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This study explores the influence of the coronavirus disease 2019 (COVID-19) career experience on the investment behavior and risk tolerance of chief executive officers (CEOs). Specifically, this study focuses on CEOs' abilities to allocate financial assets and maintain solvency.

This study adopts a comprehensive approach to analyze financial assets and asset-to-liability ratios. Financial data and individual information of CEOs from listed companies are collected from 2020Q1 to 2021Q4, along with statistics on confirmed COVID-19 cases. Instrumental and alternative variables are used to examine the robustness and endogeneity of the research, ensuring a thorough analysis.

A significant positive correlation is revealed between CEOs' COVID-19 career experience and their capacity to effectively allocate financial assets. However, COVID-19 has a negative effect on firm performance in terms of solvency. These findings contribute to the empirical evidence linking the pandemic to company performance, representing part of the initial research in this area.

The study suggests that the implementation of potential policy implications, such as loose monetary policies and tax and fee reduction measures, may alleviate the tax burden on listed companies.

This study investigates the diversification benefits of multiple cryptocurrencies and their usefulness as investment assets, individually or combined, in enhancing the performance of a well-diversified portfolio of traditional assets before and during the pandemic COVID-19.

This paper uses two optimization techniques, namely the mean-variance and the maximum Sharpe ratio. The naïve diversification rules are used for comparison. Besides, the Sharpe and the Sortino ratios are used as performance measures.

The results show that cryptocurrencies diversification benefits occur more during the COVID-19 pandemic rather than before it, with the maximum Sharpe ratio portfolio presenting its highest performance. Furthermore, the results suggest that, during COVID-19, the diversification benefits are slightly better when using a combination of cryptocurrencies to an already well-diversified portfolio of traditional assets rather than individual ones. This serves to improve the performance of the maximum Sharpe ratio portfolio, and to some extent, the naïve portfolio. Yet, cryptocurrencies, whether added individually or combined to a well-diversified portfolio of traditional assets, don't fit in the minimum variance portfolio. Besides, the efficient frontier during COVID-19 pandemic dominates the one before COVID-19 pandemic, giving the investor a better risk-return trade-off.

To the best of the author's knowledge, this is the first study that examines the diversification benefits of multiple cryptocurrencies both as individual investments and as additional asset classes, before and during COVID-19 pandemic. The paper covers all analyses performed separately in previous studies, which brings new evidence regarding the potential for cryptocurrencies in portfolio diversification under different portfolio strategies.

This study aims to test mutual fund superiority, comparing the performance of 646 Islamic mutual funds with 475 ethical funds and conventional proxies.

This study uses statistical methods including paired t-statistics of independent samples, one-way Bonferroni test–analysis of variance–F-statistic for testing means equality, the chi-squared test for median equality and regression models corrected for heteroscedasticity. These methods are used to identify superiority of mutual funds and to validate the significance of the results.

The findings confirm the superiority of conventional funds over ethical funds and ethical funds over Islamic funds. Both ethical and Islamic funds, however, outperform conventional proxies during some recessionary periods. Moreover, stronger performance is recorded for Islamic funds in Europe and North America regions and across age and asset allocation categories, but limited support for reversal fund size, composition focus and reversed price effect.

These findings should assist investors when deciding to invest and motivate Islamic and ethical funds to improve their portfolio formation and asset allocation strategies set by their professional managers.

The originality of this study is in its comprehensive approach in that it compares the performance of funds after accounting for such characteristics as fund objectives, size, age, asset allocation, geographical investment focus, fund composition focus, share price levels and the effect of global crises. This study approach is not only original and productive in documenting Islamic funds’ performance for the past three decades (1990–2022) but can also update the literature on these characteristics collectively and individually.

The purpose of this paper is to explore and evaluate the main segments of existing empirical literature related to Sovereign Wealth Funds (SWFs) and provide a thorough investigation of their research questions, theoretical frameworks, data selections and research methodologies.

The literature on SWFs has been split into three main streams: qualitative studies with theoretical contributions aiming to conceptualize the phenomenon of SWFs; normative assessments of the optimal asset allocations of SWFs; and empirical works that aim to investigate different perspectives of SWFs. The paper attempts to review the state of existing literature relating to these areas by answering specific questions.

Despite their significant size and potential impact, the literature on SWFs seems to be still in its infancy. The paper collects insights from previous literature, addresses its difficulties and challenges.

The characteristics of the previous empirical literature and the challenges facing this line of research offer an insightful thought for the future research works in this topic.

The paper offers a thorough assessment of the existing empirical research on SWFs and shade some light on the techniques and procedures used.

