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Mutual funds and exchange-traded funds (ETFs) differ in significant ways. ETFs trade on exchanges whereas mutual funds do not. ETFs generate few, if any, capital gains that are passed through to shareholders which makes them tax efficient. Alternatively, mutual funds often generate capital gains that are passed through to shareholders, and this makes them tax inefficient. To correct this tax inefficiency, Vanguard astutely added an ETF share class to many of its mutual funds back in 2001. They patented this structure and recently the patent expired. Several fund sponsors have applied to the Securities and Exchange Commission (SEC) to create this structure for their own funds. If approved, this would change the operation of affected funds in ways that are important to investors. [ABSTRACT FROM AUTHOR]

We analyze how ETFs compete. Drawing on a new model and empirical analysis, we show that ETF secondary market liquidity plays a key role in determining fees. More liquid ETFs for a given index charge higher fees and attract short-horizon investors who are more sensitive to liquidity than to fees. Higher turnover from these investors sustains the ETF's high liquidity, allowing the ETF to extract a rent through its fee, and creating a first-mover advantage. Liquidity segmentation through clientele effects generates welfare losses. Our findings resolve the apparent paradox that higher-fee ETFs not only survive but also flourish in equilibrium. [ABSTRACT FROM AUTHOR]

We document and explain the sharp performance deterioration of smart beta indexes after the corresponding exchange-traded funds (ETFs) are launched for investment. While smart beta is purported to deliver excess returns through factor exposures, the market-adjusted return of smart beta indexes drops from about 3% "on paper" before ETF listings to about −0.50% to −1% after ETF listings. This performance decline cannot be explained by variation in factor premia, strategic timing, or diminishing returns to scale. Instead, we find strong evidence of data mining in the construction of smart beta indexes, which helps ETFs attract flows, as investors respond positively to backtests. [ABSTRACT FROM AUTHOR]

This article investigates the impact of exchange-traded fund (ETF) ownership on seasoned equity offerings (SEOs). We find that increases to firms' ETF ownership is positively related to their propensity to conduct an SEO. ETF ownership is also associated with less negative SEO announcement returns, smaller discounts, and better long-run stock returns. Our evidence is consistent with equity issuance following investor demand for stocks driven by greater participation in ETFs, suggesting a possible alternative source of market timing opportunity. [ABSTRACT FROM AUTHOR]

We identify a novel economic mechanism through which passive ownership positively affects informational efficiency in the cross-section of firms. Passive investors' inelastic demand lowers a firm's cost-of-capital, inducing it to take more risk. The higher cash flow variance, in turn, incentivizes active investors to acquire more precise private information, pushing up price informativeness for firms with high passive ownership. High passive ownership also implies higher stock prices and higher stock-return variances. An increase in the aggregate size of passive investors amplifies these cross-sectional differences. We also document complementarities in firms' real investment and investors' information choices that can cause information crashes. Received May 31, 2020; editorial decision January 4, 2023 by Editor Holger Mueller. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

We study how the growth of exchange-traded funds (ETFs) affects the sensitivity of international capital flows to the global financial cycle. Using comprehensive fund-level data on investor flows, we show that their sensitivity to global financial conditions for equity (bond) ETFs is 2.5 (2.25) times higher than for equity (bond) mutual funds. This higher sensitivity can be directly linked to ETFs underlying shorter-trading-horizon clientele that trades more often in response to shocks. Using country-level data, we find that where ETFs hold a larger share of financial assets, equity inflows and prices become more sensitive to global risk. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

