Search results

This study aims to examine the relation between illiquidity, feedback trading and stock returns for several European markets, using panel regression methods, during the financial and the sovereign debt crises. The authors’ interest here lies twofold. First, the authors seek to compare the results obtained here under crisis conditions with those in the existing literature. Second, and of greater importance, the authors wish to examine the interaction between liquidity and feedback trading and their effect on stock returns.

The authors jointly model both feedback trading and illiquidity, which are typically considered in isolation. The authors use panel estimation methods to examine the relations across the European markets as a whole.

The key results suggest that in common with the literature, illiquidity has a negative impact upon contemporaneous stock returns, while supportive evidence of positive feedback trading is reported. However, in contrast to the existing literature, lagged illiquidity is not a priced risk, while negative shocks do not lead to greater feedback trading behaviour. Regarding the interaction between illiquidity and feedback trading, the study results support the view that greater illiquidity is associated with stronger positive feedback.

The study results suggest that when price changes are more observable, due to low liquidity, then feedback trading increases. Therefore, during the crisis periods that afflicted European markets, the lower levels of liquidity prevalent led to an increase in feedback trading. Thus, negative liquidity shocks that led to a fall in stock prices were exacerbated by feedback trading.

The aim of this paper is to examine dynamic linkages between price and rent and between property types. Intuition suggests that housing market segments experience different market cycles in response to macroeconomic shocks. However, they may be dynamically interlinked in urban areas because of substitutability. The linkage may even change, if preference weakens for multiple occupancies. A sudden reduction in apartment demand may create repercussions to other housing segments. Past analyses, despite their contributions, are static and do not consider possible linkages between property types. To fill this void, this paper investigates the price-rent dynamics for urban homes by adopting the case of Singapore.

This paper applies a methodology from Phillips et al. (2015) to Singaporean housing (price and rent) data. Phillips et al. (2015) recently proposed a test for an explosive root in time series data and has spurred several empirical applications in the bubble literature.

This paper finds for Singapore that the markets were subjected to explosive growth (where rents grew at a higher rate than prices did) during the Global Financial Crisis. Also, the results suggest that rent drives price and that non-landed housing (offices in central areas) leads to other residential housing (non-residential housing) in both price and rent.

Overall, the present findings suggest that rent drives price, while property types are interlinked. Non-landed homes and offices in central areas are the sources of repercussions. Under normal circumstances, rental shocks may be propagated positively from nonlanded housing (central offices) to the other residential (non-residential) property types as the present findings suggest, which enables us to infer that a decrease in non-landed housing (central offices) rent may lead to an increase in rent on other property types because pandemic shocks only shift demand fromone property type to another, unlike typical macroeconomic shocks.

Urban homes are faced with uncertainty arising from the COVID-19 outbreak for which city residents have a stronger incentive to exile to suburbs. Urban life may no longer be attractive because of social distancing and work from home policy. This has implications for urban home demands that are closely linked to urban house price and rent. In the present study, the paper set out to investigate the price-rent and property-type dynamics for urban homes in Singapore.

This paper aims to ask whether a range of stock market factors contain information that is useful to investors by generating a trading rule based on one-step-ahead forecasts from rolling and recursive regressions.

Using USA data across 3,256 firms, the authors estimate stock returns on a range of factors using both fixed-effects panel and individual regressions. The authors use rolling and recursive approaches to generate time-varying coefficients. Subsequently, the authors generate one-step-ahead forecasts for expected returns, simulate a trading strategy and compare its performance with realised returns.

Results from the panel and individual firm regressions show that an extended Fama-French five-factor model that includes momentum, reversal and quality factors outperform other models. Moreover, rolling based regressions outperform recursive ones in forecasting returns.

The results support notable time-variation in the coefficients on each factor, whilst suggesting that more distant observations, inherent in recursive regressions, do not improve predictive power over more recent observations. Results support the ability of market factors to improve forecast performance over a buy-and-hold strategy.

The results presented here will be of interest to both academics in understanding the dynamics of expected stock returns and investors who seek to improve portfolio performance through highlighting which factors determine stock return movement.

The authors investigate the ability of risk factors to provide accurate forecasts and thus have economic value to investors. The authors conducted a series of moving and expanding window regressions to trace the dynamic movements of the stock returns average response to explanatory factors. The authors use the time-varying parameters to generate one-step-ahead forecasts of expected returns and simulate a trading strategy.