The paper examines how equity mutual funds manage their liquidity. Specifically, the authors investigate what strategies fund managers use to meet investor redemption demand, whether these strategies vary over time, whether different type of funds employ different liquidation practices in response to fund outflows, and whether liquidity strategies impact fund performance.

This study uses a sample of U.S. actively managed equity funds over the period 1990–2019. The authors use three different measures to capture funds' liquidity management practices. The authors examine the relationship between fund liquidity measures and net flow by estimating panel regressions over the entire sample period, on 2 sub-sample periods of different market conditions measured by the magnitude of implied market volatility (VIX), and on 2 sub-samples of funds with different liquidity profiles. The authors also examine the relationship between funds liquidity status and near-term performance through both a portfolio approach and regression analysis.

The authors find that on average, mutual funds reduce their cash position and the most liquid asset holdings to meet investor redemption demand. Furthermore, the authors find that fund managers choose different liquidity strategies under different market conditions. During highly volatile markets, mutual funds use cash and their most liquid assets to meet redemption demand while maintaining their portfolio liquidity. During low volatility markets, mutual funds rely heavily on cash but less on liquidity assets and tend to increase their portfolio illiquidity. Upon further examination of funds across portfolio liquidity profiles, the authors find that liquid funds increase portfolio liquidity when facing outflows, whereas illiquid funds maintain their portfolio liquidity position. The different liquidity strategies have significant impact on funds' near-term performance. Specifically, liquid funds underperform illiquid funds following the increase in their portfolio liquidity.

This paper contributes to the literature on liquidity management by asset managers by taking a holistic approach to examine funds liquidation practice at the portfolio holdings level. Considering the recent increase in market volatility, mutual fund liquidity management has drawn an increasing share of interest and attention from policy makers, investment professionals, and academia. This study covers both uncertain and stable market states during a long sample period and provides empirical evidence on the flow-induced liquidation decisions by equity mutual funds. In addition, this paper also contributes to the literature on mutual fund performance by providing evidence that funds' liquidity strategies significantly impact their near-term performance.

Referring to “behavioural finance” and “normative model” theories, this study explores the relative significance of behavioural heuristic biases in the investment decisions of real estate investment trusts (REITs) when compared with the conventional normative decision factors, with an ultimate aim to identify the significant behavioural factors that should be avoided to ensure rational asset acquisitions and market efficiency.

A triangulation approach was adopted. Qualitative multiple case studies were conducted, with four cases selected from Australian and New Zealand REITs across the industry, to identify what normative and behavioural finance factors are involved in investment decisions. This formed the basis for the subsequent expert review survey to explore how significant the behavioural factors were manifested in the judgement when compared with the normative factors.

Three out of four theoretical behavioural factors manifested themselves in the investment decisions: investor sentiment, anchoring factors and overconfidence. The overall impact of these three behavioural factors was that they were as significant as normative factors in investment decisions. The heuristic availability of information was found to have no significant effect on experienced REIT fund managers.

The findings were based on four multiple cases and an expert review survey of six frontline fund managers, which form a baseline upon which further research can be conducted to widen the scope of research to cover all REITs in Australasia so that the results can become more robust to benefit the entire market in the region.

As behavioural factors are significant in the decision-making process, REIT fund managers should raise awareness to avoid the significant behavioural factors identified, in particular investor sentiment, which was found to be the most significant one.

This study confirms the relative significance of behavioural factors in property investment decisions within the context of Australasian REITs and alerts fund managers to the ways they should follow to ensure rational investments and market efficiency. It also extends the scale of existing studies to cover not only Australia but also New Zealand for the benefit of the entire Australasian market.

This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

Based on the theory of performance feedback, this study aims to explore the theoretical relationship between performance shortfalls and the financialization of non-financial enterprises. It further analyzes the moderating effect of economic policy uncertainty (EPU) and organizational redundant resources.

Multiple regression analysis is used on 16,555 initial samples of 2,658 Chinese A-share issuing enterprises from 2007 to 2019 to empirically test the relationship between performance shortfalls and the financialization of non-financial enterprises, and an instrumental variables-generalized moments estimation model is also used to verify the robustness of the results.

The results reveal that the greater the performance gap below the aspiration level, the higher the degree of enterprise financialization. Moreover, EPU strengthens the relationship between performance shortfalls and financialization, whereas organizational redundant resources weaken the relationship between performance shortfalls and financialization.

Decision-makers should determine the aspirated performance level of enterprises to make investment decisions that are most conducive to the long-term development of enterprises. Each enterprise should establish scientific management evaluation and supervision systems to avoid financial investment behaviors that place too much emphasis on short-term performance.