Semantic segmentation often suffers from class imbalance, where the label ratio for each class in the dataset is not uniform. Recent studies have addressed the issue of class imbalance in semantic segmentation by leveraging the neural collapse phenomenon in conjunction with an Equiangular Tight Frame (ETF). While the use of ETF aids in enhancing the discriminability of minor classes, class correlation is another crucial factor that must be taken into account. However, managing the balance between class correlation and discrimination through neural collapse remains challenging, as these properties inherently conflict with one another. Moreover, this control is established during the training stage, resulting in a fixed classifier. There is no guarantee that this classifier will consistently perform well with different input images. To address this problem, we propose an Equiangular Tight Frame Transformer (ETFT), a transformer-based model that jointly processes the features and classifier using ETF structure, and dynamically generates the classifier as a function of the input for imbalanced semantic segmentation. Specifically, the classifier initialized with the ETF structure is jointly processed with the input patch tokens during the attention process. As a result, the transformed patch tokens, aided by the ETF structure, achieve discriminability between classes while preserving contextual correlation. The classifier, initially structured as an ETF, is adjusted to incorporate the correlation information, benefiting from the attention mechanism. Furthermore, the learned classifier is combined with the fixed ETF classifier, leveraging the advantages of both. Extensive experiments demonstrate that the proposed method outperforms state-of-the-art methods for imbalanced semantic segmentation on both the ADE20K and Cityscapes datasets. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We empirically examine whether feedback traders are active in the Bitcoin and the extent to which their presence is affected by a series of noise-related factors (sentiment; volume; liquidity) at three different frequencies (hourly; daily; weekly) for the April 2013–July 2019 period based on Bitstamp data. Our findings suggest that positive feedback trading grows stronger for higher (hourly; daily) frequencies, with its presence manifesting itself mainly during periods of high/improving sentiment and high/rising volume/liquidity. Additional tests reveal that the significance of hourly feedback trading is identified during hours corresponding to the trading hours of major European/North American markets. Overall, our results confirm extant literature evidence on the prevalence of noise trading in cryptocurrencies, while further showcasing that the factors motivating feedback trading in other asset classes (equities; ETFs; futures) exhibit similar effects over the presence of feedback traders in the cryptocurrency market. [ABSTRACT FROM AUTHOR]

This commentary spotlights the continued impact of the Russian invasion on geography education in higher education in Ukraine. From discussions with Ukrainian geographers in institutions in contrasting regions of the country, we describe their resilience in adapting the delivery of the physical geography curriculum, especially in the essential area of fieldwork and the use of digital tools. This ‘lived experience’ perspective builds on the theoretical contributions to the discussion initiated by Klinke (2023) in this journal about the challenges posed for geographers. In the third year of the conflict, the challenges set out are considerable, long term, and we call for individuals, universities and funders to further facilitate teaching and learning collaborations despite the limited funds available for the exchange of teaching and learning support and innovation. [ABSTRACT FROM AUTHOR]

Investment fund managers have been trying to provide more attractiveness for investors by earning higher yields and generating liquidity. The investment rate of return of a mutual fund is obtained from the difference between the issuance and redemption of Net Asset Values (NAVs) per investment unit. However, the Exchange Traded Funds'(ETFs') yield should be calculated differently, and investors must consider the changes in market prices (Not only the NAVs), which are not usually announced through the Ads, so they disregard the investors. Investment fund managers believe that the attractiveness of the rate of return, even to a small extent, leads to over-welcoming of the investors and a faster growth of the funds' size. According to the information available in recent years, investors have shown more interest in fixed-income investment funds, and the growth of ETFs has been significant compared to the growth of total funds, so it can be assumed that investors are more interested in ETFs. Thus, in this research, we will identify factors affecting the development of ETFs, especially fixed-income ones. To fulfill our purpose, we examined all active fixed-income investment funds that are traded in the Tehran Stock Exchange and the Iran Farabourse from March 2021 to September 2023, including 25 ETFs. We analyzed our panel data through ordinary least squares. Analyzing the effective rate of returns of 25 Fixed Income ETFs, which have been active from March 2021 to September 2023, our results showed that ETFs development is significantly related to the fund size, daily price volatility, and liquidity. Despite our expectations, rate of return, fund age, and price adjustment do not have a significant effect on the development of investment funds. The result showed that a higher rate of return did not have a significant effect on the attractiveness and acceptance of investors, but the liquidity of investment units positively affects the development of fixed-income ETFs. We also found that the daily volatility of the final price inversely impacted the fund's size. This is consistent with investors' low risk-taking spirit in fixedincome funds and emphasizes their preference to avoid liquidity risk and price volatility risk. [ABSTRACT FROM AUTHOR]

