performance and alpha generation has been a grey area since the inception of mutual funds. The interest in the subject constantly lightens up as fresh instruments infiltrate financial markets. Indeed the mutual fund puzzle (Gruber, 1996) together with the enhanced growth of ETFs has again rejuvenated the active versus passive debate, making it worth a detailed analysis especially for the benefit of investors who confront a dilemma in choosing between the two management styles.

Fair value pricing is a critical issue for mutual funds with international market exposure because trading in the underlying foreign securities is not synchronous with US market trading. Using a sample of Japanese open‐end mutual funds that trade in the USA, this paper explores the potential for exploitation of common mutual fund pricing practices and identifies much larger pricing errors than previously reported. A simple, objective solution to the fair value pricing quandary is proposed. The solution, based on foreign exchange‐traded funds and the S&P 500, provides a timely, objective pricing alternative that is less exploitable than current mutual fund pricing practices.

This chapter examines the current state of crypto exchange-traded funds (ETFs). It focuses on issues preventing wider implementation and specific products. ETFs have become a popular investment vehicle that investors use to help achieve their long-term goals. A recurring theme is that regulators protect individual investors from direct exposure to cryptocurrency, which many view as highly speculative investments. Pressure from institutions and investors for a bitcoin-based ETF made progress in 2021 when Proshares, an ETF specialized investment company, debuted the first-ever bitcoin futures ETF in the United States. This event is the first-time investors could buy a fund on the New York Stock Exchange that tracks derivative futures contracts of bitcoin. This occurrence pushed this digital asset’s spot price to all-time highs, serving as a breakthrough in cryptocurrency history.

Recent developments in technology and research have brought new innovations into the finance sector. Applying mathematics and computer science into finance has developed a multidisciplinary financial engineering field, where new quantitative and complex financial products are supplied to investors. In this chapter, we describe financial technologies as high-frequency trade; investment vehicles as mutual, exchange-traded, and hedge funds in the finance sector with figures of past 10 years and their impact in international trade volume. Financial derivatives are innovative products where investor may mitigate risk on their domestic and international transactions. The author also discusses cryptocurrencies as an important tool in innovation.