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This study aims to investigate the impact of the macroeconomic environment on South African industrial sector returns.

Using standardized coefficients derived from time-series factor models, the authors quantify the impact of macroeconomic influences on industrial sector returns. The authors analyze the structure of the resultant residual correlation matrices to establish the level of factor omission and apply a factor analytic augmentation to arrive at a specification that is free of omitted common factors.

The authors find that global influences are the most important drivers of returns and that industrial sectors are highly integrated with the global economy. The authors show that specifications that comprise only macroeconomic factors and proxies for omitted factors in the form of residual market factors are likely to be underspecified. This study demonstrates that a factor analytic augmentation is an effective approach to ensuring an adequately specified model.

The findings have a number of implications that are of interest to investors, econometricians and researchers. While the study focusses on a single market, the South African stock market, as represented by the Johannesburg Stock Exchange (JSE), it is a highly developed and globally integrated market. In terms of market capitalization, it exceeds the Madrid Stock Exchange, the Taiwan Stock Exchange and the BM&F Bovespa. Yet, a limited number of studies investigate the macroeconomic drivers of the South African stock market.

Investors should be aware that while the South African domestic environment, especially political risk, has an impact on returns, global influences are the greatest determinants of returns. No industrial sectors are insulated from global influences and this limits the potential for diversification. This study suggests an alternative set of macroeconomic factors that may be used in further analysis and asset pricing studies. From an econometric perspective, this study demonstrates the usefulness of a factor analytic augmentation as a solution to factor omission in models that use macroeconomic factors to proxy for systematic influences that describe asset prices.

The contribution lies in providing insight into a large and well-developed yet understudied financial market, the South African stock market. This study considers a much broader set of macroeconomic factors than prior studies. A methodological contribution is made by estimating and interpreting standardized coefficients to discriminate between the impact of domestically and internationally driven factors. This study shows that should coefficients not be standardized, inferences relating to the relative importance of factors will differ. Finally, the authors unify an approach of using pre-specified factors with a factor analytic approach to address factor omission and to ensure a valid and readily interpretable specification.

The purpose of this study is to analyze the benchmark model and offer a practical implementation of the macro stress test. The emergence of complicated instruments such as securitized products has rendered the risk management methodologies used in non-crisis periods insufficient. The macro stress test has become prominent as both an internal risk management tool for financial institutions and a way for supervisory authorities to maintain financial stability. However, no practical model is available for transforming macro stress scenarios into the risk parameters of an institution’s internal model.

This study presents a model for assessing a company’s default risk through a multi-level regression based on simultaneous estimates of the impacts of company-specific, macroeconomic and sector-specific risk factors using panel and time series data.

Equity capital, EBITDA, the current ratio and the fixed assets to fixed liability ratio are selected as the company-specific factors, while the CPI core rate, overall unemployment rate, overnight call rate and JGB yield to subscribers are selected as the macroeconomic factors. The correlation coefficients among the latent sector factors are significant at 5 per cent. In addition, the accuracy ratio values prove that the presented model has more default prediction power than do models without them.

This study is the first to provide a benchmark model for incorporating macroeconomic variables into a credit risk model for use in a bottom-up macro stress test.

The main purpose of this study is to examine whether macroeconomic variables could subsume the size and book‐to‐market (BM) anomalies for longer‐return intervals using Tokyo Stock Exchange‐listed stocks.

The Fama‐MacBeth cross‐sectional regressions of various models over time‐intervals ranging from one month to one year are performed.

The empirical results show that most macroeconomic variables explain short‐term returns within six months, with the industrial production as the only variable that persistently explains returns of all horizons ranging from one month to one year. Firm size does bear significant risk premium, but its significance diminishes for return‐intervals beyond three months when macroeconomic variables are included in the regression. BM is the only variable that significantly accounts for the cross‐section of stock returns for all horizons, regardless of the inclusion of macroeconomic variables.

These empirical findings suggest that stock returns are determined by both rational factors such as macroeconomic variables and behavioral factors such as BM.

The findings suggest that potential trading strategies indeed can be formed to exploit the persistent predictability, especially the BM regularity.

This paper is the first study that examines the competing explanatory power of various asset‐pricing models over different investment horizons.

The purpose of this paper is to determine if macroeconomic announcements affect the Fama‐French market, size, book‐to‐market risk factors and momentum factor.