Some US-listed country exchange-traded funds (ETFs) suffer from chronic and meaningful mispricing in the form of premiums or discounts relative to their fundamental value despite the presence of the creation/redemption mechanism. This mispricing is mainly attributed to the staggered information flow due to nonoverlapping time zones between the market where the ETF is listed and its underlying home market. This study provides out-of-sample evidence on the price formation of Gulf Cooperation Council (GCC) country ETFs and gauges the impact of mispricing on their underlying home markets. The GCC context is particularly insightful because these markets have nonoverlapping time zones with the US and follow distinct trading schedules. Our sample comprises daily data from three countries' iShares that exclusively track the Qatari, Saudi, and Emirati stock markets from 17 September 2015 to 14 March 2023. The results show that GCC ETFs are driven mainly by their net asset values (NAVs), albeit imperfectly, while the S&P500 exerts a relatively mild influence on these ETFs compared to other country ETFs, as reported by prior studies. Moreover, we find that crude oil prices positively and significantly impact GCC ETFs' pricing. When we control for unsynchronized trading days between the US and the GCC home markets, we find a structural difference between overlapping and nonoverlapping trading days. This structural difference manifests in a sluggish adjustment to correct mispricing in the ETF market on the day the home market is closed; however, other variables, including the S&P500, show no discernible difference, which refutes the overreaction explanation. This recurrent pattern is reflected in a clear day-of-the-week pattern in the price discovery these ETFs offer to their underlying home markets. [ABSTRACT FROM AUTHOR]

This study examines the link between stocks and decentralized finance (DeFi) in terms of returns and volatility. Major G7 exchange-traded funds (ETFs) and various highly traded DeFi assets are considered to ensure the robustness of the empirical experiment. Specifically, this study applies the vector autoregression generalized autoregressive conditional heteroskedasticity (VAR-GARCH) model to examine the information transmission of these two markets on a two-way basis and the dynamic conditional correlation (DCC)-GARCH model to assess the bivariate correlation structure between each DeFi and ETF pair. The volatility spillover analysis proves a contagion effect occurred between different geographic markets, and even between markets of different natures and typologies, during the most turbulent moments of the COVID-19 crisis and the war in the Ukraine. Our results also reveal a weak positive correlation between most DeFi and ETF pairs and positive hedge ratios that approach unity during turbulent times. In addition, DeFi assets, except for the Bazaar (BZR) Protocol, can offer diversification gains when included in financial investment portfolios. These results are particularly relevant for portfolio managers and policy-makers when designing investment strategies, especially during periods of financial crisis. [ABSTRACT FROM AUTHOR]

Investment in firms committed to environmental, social, and governance (ESG) issues is both popular and controversial. Critics argue ESG investing fails to yield significant financial returns because of increased costs, while proponents argue that it provides significant social returns, which are valued by the public and will be reflected in financial returns. Using the Fama–French asset pricing model with data on exchange-traded funds (ETFs) focused on ESG firms, the authors provide empirical evidence that rejects the claim that ESG investment results in lower financial returns. Rather, they show that ESG investment results in statistically significant, albeit only marginally higher, returns than predicted by the market. Thus, independent of any social value it may create, there is a financial incentive for ESG investment. [ABSTRACT FROM AUTHOR]

Recently it was shown that the news-based stock pricing model (NBSPM) outperforms the momentum-enhanced five-factor Fama–French model (FF5M) for a representative list of holdings of the major US equity sector ETFs both in-sample and out-of-sample. The leading term in NBSPM besides the market (CAPM) beta is the industry beta estimated using returns of the relevant equity sector ETFs or industry ETFs. In this article, the industry beta is added to FF5M. It is found that the resulting model (FF5MI) is generally more accurate in-sample than NBSPM in terms of the mean squared error but not necessarily in terms of the mean absolute error. FF5MI is, however, always inferior to NBSPM out-of-sample. This implies that the industry beta has the major impact on stock prices while the FF5M factors may yield an overfitted model. [ABSTRACT FROM AUTHOR]