This study finds that financialization is one of the reactions when performance of enterprises is lower than the aspiration level, thus expanding the functional dimensions of performance feedback and supplementing the research on the influencing factors of enterprise financialization. The results also reveal information about situational factors, helping identify the boundary conditions through which performance below aspirations affects enterprise financialization.

The objective of this systematic literature review (SLR) is to explore the current state of research in the field of household finance (HF). This study aims to summarize the existing research to highlight the importance of household finance in a nation’s economy. By exploring all conceptual and applied implications of HF, this study projects directions for future research to develop a comprehensive understanding of the subject.

This SLR is based on 112 articles published in peer-reviewed journals between 2006 and 2020 (Table 3). The methodology comprises five steps, namely, formulation of research questions, identification of studies, their selection and evaluation, analyses and syntheses and presentation of results.

The findings of this study show that studies on HF are gradually increasing worldwide with the USA registering the highest number of published research on the topic during the period under scrutiny. Notwithstanding the increasing attention and research on HF, empirical research in emerging economies is lagging. Additionally, this study finds that HF structure presents a perfect setting to understand how households compose their financial portfolio, make financial decisions and what factors influence their decisions.

This study is an SLR – an accurate and accepted method of reviewing available literature on a selected subject. However, the selection of inclusion and exclusion criteria depends on the researchers’ rationale which might lead to research bias. This should be considered an inherent limitation of SLR.

By synthesizing the contents of extant literature, this study presents important insights into HF. This study underlines the most discussed topics in the domain and identifies potential investigation areas. This study gives the knowledge of leading articles, authors and journals and informs scholars and academicians about the areas that need further investigation by portraying the complete picture of the subject in a systematic manner. Further, this study highlights that households make suboptimal financial decisions that affect their financial well-being. To reduce the adverse impacts of these decisions, policymakers and financial institutions must take steps to improve households’ use of formal financial markets. Household decisions can be reformed by enhancing consumers’ knowledge about financial products and services. Furthermore, households can be served better by offering customization in traditional financial products.

This study synthesizes the main findings of selected literature on HF. The expansion of studies on HF has generated the need to review the existing literature in a systematic manner. To the researchers’ best knowledge, this SLR is the first thorough study of available articles in the HF domain. This study presents the scope of future research by highlighting numerous aspects and functions of HF.

The aim of this research is to explore multiscale hedging strategies among cryptocurrencies, commodities, and GCC stocks. Particularly, this is done by evaluating the connectedness among these asset classes covering a period with COVID-19 implications. Using the wavelet approach, the present study aims to recommend whether there exist different time horizon-based hedging abilities across the asset classes.

The approach used in this study is a multiscale decomposition of time series based on wavelets of daily prices of 13 asset classes. Since the wavelet analysis allows to decompose the time series into its frequency components at different time scales by a filtering process the study covered 1-day, 8-day, and 64-day time horizons to examine the hedging properties across those asset classes.

The results of this study show that hedging effectiveness differs among stock markets over time. In some cases, cryptocurrencies may keep their hedging properties across time while in others they switch from safe haven to hedge devices. In almost all cases, the three main cryptocurrencies showed diversifying properties as was observed by the multiscale correlation and hedge ratio estimations. In a competing sense, gold showed safe haven properties across time than cryptocurrencies except at an 8-day time scale where hedge ratios were low, positive and statistically different from zero that could be interpreted as a good hedge device in the medium term.

Though this research has considered a set of thirteen asset classes, it was limited to a period in which most cryptocurrencies started trading for the first time which reduces the number of observations compared to Bitcoin prices and stable coins such as Ethereum, Ripple, and Bitcoin Cash. Also, the research was focused on the GCC stock markets which may have different results as compared to other regional markets of Asia or Latin America. A comparative analysis in future could be another area of research in future.

This study has some significant policy implications. The cryptocurrency market is severely affected by demand and risk shocks to crude oil prices during the COVID-19 period. From the investor's point of view, diversification benefits can be obtained by combining cryptocurrencies along with oil-related products during episodes of financial turmoil and COVID-19 pandemic. The GCC region is constantly endeavoring to adopt more scientific tools and mechanisms of investment, and therefore, this study's results will provide some useful directions to the government, policymakers, financial institutions, and investors.

The current study covers a big bunch of 13 assets spanning across financial and real assets. This is based on literature gap and hence, will be a significant addition to the existing literature. Moreover, the GCC region is emerging as a global investment hub and this study will provide investors dynamic hedging strategies across these asset classes.