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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.

This paper aims to introduce a new perspective on long-term stock return predictability by focusing on the relative (individual and hybrid) informative power of a wide range of accounting (firm-related), technical and macroeconomic factors while considering the past performance of the stocks using machine learning algorithms.

The sample includes a panel data set of 94 non-financial firms listed in Egyptian Exchange 100 index from 2014: Q1 to 2019: Q4. Relativity has been investigated by comparing relevant factors’ individual and combined informative power and differentiating between losers and winners based on historical stock returns. To predict the quarterly stock returns, Gaussian process regression (GPR) has been used. The robustness of the results is examined through the out-of-sample test. This study also uses linear regression (LR) as a benchmark model.

The past performance and the presence of other predictors influence the informative power of relevant factors and hence their predictive ability. The out-of-sample results show a trade-off between GPR and LR with proven superiority to GPR in limited experiments. The individual informative power outperforms the hybrid power, in which macroeconomic indicators outperform the remaining sets of indicators for losers, while winners show mixed results in terms of various performance evaluation metrics. Prediction accuracy is generally higher for losers than for winners.

This study provides interesting insight into the dynamic nature of the predictor variables in terms of stock return predictability. Hence, this study also deepens the understanding of asset pricing in a way that directly contributes to practitioners’ portfolio diversification strategies.

In concern of the chaos of factors in the literature and its accompanying misleading conclusions, this study takes another look at the approach that studies stock return predictability. To the best of the authors’ knowledge, this is the first study in the Egyptian context that re-examines the predictive power of the previously discovered factors from a different perspective that highlights their relative nature.

The purpose of this paper is to analyse the relation between stock market volatility and macroeconomic fundamentals for G-7 countries using monthly data over the period from July 1985 to June 2015.

The empirical methodology is based on two steps: in the first step, the authors obtain the conditional volatilities of stock market returns and macroeconomic variables through the GARCH family of models. The authors also incorporate the impact of early 2000s dotcom and the global financial crises. In the second step, the authors estimate multivariate vector autoregressive model to analyze the dynamic relation between stock markets return and macroeconomic variables.

The overall results for G-7 countries indicate a weak volatility transmission from macroeconomic factors to stock market volatility at individual level but the collective impact of volatility transmission is highly significant. Although, the results of block exogeneity indicate a bidirectional causality except UK, but the causal linkage is quite weak from stock market to macroeconomic variables. Moreover, the local financial variables excluding interest rate are closely integrated, and the volatility of industrial production growth and oil price are identified as the most significant macroeconomic factors that could possibly influence the directions of stock markets.

This research establishes the nature of the links between stock market and macroeconomic volatility. Research to date has been unable to satisfactorily establish the empirical nature of such links. The authors believe this paper begins to do this.

This study aims to examine the links between oil price shocks and Gulf Cooperation Council (GCC) stock markets from February 2004 to December 2019. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors use the Ready (2018) oil price decomposition method and the quantile regression approach to conduct the analysis.

Initial results show a positive oil price change increases stock returns, while greater volatility decreases returns. The oil shock decomposition results reveal a significant positive impact of supply-side shocks on stocks. This contrasts with the literature that argues demand-side shocks are more important. While factors such as liquidity and the lack of hedging instruments can increase the vulnerability of GCC equities to oil price shocks, the result reflects the unique economic structure of the GCC bloc, notably, marked by dependency on oil revenues. In analysing quantile-based results, oil supply shocks mainly exhibit lower-tail dependence, while the authors do uncover some evidence of demand-side shocks affecting mid and upper-tail dependence.

Acknowledging the presence of endogeneity in the relation between oil and economic activity, to the best of the authors’ knowledge, this study is the first to combine the oil price decompositions of Ready (2018) with a quantile regression framework in the GCC context. The results reveal notable difference to those previously reported in the literature.

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.

This paper investigates the effect of political connections on the capital structure of banks before and after the financial crisis in Gulf Cooperation Council (GCC) countries.

This paper employs the natural experiment that the financial crisis offers and uses a difference-in-differences model to investigate the effect of political connections on capital structure. Capital structure is measured by the total debt to total assets ratio. Control variables include bank size, growth, profitability, coverage ratio and volatility. The research sample includes all the banks in the GCC from 2005 to 2016.