This article proposes an H∞$$ {H}_{\infty } $$ optimal leader‐follower consensus control protocol with finite‐time prescribed performance for nonlinear multiagent systems suffering from the actuator fault based on the zero‐sum game framework. First, to guarantee the specified performance of the system within a finite time frame, a novel error transformation function (ETF) is constructed. The ETF proposed in this paper can adjust the mapping range of error transformation to achieve better error convergence performance, thereby enhancing the flexibility of the controller design. Then, to compensate for the negative impact of actuator fault, an error‐related item is separated from the optimal performance index function to design an online fault estimator, which can obtain a better error estimation accuracy. Furthermore, to lessen the need for difficult‐to‐verify persistent excitation signal in adaptive dynamic programming algorithm, both historical and real‐time data are applied to adjust the updating law of neural network weight. Moreover, it demonstrates that the signals within the closed‐loop system are bounded and the expected finite‐time prescribed performance can be ensured in the presence of faults. Finally, a numerical example of multiple single‐link robots manipulator system is executed to validate the efficacy of the developed scheme. [ABSTRACT FROM AUTHOR]

This paper analyses the connectivity between geopolitical risk (GPR) and several segments of exchanged‐traded funds, aligned with the United Nations Sustainable Development Goals (SDGs), in order to understand the implications of risk associated with wars, political tensions and terrorist acts in the dynamics generated by this type of asset. We studied the behaviour of assets representative of 6 SDGs and 2 GPR indices, over a period of approximately 14 and a half years, characterized by several market phases, with special emphasis on the pandemic crisis and the war in Ukraine. Resorting to dynamic analysis, based on several multivariate models, it was possible to identify spillover effects in phases corresponding to turbulence in financial markets, in particular in the downward movements of prices of sustainable assets, generated from the geopolitical threat index. The results obtained are relevant for understanding the effect of GPR on sustainable investment, being of interest to various market actors. [ABSTRACT FROM AUTHOR]

This study concerns the position tracking control of the hybrid-powered barrel elevator (HPBE) with dual-channel model uncertainty and output constraints. To realize an outstanding control performance, a dual-extended-state-observer-based command filtered adaptive prescribed performance control (DESO-CFAPPC) strategy is presented based on the dynamic model considering various nonlinearities and model uncertainties. The conjunction of the PPC and barrier Lyapunov function in the DESO-CFAPPC not only prevents violation of output constraints of the barrel, but also prevents the complex calculation caused by the logarithmic ETF in the traditional PPC. The adaptive laws are constructed to estimate uncertain parameters. The DESO further estimates the unknown velocity, mismatched and matched model uncertainties. The obtained estimates are incorporated into the control law to enhance the tracking performance. The stability and convergence of the DESO-CFAPPC are theoretically proved and comparative experimental results indicate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Understanding liquidity and liquidity risk is essential for effective risk management. We investigate liquidity spillover effects among ETFs that track the S&P sectors. In particular, using COVID-related news shocks as a natural experiment, we estimate the direction and magnitude of two-way net spillovers and their asymmetry across good and bad news regimes, where liquidity is measured by the daily quoted bid–ask spread and the Amihud illiquidity ratio. Our results confirm the liquidity links amongst ETFs and suggest that liquidity spillovers are more pronounced during bad news periods compared to good news periods. In addition, we document the variations in the results obtained using the bid–ask spread and the Amihud ratio, which provide insights into different dimensions of liquidity and liquidity risk, including volatility and trading volume. [ABSTRACT FROM AUTHOR]

Copyright of Wirtschafts- und Sozialwissenschaftliches Institut Mitteilungen is the property of Nomos Verlagsgesellschaft mbH & Co. KG and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Using marketable order flow data, we analyze key characteristics of aggregate retail exchange‐traded fund (ETF) investing from 2010 to 2021, including allocations, holding period and investment performance. Retail traders allocate 12% more dollar volume to leveraged and inverse ETFs versus nonretail traders. Retail ETF trades distinctly increase with prior ETF returns, in contrast to contrarian stock trading. Estimated ETF holding periods are longer for retail investors versus nonretail. Finally, retail and nonretail ETF trades perform similarly over hypothetical holding periods up to one quarter. Overall, we provide policy‐relevant insights into retail investing behaviours, which have been the subject of recent concern. [ABSTRACT FROM AUTHOR]