Muslim’s hope that the holy month of Ramadan will create something more valuable for them. Through fasting and good actions, they can get rewarded twice than they normally can achieve. With this motivation, the purpose of this paper is to investigate the holy month of Ramadan effect on the returns and volatility of the Shariah index in India.

Using the ordinary least square methods, this paper examines the impact of Ramadan effect on the returns of the Shariah index in India. This paper further investigates the impact of the holy month of Ramadan effect on the volatility of the Shariah index by applying GARCH-modified models. This paper categorizes the Ramadan days into three parts, namely God’s Mercy, God’s Forgiveness and Emancipation from hellfire to examine the relationship between the Ramadan effect and the returns and volatility of the Shariah index in India.

The results show that the returns during the month of Ramadan as a whole are statistically significant. The results further motivate that its last ten days have high influences than other days over the period. Finally, the study examines the Ramadan effect on volatility by applying GARCH modified models and finds an evidence of Ramadan effect during the first ten days of Ramadan month.

The positive impact of Ramadan increases on the days associated with higher worship intensity. The study provides an important information to the ethical investors to invest in the Shariah stocks during Ramadan days. This information is very useful for the investors to get an abnormal return during the Ramadan days.

This paper aims to examine the behaviour, both contemporaneous and causal, of stock and bond markets across four major international countries.

The authors generate volatility and correlations using the realised volatility approach and implement a general vector autoregression approach to examine causality and spillovers.

While results confirm that same asset-cross country return correlations and spillovers increase over time, the same in not true with variance and covariance behaviour. Volatility spillovers across countries exhibit a substantial amount of time variation; however, there is no evidence of trending in any direction. Equally, cross asset – same country correlations exhibit both negative and positive values. Further, the authors report an inverse relation between same asset – cross country return correlations and cross asset – same country return correlations, i.e. the stock return correlation across countries increases at the same time the stock and bond return correlation within each country declines. Moreover, the results show that the stock and bond return correlations exhibit commonality across countries. The results also demonstrate that stock returns lead movement in bond returns, while US stock and bond returns have predictive power other country stock and bond returns. In terms of the markets analysed, Japan exhibits a distinct nature compared with those of Germany, the UK and USA.

The results presented here provide a detailed characterisation of how assets interact both with each other and cross-countries and should be of interest to portfolio managers, policy-makers and those interested in modelling cross-market behaviour. Notably, the authors reveal key differences between the behaviour of stocks and bonds and across different countries.

The purpose of this paper is to examine the behavior of the stock market returns in the different days of the week and different months of the year in accordance with the Islamic calendar. Further, the study estimates the risk-adjusted returns to test the performance of the indices during the Ramadan and non-Ramadan days. Finally, the study investigates the impact of Ramadan on the returns and the volatility of the stock market indices in India.

Initially, the study applies the Ordinary Least Square method to test the day-of-the-week and the month-of-the-year effect of the common and Shariah indices. Next, the study employs the risk-adjusted measurement to examine the underperformance and over-performance of the indices for both the periods. Finally, the study estimates the GARCH (1,1) and GJR-GARCH (1,1) models to observe the impact of Ramadan on the returns and the volatility of the Shariah indices in India.

The study finds that an average return of the indices during the Ramadan days are higher than non-Ramadan days. Further, the average returns of the Shariah indices are significantly higher on Wednesday than other days of the week. In addition, the highest and significant mean returns and mean risk-adjusted returns of the indices during the Ramadan days are observed. Finally, the study finds an evidence of the Ramadan effect on the returns and volatility of the indices in India.

The study observes evidence that the Ramadan effect influences the Shariah indices, but not the common indices in the stock market of the non-Muslim countries. It indicates that the Ramadan creates the positive mood and emotions in the investors buying and selling activities. The study suggests that investors can buy the shares before Ramadan period and sell them during the Ramadan days to get an abnormal return in the emerging markets.

This paper aims to empirically test for multiple cointegrating vectors in a holistic manner. Theoretical developments imply bivariate cointegration among stock prices, dividends, output and consumption where independent models identify key theoretical cointegration vectors.

This paper considers both Johansen and Horvath–Watson testing approaches for cointegration. This paper also examines the forecasting power of these cointegrating relationships against alternate forecast variables.

The results suggest evidence of a long-run cointegrating relationship between stock prices, dividends, output and consumption, although not necessarily linked by a single common stochastic trend; each series responds to disequilibrium with greater evidence of a reaction from dividends and consumption – of note, output responds to changes in stock market equilibrium; and there is forecast power from the joint stock market–macro cointegrating vector for stocks returns and consumption growth over the historical average. Of particular note, other forecast models that include consumption perform well and suggest a key role for this variable in stock return and consumption growth forecasts.

