Search results

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

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

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

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

This paper discusses the meaning and measurement of negative value added both in real and money terms. Examples as to how it might occur are provided and methods of dealing with inconsistencies which arise because of it, will be outlined.

The purpose of this paper is to examine the inter-relations among the US stock indices.

Data of nine US stock indices spanning a period of sixteen years (2000-2015) are employed for this purpose. Asymmetries are examined via an error correction model. Non-linear inter-relations are researched via Breitung’s nonlinear cointegration, a M-G nonlinear causality model, shocks to the forecast error variance, a shock spillover index and an asymmetric VAR-GARCH (VAR-ABEKK) approach.

The inter-relations are significant. The results are robust across all types of inter-relations. They are highest in the Lehman Brothers sub-period. Higher stability after the EU debt crisis, enhances independence and growth for the US stock indices.

To the best of the knowledge, this is the first study to examine the inter-relations of US stock indices. Most studies on inter-relations concentrate on the portfolio analysis to reveal diversification benefits among various asset markets internationally. Hence this study contributes to this literature on the inter-relations of a specific asset market (stock), and in a specific nation (USA). The evident inter-relations support the notion of diversification benefits in the US stock markets.

This paper aims to investigate whether Islamic and conventional equity indices offer some alpha. These indices are expected to offer no alpha being value-weighted, passive and unmanaged.

This paper used monthly data from 1996 to 2016 of four Dow Jones (DJ) and one financial times stock exchange (FTSE) Islamic equity indices and five conventional Morgan Stanley Capital International (MSCI) equity indices. This study used a simple ordinary least square (OLS) rolling window regressions to generate the alphas and risk loadings when adjusting for prominent pricing factor models.

The findings from OLS regressions suggest that DJ Islamic indices of Japan, Europe and World generate significant alphas, whereas, MSCI conventional indices of Asia/Pacific, USA and World generate significant alpha when risk-adjusted for pricing factor models. However, in 36-month rolling window regressions, all Islamic indices generate significant alpha and factor loading. The magnitude of alpha and factor loading changes over time.

The finding shows that the Shari’ah-compliant investment fund’s alpha must be adjusted with the respective benchmark index alpha to measure the fund manager’s skill performance quantitatively.

To the best of the author’s knowledge, this is the first study that investigates and compares the Islamic, as well as conventional indices for abnormal returns, which are adjusted for both Fama–French five and q-theory-based four assets pricing risk factors and as a benchmark for Shari’ah-compliant fund’s performance.

The purpose of this paper is to examine the information content in the Standard & Poor (S&P) 500 index revision and its impact on the corporate bonds and earnings of the firms whose stocks are added to or deleted from the index.

The paper uses panel regressions on a 13-year sample of the companies added and deleted from the S&P 500 index.

The regression results on the bond yields and earnings show that analysts and investors draw positive (negative) information from Index additions (deletions) and adjust their expectations of the firm performance as well as the required rates of return on corporate bonds after index revisions.

The paper suggests that deletions from the Index have significantly negative impacts on corporate bonds and earnings performance of deleted firms while additions to the index do not have significant impacts on the bonds or realized earnings of added firms.

This paper uses corporate bonds and earnings to test competing hypotheses proposed to explain the excess stock returns of index revision, including information content hypothesis and liquidity hypothesis. The results are consistent with the information content hypothesis and do not support the liquidity hypothesis.

This study aims to investigate the day-of-the-week (DoW) effect in globally listed private equity (LPE) markets using daily data covering the period 2004–2021.

To investigate the existence of the DoW effect in globally LPE markets, ordinary least squares regression, generalised autoregressive conditional heteroscedasticity (GARCH) regression and robust regressions are used. In addition, robustness audits are conducted by subdividing the sampling period into two sub-periods: pre-financial and post-financial crisis.

Limited statistically significant evidence is found for the DoW effect. By taking time-varying volatility into account, a statistically significant DoW effect can be observed, indicating that the DoW effect is driven by time-varying volatility. Economic significance is captured through visual inspection of average daily returns, which illustrate that Monday returns are lower than the other weekdays.

The results have important implications on whether to adopt a DoW strategy for investors in LPE. The findings show that higher returns on selected days of the week for certain indices are possible.

To the best of the author’s knowledge, this paper provides the first study to examine the DoW effect for globally LPE markets by using LPX indices and contributes valuable insights on this growing asset class.