This study adopts a composite threshold model that differentiates between the upside and downside betas of the major US-based renewable and non-renewable exchange-traded funds (ETFs) during heightened uncertainty. It is found that downside betas for both renewable and non-renewable energy ETFs are significantly greater than upside betas. However, in a highly uncertain market, renewable energy ETFs tend to enjoy higher upside gains than the fossil-fuel ETFs. The results suggest that renewable energy ETFs have great potential to generate high returns, but the downside risk associated with renewables should be mitigated by government incentivizing the use of renewables in both domestic and foreign markets. Investing in renewable energy is not only good for the environment but also compared to other investment alternatives (including fossil fuels) it provides better risk-adjusted returns. During the last 5 years, some renewable energy ETFs have even outperformed several well-established sectoral ETFs. This paper finds that there is a more favourable business case for investing in renewables than common perception would suggest. [ABSTRACT FROM AUTHOR]

We examine the relationship between gold prices and the U.S. dollar exchange rate, arguing that their interactions are state-dependent and asymmetric under different market conditions. State dependency hinges on different short-term interest rate zones. To prove this point, we determine three distinct levels or zones of the effective federal funds rate using SETAR(2,p) tests. Subsequently, we perform conditional least square estimations of log changes in gold prices as a function of log changes in the nominal broad U.S. dollar exchange rate index for each of the obtained zones. Their relationship is consistently inverse, suggesting that gold and the U.S. dollar are risk-hedging substitutes for normal market periods. This also implies that gold is a safe-haven asset against the U.S. dollar exchange rate risk against a broad range of currencies. The substitution is weaker in the low-interest rate zone, more robust in the intermediate zone, and very pronounced in the high zone. We also perform a Markov switching test on the double-log function of gold prices and the exchange rate. The tests show a pronounced inverse relationship, i.e., substitution between assets, at normal market conditions. The relationship becomes significantly positive during episodes of financial distress, indicating complementarity between gold and U.S. dollar assets. [ABSTRACT FROM AUTHOR]

We look at what can be done with a concentrated position in low-basis stock. Options include selling the stock and getting capital-gains treatment, holding the stock until death and getting a stepped-up basis, gifting the stock to loved ones, swapping the stock via an exchange fund, and gifting the stock to charity. The pros and cons of each alternative are explored. [ABSTRACT FROM AUTHOR]

The interplay between investors' demand and providers' incentives has shaped the evolution of exchange-traded funds (ETFs). While early ETFs invested in broad-based indexes and therefore offered diversification at low cost, more recent products track niche portfolios and charge high fees. Strikingly, over their first 5 years, specialized ETFs lose about 30 |$\%$| (risk-adjusted). This underperformance cannot be explained by high fees or hedging demand. Rather, it is driven by the overvaluation of the underlying stocks at the time of the launch. Our results are consistent with providers catering to investors' extrapolative beliefs by issuing specialized ETFs that track attention-grabbing themes. [ABSTRACT FROM AUTHOR]

We investigate the link between exchange-traded funds and real investment. Cross-sectionally, higher ETF ownership is associated with an increased sensitivity of real investment to Tobin's q and a heightened ability of stock returns to forecast future earnings. Inclusion of stocks in industry ETFs enhances investment- |$q$| sensitivity and implies greater incorporation of earnings information into prices prior to public releases. Greater nonmarket ETF ownership leads to increased (reduced) reliance of real investment on own (peers') stock prices. Overall, the evidence is consistent with ETFs positively affecting real investment efficiency via greater flows of information. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