The authors find that political connections negatively affect banks capital structure decisions. The results contradict the claim that politically connected firms tend to sustain higher debt due to government privilege and a lower chance of bankruptcy. Additionally, the results show that after the financial crisis, politically connected banks de-lever more compared to non-connected counterparts. This could suggest that the degree of support received by connected banks changes or that they exploit their retained earnings for financing (individual country results, however, suggest that leverage increases in Qatar).

This paper provides several contributions. First, GCC countries present an interesting and important area in which to study the relation between political connections and capital structure as it represents a mix of newer markets that seek to attract investors and foreign capital. Second, to the best of our knowledge, the present study is the first to examine the effect of the political connection and capital structure in GCC region where royal families play a significant role, especially for banks. Third, our paper is the first to link connections with leverage after the financial crisis in the banking sector. Moreover, our paper is the first to investigate this phenomenon in the GCC countries using manually collected primary data.

The purpose of this paper is to consider the economic information content within several popular stock market factors and to the extent to which their movements are both explained by economic variables and can explain future output growth.

Using US stock portfolios from 1964 to 2019, the authors undertake three related exercises: whether a set of common factors contain independent predictive ability for stock returns, what economic and market variables explain movements in the factors and whether stock market factors have predictive power for future output growth.

The results show that several of the considered factors do not contain independent information for stock returns. Further, most of these factors are neither explained by economic conditions nor they provide any predictive power for future output growth. Thus, they appear to contain very little economic content. However, the results suggest that the impact of these factors is more prominent with higher macroeconomic risk (contractionary regime).

The stock market factors are more likely to reflect existing market conditions and exhibit a weaker relation with economic conditions and do not act as a window on future behavior.

Fama and French three-factor model still have better explanations for stock returns and economic information more than any other models.

This paper contributes to the literature by examining whether a selection of factors provides unique information when modelling stock returns data. It also investigates what variables can predict movements in the stock market factors. Third, it examines whether the factors exhibit a link with subsequent economic output. This should establish whether the stock market factors contain useful information for stock returns and the macroeconomy or whether the significance of the factor is a result of chance. The results in this paper should advance our understanding of asset price movement and the links between the macroeconomy and financial markets and, thus, be of interest to academics, investors and policy-makers.

This paper seeks to examine the nature of spillovers between output and stock prices using both a long annual time series spanning 200 years and a shorter but quarterly observed data set.

The authors’ particular interest is to examine both the time-varying nature of the spillovers and spillovers across the frequency using wavelet analysis.

The results reveal an interesting detail that is missed when considering spillovers for the raw data. Using annual long run data, spillovers in the raw data are in the order of approximately 10 per cent for stocks to output and 25 per cent for output to stocks. But this increases up to 50 per cent and above (in both directions) when considering different frequencies. Similar results are reported with the quarterly data, although the differences between the raw data and the wavelets are smaller in nature. Finally, output explains more of the variation in stocks than stocks explains in output.

The nature of these results is important for policy-makers, market participants and academics alike, while the use of wavelets provides information across different frequencies.

Market-based value style equity portfolios do not systematically outperform market-based growth style equity portfolios, despite considerable academic research that suggests that they should. This is an unresolved puzzle in the long lineage of work on this topic. The purpose of this paper is to question whether portfolio constituency rules employed by active growth and value equity investment managers might explain this puzzle.

The authors use the traditional research design and methodology of Fama and French (1993) to ensure comparability of results to prior research. Further, the authors adapt the return decomposition method of Keim (1999) to specifically answer the question in the research.

The authors find that restrictive constituency rules that omit the smallest, most illiquid stocks improve the performance of both value and growth stock portfolios. However, the authors find the impact of constituency rule restrictions on portfolio returns to be asymmetric with respect to value and growth in the small-cap investment space. Growth portfolios benefit from these changes more than value portfolios. Consistent with prior research, the authors find that value and growth style portfolios constructed from more liquid equities to be void of a statistically significant value-minus-growth return premium. The authors suggest these results might go a long way in explaining why market-based growth fund returns generally equal those of their value fund counterparts over time.

The research question central to the research, the value equity premium, has been investigated by researchers around the world over the last 20 years. The 20 year lineage of global published research on the value equity premium does, however, contain several unresolved questions. The paper specifically asks why the premium, long observed in global equity market returns, does not appear in market-based passive or active equity portfolios. This puzzle exists at the heart of the origins of the return premium itself and has serious implications for investment practitioners. If the matter cannot be reconciled, then market participants might rightly view the entire 20 year lineage of published research as irrelevant. The paper is one of few that has now extended the long lineage of research to its application in real 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.