This study aims to examine the attractiveness of the regional Dow Jones Sustainability Indexes (DJSI) and several renewable energy indexes during December 31, 2010 to December 31, 2019. This study uses a risk-return analysis and a set of explanatory factors. Lastly, this study conducts a comparative analysis of these indexes with conventional indexes.

This study uses data from Eikon, a Thomson Reuters database. To analyze the indexes’ behavior, this study uses the indexes’ annual return as of December 31 for each year. Next, this study estimates the Fama and French’s five-factor model using an ordinary least squares regression for regional DJSI and renewable energy indexes.

The results show that regional DJSIs delivered returns both above and below conventional indexes. In contrast, renewable energy indexes had high betas and negative returns, making them unattractive to investors.

The results imply the need for public financing programs that support the transition to a sustainable economy and reduce risk and increase the return on private investment.

This study provides insights for policymakers regarding the importance of sustainability indexes in the transition to a green economy.

This study contributes to the growing literature on Fama and French’s five-factor model of sustainability indexes, especially in the current context characterized by intense green political changes. In particular, this study complements the few studies that have addressed the economic implications of renewable energy indexes in markets.

This paper aims to capture tail dependence between sentiment index and Shanghai composite index (SCI) by proposing a sentiment index based on text mining.

Online text mining and the Copula model were used in this study.

First, the paper finds herding effect in the expression of investors’ sentiment from online text data, and the usage occurrence frequency of most vocabulary is less correlative with SCI. Second, given these two features, the paper uses weighted divide-and-conquer algorithm to construct a sentiment index. Finally, because of multivariate non-Gaussian joint distribution between them, the paper uses the Copula model to detect their tail dependences, and finds that both upper and lower tail dependences could have a significant influence between positive sentiment and SCI, with a higher probability on the upper one. Additionally, only the upper tail dependence exhibits the significant influence between negative sentiment and SCI.

This paper proposes a framework of constructing investment sentiment index with the weighted conquer-and-divide algorithm, and characterizes tail dependence between sentiment index and SCI. The implication can measure the environment of investment market of China and provide an empirical ground for bandwagon effect and bargain shopper effect.

This study aims to predict the financial performance of Islamic banks with sentiments of management from the textual information in annual reports.

The study uses data from 33 Islamic banks in six Islamic countries from 2006 to 2020. The authors estimate the model using the system GMM because it helps dealing with endogeneity problem, which are inherent in panel data.

The findings of the study reveal that there is a strong relationship between the sentiment expressed by management in annual reports and the current (future) financial performance of Islamic banks. The higher the positive sentiments of management, the better financial performance. In addition, the study also suggests that negative sentiments using term frequency-inverse document frequency is linked to a decrease in banks’ financial performance.

The study does not present the Islamic view on sentiment analysis in the context of Islamic scriptures due to the unavailability of a relevant dictionary.

The findings of the study suggest that developing accurate models with the help of textual information for performance prediction of Islamic banks help shareholders, regulators and policymakers avoid devastating events. Using textual information may also help reduce the information asymmetry between the management and shareholders, which may lead to more efficient bank supervision. The study can also help investors evaluate their prospective investments in the Islamic bank.

To the best of the authors’ knowledge, this study is the first of its kind that uses management sentiments for performance prediction of the Islamic banking sector. It may add a valuable contribution to the existing literature.

The purpose of this paper is to empirically examine the volatility and return spillover between exchange-traded funds (ETFs) and their respective benchmark indices in India. The paper uses time series data which consist of equity ETF and respective index returns.

The study uses autoregressive moving average–generalized autoregressive conditional heteroscedasticity and autoregressive moving average–exponential generalized autoregressive conditional heteroscedasticity models. The study uses data from the inception date of each ETF to December 2016.

The findings of the paper confirm that there is unidirectional return spillover from the benchmark index to ETF returns in most of the ETFs. Furthermore, ETF and benchmark index return have volatility persistence and show the presence of asymmetric volatility wherein a negative news has more influence on volatility compared to a positive news. Finally, unlike unidirectional return spillover, there is a bidirectional volatility spillover between ETF and benchmark index return.

The study has several practical implications for investors and regulators. A positive daily mean return over a fairly long period of time indicates that the passive equity ETFs can be a viable long-term investment option for ordinary investors. A bidirectional volatility spillover between the ETFs and benchmark index returns calls for the attention of the market regulators to examine the reasons for the same.

ETFs have seen fast growth in the Indian market in recent years. The present study considers the longest period data possible.