This paper explores the spillover and leverage effects, as well as trading volume dynamics, of Financial, Technology, and FinTech Exchange-Traded Funds (ETFs) using ARMA-GARCH and ARMA-EGARCH models. The study indicates that these ETF sectors and the stock market index have significant connections and interdependencies, which can transmit shocks and volatility. Market fluctuations significantly impact the ETF sectors, with negative shocks having a more significant impact on volatility. Furthermore, increased volatility is linked to increased trading activity, which indicates active investor adjustments in uncertain periods. The practical implications of these findings for investors, portfolio managers, and policymakers are aimed at supporting portfolio diversification, risk management, and asset allocation decisions. Understanding the effect of market volatility on trading volumes can help improve trading strategies and liquidity management. The paper increases comprehension of spillover and leverage effects and trading volume in ETFs, enabling stakeholders to make well-informed decisions in the financial markets. [ABSTRACT FROM AUTHOR]

The article examines the use of the so-called "international argument" in vocational education and training (VET) for the transfer of VET elements. Using policy documents of two political actors of the European Union at the interface between politics and research (CEDEFOP and ETF), exemplary ways of using the "international argument" are examined and systematised. Finally, desiderata for practice and research for a systematic investigation of the "international argument" are presented. [ABSTRACT FROM AUTHOR]

Exchange-traded funds (ETFs) have revolutionized the investment universe since their inception in 1993. They are indubitably one of the most successful investment structures in history. Their transparency, transactional superiority, tight arbitrage-based pricing, tax efficiency, and low fees are all contributing factors to their success. The authors expect their growth to continue at the expense of both mutual funds and other structured products, particularly as regulatory constraints are removed. ETFs are more difficult to operate when the underlying isn't transactionally liquid or easily valued. For this reason, the authors don't expect all ETFs to be successful. ETFs that use derivatives as underlying possess some unattractive characteristics that need to be thoroughly understood by investors. ETFs based on thematic strategies are often driven more by investor exploitation than sound investment thesis and will continue to underperform. This underperformance creates opposing dynamics in terms of both fees and assets under management. In this article, the authors offer an overview of the current ETF market, particularly focusing on recent developments in this area. [ABSTRACT FROM AUTHOR]

Purpose: Traditionally, Task–Technology Fit (TTF) theory has been applied to examine the usefulness of technology in the work environment. Can the same approach (based on experience rather than tasks) be applied to non-work, cultural heritage environments? This is the question the authors ask in this study. This study proposes a new variation of TTF based on the experience economy model, namely Experience–Technology Fit (ETF), for the non-work environment, in particular, in the context of cultural heritage, where visitor experience is enhanced by extended reality technology, which combines immersive technologies and artificial intelligence. Design/methodology/approach: Employing a quantitative survey method, the empirical analysis seeks to determine the influence of Mixed Reality (MR) characteristics (interactivity, vividness), Voice User Interface (VUI) characteristics (speech recognition, speech synthesis) and experience economy factors (education, entertainment, esthetic, escape) on satisfaction, revisit intention and actual purchase to propose a new ETF model. Findings: VUI, MR, and experience factors were significantly associated with ETF; when combined with MR-based experience, ETF was significantly associated with satisfaction. This study's findings further demonstrate the relationship between users' satisfaction when engaging with MR-based experience and revisit intention, while purchase intention was significantly associated with the actual purchase. Originality/value: The novel contribution of this study is the proposal of the EFT model, a new variation of TTF based on the experience economy model. Overall, this study expands the applications of TTF to an experience-oriented business, thereby broadening the authors' understanding of technological success with a specific focus on the technology fit of Extended Reality (XR) in the context of cultural heritage. [ABSTRACT FROM AUTHOR]

The present study addresses the important demographic of director age in relation to the performance of the constituent firms of Fintech-focused Exchange Traded Funds (ETFs). While private Fintech boards accommodate generally young officers, regulatory and market forces contribute to notable shifts in the board age composition of seasoned, publicly listed Fintech entities. Within the fast-moving and evolving context of Fintech, we assess how board age composition impacts on such firms' return-on-assets, sales-on-assets, cash flow proficiencies, and market-to-book value. Our study findings suggest age diversity exhibits a significant inverse relation with the first three of these performance measures. Fintech entities with lower board age dispersion achieve stronger performance in the key metrics. Such a finding holds in cross-sectional terms (i.e. without material change in the average age of board members across the study period). Within our study context, we also assess the age gap between non-executive directors (NEDs) and executive officers (EDs). For most sample firms, average NED age markedly exceeds ED age. Through a battery of tests, we demonstrate more seasoned (i.e. less young) EDs support Fintech firm performance. The presence of more experienced EDs serves in narrowing the age gap with older and more seasoned NEDs. [ABSTRACT FROM AUTHOR]