This is the first paper to combine the cointegrating relationships between stocks, dividends, output and consumption. Thus, the empirical validity of stated theoretical hypotheses can be analysed. The forecast results also demonstrate the usefulness of this. They also show that forecast models that include consumption perform well and suggest a key role for this variable in stock return and consumption growth forecasts.

This study aims to investigate the effect of fear sentiment with a novel data set on Bitcoin’s (BTC) return, volatility and transaction volume. The authors divide the sample into two subperiods to capture the changing dynamics during the COVID-19 pandemic.

The authors retrieve the novel fear sentiment data from Thomson Reuters MarketPsych Indices (TRMI). The authors denote the subperiods as pre- and post-COVID-19 considering January 13, 2020, when the first COVID-19 confirmed case was reported outside China. The authors use bivariate vector autoregressive models given below with lag-length k, to investigate the dynamics between BTC variables and fear sentiment.

BTC market measures have dissimilar dynamics before and after the Coronavirus outbreak. The results reveal that due to the excessive uncertainty led by the outbreak, an increase in fear sentiment negatively affects the BTC returns more persistently and significantly. For the post-COVID-19 period, an increase in fear also results in more fluctuations in transaction volume while its initial and cumulative effects are both negative. Due to extreme uncertainty caused by the COVID-19 pandemic, investors may trade more aggressively in the initial phases of the shock.

The authors are convinced that the results in this paper have more far-reaching implications for other markets regulated by the states. BTC provides a natural benchmark to understand how fear sentiment drives and impacts the markets isolated from any interventions. Hence, the results show that in the absence of regulatory frameworks, market dynamics are likely to be more volatile and the fear sentiment has more persistent impacts. The authors also highlight the importance of using micro, asset-specific sentiment measures to capture market dynamics better.

BTC is not associated with any regulatory authority and is not produced by the governments and central banks. COVID-19 as a natural experiment provides an opportunity to explore the pure effects of market sentiment on BTC considering its decentralized and unregulated features. The paper has two main contributions. First, the authors use BTC-specific fear sentiment novel data set of TRMI instead of more general market sentiments used in the existing studies. Next, this is the first study to examine the association between fear and BTC before and after COVID-19.

The presence of a day-of-the-week effect has been investigated by many researchers over many years, using a variety of financial data and methods. However, differences in methodology between studies could have led to conflicting results. The purpose of this paper is to expand on an existing study to observe whether an analysis of the same data set with some added years and using a different statistical technique provide the same results.

The study examines the presence of a day-of-the-week effect on the Johannesburg Stock Exchange (JSE) indices for the period March 1995-2016, using a GARCH model.

The findings show that, contrary to the original study, the day-of-the week effect is present in both volatility and return equations. The highest and lowest returns are observed on Monday and Friday, respectively, while volatility is observed on all five days from Monday to Friday.

This study adds to the existing literature on day-of-the-week effect of JSE indices, where different patterns or, in some cases, no pattern have been noted. Few previous studies on the day-of-the-week effect observed the effect at micro-level for separate industries or made use of a GARCH model. The present study thus expands on the study of Mbululu and Chipeta (2012), by adding four additional observation years and using a different statistical technique, to observe differences that arise from a different time period and statistical technique. The results indicate that a day-of-the-week effect is mostly a function of the statistical technique applied.

The last decades have experienced increasingly integrated global political and economic dynamics ranging especially from the influence of exchange rates and trade amid other sources of uncertainties. The purpose of this study is to examine the exchange rate dynamics of Brazil, Russia, India, China, and South Africa (BRICS) and the Republic of Turkey.

Given this perceived global dynamics, the current study examined the BRICS countries and the Republic of Turkey's exchange rate dynamics by using the United States (US) monthly dollar exchange rate data between January 2002 and August 2019. The price bubble which is expressed as exceeding the real value of assets' prices which is observably caused by speculative movements is investigated by using the Supremum Augmented Dickey-Fuller (SADF) and the Generalized Supremum Augmented Dickey-Fuller (GSADF) approaches.

Accordingly, the GSADF test results opined that there are price bubbles in the dollar exchange rate of other countries except for the United States Dollar (USD)/Indian Rupee (INR) exchange rate. As the related countries are classified as developing countries in terms of their structure, they are also expectedly the subject of speculative exchange rate movements. Speculative movements in exchange rates may cause serious problems in national economies.

Thus, the current study provides a policy framework to the BRICS countries and the Republic of Turkey.