The digital frequency-domain multiplexing technique is widely used for astrophysical instruments with large detector arrays. Detailed detector characterization is required for instrument calibration and systematics control. We conduct the TES complex electrothermal-feedback response measurement with the DfMux readout system as follows. By injecting a single sideband signal, we induce modulation in TES power dissipation over a frequency range encompassing the detector response. The modulated current signal induced by TES heating effect is measured, allowing for the ETF response characterization of the detector. With the injection of an upper sideband, the TES readout current shows both an upper and a lower sideband. We model the upper and lower sideband complex ETF response and verify the model by fitting to experimental data. The model not only can fit for certain physical parameters of the detector, such as loop gain, temperature sensitivity, current sensitivity, and time constant, but also enables us to estimate the systematic effect introduced by the multiplexed readout. The method is therefore useful for in situ detector calibration and for estimating systematic effects during astronomical telescope observations, such as those performed by the upcoming LiteBIRD satellite. [ABSTRACT FROM AUTHOR]

This study analyzes the risk‐adjusted performance of commodity exchange‐traded funds (ETFs) across diverse market conditions. Examining monthly returns from December 2004 to June 2022, our findings suggest that commodity ETFs underperformed US stocks, indicating limited diversification benefits. However, we document positive α during turbulent market periods like the COVID‐19 crisis, signifying potential resilience. Furthermore, our factor regressions reveal that shifts in the global commodity price index and disposable personal income significantly influence commodity ETFs' excess returns, pointing to broader economic and income‐related trends. Commodity ETFs exhibit lower Value‐at‐Risk and Expected Shortfall compared to stock market indices, indicating reduced downside risk exposure for investors. Given the increasing popularity of commodity ETFs, these insights hold substantial significance for market participants. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to add further evidence to adoption criteria for "revolutionary" business techniques. Design/methodology/approach: Adoption criteria for business techniques with a high degree of novelty have been developed earlier. The case of exchange-traded funds supports the earlier findings. The methodology applied is explicative. Findings: The analysis supports findings that an effective response to a problem, the availability of a controllable procedure, the means to apply the procedure easily and the hardware jointly explain adopting "revolutionary" business techniques. Research limitations/implications: The results of case studies, in general, do not permit induction. More research might identify additional adoption criteria or falsify the presently obtained results. Therefore, further research is invited. Practical implications: Managers seeking or being introduced to new techniques in business administration might use the criteria outlined here for their evaluation. Originality/value: The author believes this paper corroborates earlier findings on adopting "revolutionary" business techniques that draw on theoretically developed technologies. [ABSTRACT FROM AUTHOR]

The popularity of environmental, social, and governance (ESG) investing has soared over the past few years, with a surge in public attention toward sustainability and a heightened interest in ESG funds. This study aims to explore whether investors' focus on ESG investing has an impact on the performance of ESG ETFs. To assess investor attention, the authors use the Search Volume Index (SVI) from Google Trends and test the panel data consisting of US equity ESG ETFs. The findings indicate that investor attention plays a significant role in ESG ETF returns, which demonstrates that investors reflect their investment interests through trading. Furthermore, the study reveals that ESG ETFs underperformed the market over the 2021–2022 period and that ESG scores of ETFs positively influenced ETF returns. By using the SVI to measure investor attention directly, the authors provide valuable new insights into the impact of investor attention on ETF returns. [ABSTRACT FROM AUTHOR]

In the literature on score-driven models, alternative choices of the scaling parameters of the conditional score terms are used, but the optimal choice of those parameters is an open question. Although there are score-driven models for which the choice of the scaling parameters is irrelevant, there are important score-driven models for which score-driven scale filters appear in the information matrix, and the choice of the scaling parameters is relevant. We focus on the quasi-autoregressive (QAR) plus Beta- $t$ t -EGARCH (exponential generalized autoregressive conditional heteroscedasticity) model, by using data on the Vanguard Standard & Poor's 500 (S&P 500) exchange-traded fund (VOO) and all available S&P 500 stocks for the period of 2013–2023. For QAR plus Beta- $t$ t -EGARCH, each updating term is the product of a scaling parameter and a conditional score, and we use specific alternative scaling parameters from the literature. For different scaling parameters in the scale filter (volatility), alternative location and scale filters coincide. For different scaling parameters in the location filter (expected return), alternative location and scale filters differ significantly. For the statistical and volatility forecasting performances of VOO and most of the S&P 500 stocks, the best-performing scaling parameter for the score-driven location is the conditional inverse information matrix. [ABSTRACT FROM AUTHOR]

• Adoption of sustainable investing exchange-traded funds is shaped by various factors. • Insurance companies and pension funds with positive effects. • Also supporting impact of stock markets, new technologies and financial development. • Lesser importance of the financial motives. • In case of mutual funds and institutional variables results are mixed. Despite the growing interest in various topics related to sustainable (ESG) investing, some issues remain understudied, such as the determinants of their utilization at the macro level. This paper contributes to the state of knowledge two-directionally. First, it shows the development of sustainable investing exchange-traded funds (ETFs) in European countries. Second, it traces the significant determinants of adopting sustainable investing/ESG ETFs in Europe. More specifically, we aim to determine which financial, technological, social or institutional factors have the most significant impact on the growth of levels and over-time dynamics of the sustainable investing ETFs. The empirical sample covers five European economies: France, Germany, Italy, Switzerland, and the United Kingdom and the period of the analysis is 2006–2020. Adopting panel regression analysis, we investigate twenty different variables that potentially impact the development of sustainable investing ETFs across examined countries. Our results confirm the positive effects of the development of insurance companies and pension funds for the assets of the ESG ETFs. Also, factors such as stock markets development, ICT adoption, financial access and literacy, and the prevalence of tertiary-level education demonstrate a positive impact on ESG ETFs. The role of the financial performance and tax levels resulted in being neutral, thus indicating the lesser importance of the financial motives in relation to the other factors. The results were mixed in the case of the mutual funds and institutional variables. [ABSTRACT FROM AUTHOR]

It remains a challenge for existing financial models to accurately capture the shapes of implied volatility (IV) of options with all maturities simultaneously. Inspired by Chen et al.'s empirical finding, 'the shorter the option expiry, the higher the IV is', we propose a novel and simple approach to solve this challenge, by introducing a term-structure-based correction (i.e. an exponential increase function of the options expiry) to the volatility of volatility (vol–vol) term of the classical Heston stochastic volatility model. We derive an approximate formula for the IV under the corrected model with the perturbation method and further apply the formula to predict the IVs of options written on the Shanghai Stock Exchange 50 ETF. Numerical experiments and empirical results show that the introduction of a term-structure-based correction function surely overcomes the deficiency of the classical Heston model in capturing the short-term IVs, thus improving notably its performance of IV forecasting. [ABSTRACT FROM AUTHOR]

Traditional options pricing relies on underlying asset volatility and contract properties. However, asset volatility is affected by the "lead–lag effects," known as the "momentum spillover effect." To address this, we propose a proxy measuring correlated options' influence based on maturity date. Findings indicate that 1‐day‐lagged proxy indicators positively impact option returns. Furthermore, to capture the dynamic effects of correlated options, we introduce a deep graph neural network‐based model (GNN‐MS). Empirical results on Shanghai Stock Exchange 50 exchange‐traded fund options reveal GNN‐MS significantly outperforms classics, enhancing root‐mean‐square error by at least 8.81%. This study provides novel insights into option pricing considering momentum spillover effects. [ABSTRACT FROM AUTHOR]