Using unexpected announcements of major macroeconomic indicators, a study is made of how daily innovations of risk factors react to macroeconomic shocks. In a Flannery and Protopapadakis framework, the impact of macroeconomics surprises on the levels and volatilities of the risk factors is measured. A VAR model is employed as a robustness check. To better understand the mechanism of announcement impacts on risk factors, the relationship between the macroeconomics announcements and Fama‐French size/book‐to‐market portfolio returns is investigated.

Inflation, employment, consumption and business activities were found to affect levels and volatilities of risk factors. However, these macro variables affect risk factors differently. Inflation and non‐farm payrolls decrease the market risk premium while increasing the size premium. Personal income increases the size premium while reducing the book‐to‐market premium. Industrial production and GDP only influence the level of the momentum factor. In this model specification, producer inflation (PPI) and personal income increase the volatility of the size premium while business inventories increase the volatility of the market premium.

This paper's results support the notion that different risk factors capture different economic fundamentals.

Extant literature suggests that the difficulty associated with the interpretation of macroeconomic news announcements by the market in general in different economic environments, might be the reason why most studies do not find any significant relationship between real-sector macroeconomic variables and financial asset returns. This paper aims to use a different approach to measure macroeconomic news. The objective is to examine if a different measure of a macroeconomic news variable, constructed from media coverage of the same, significantly affects hedge fund returns.

The authors use a news index for unemployment, which is a real-sector variable, constructed from newspaper coverage of unemployment announcements and examine its impact on hedge fund returns.

Contrary to the other studies that examine the impact of macroeconomic news on hedge fund returns, the authors find that media coverage of unemployment news announcements significantly affects hedge fund returns.

Overall, this paper demonstrates that the manner in which the market interprets macroeconomic news announcements in different economic environments is probably a more relevant factor for hedge funds and is more likely to impact hedge fund returns. In conjunction with variables – constructed from media coverage of unemployment news announcements – that factor in the manner of interpretation, it is found that surprises also matter for hedge fund returns. This is an important consideration for hedge fund managers as well.

To the best of the authors’ knowledge, this is the first study that examines the impact of media coverage of macroeconomic news announcements on hedge fund returns and finds significantly different results with real-sector macro variables.

This paper aims to examine the influence of key macroeconomic factors on the inward and outward acquisition activities of six ASEAN (ASEAN: Association of Southeast Asian Nations) countries, namely, Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam, over the 1996-2015 period.

The study uses alternative panel data methods, including pooled mean group, mean group and dynamic fixed-effect estimators.

The results indicate that gross domestic product (GDP), interest rate, exchange rate, money supply and inflation rate are the most important macroeconomic factors explaining the trends of cross-border mergers and acquisition outflows of the ASEAN-6 countries. Specifically, GDP, money supply and inflation rate have significant positive relationships with acquisition outflows, while interest rate and exchange rate exert significant negative influence. On the other hand, the authors find four significant macroeconomic factors explaining the trends of the inward acquisitions. Essentially, GDP, money supply and inflation rate have significant positive impacts on inward acquisitions, while the impact of exchange rate is negatively significant.

Unavailability of data limits this study to pool six sample countries from ASEAN, instead of ten representative member countries.

The results of this study can signal to firms or investors, involving in cross-border mergers and acquisitions, where to direct foreign resources flows. Moreover, having the knowledge about the relative levels of market size and other macroeconomic factors in both home and host countries can be of great importance for investment decision. Therefore, policymakers of ASEAN countries should make appropriate macroeconomic policies that can stimulate inward and outward acquisitions.

The main contribution of this paper is that it is the first to present the analysis of macroeconomic influences on the trends of inward and outward merger and acquisition activities in six ASEAN countries.

This paper aims to examine the relationship between the conditional variance of the factors from the Fama–French three‐factor model and macroeconomic risk, where macroeconomic risk is proxied by the conditional variance for a default risk premium and real gross domestic product (GDP) growth.

A generalised autoregressive conditional heteroscedastic model is used to generate the conditional volatilities and bivariate Granger causality tests are used to examine the empirical relationship between the risk measures.

Past values of the conditional variance for a default risk premium have information that is precedent to the conditional volatility for value premium and the small stock risk premium, and the conditional variance for the market risk premium has information about the future volatility of macroeconomic risk, as proxied by the conditional variance for GDP growth.

The implications are that conditional volatility associated with default is related to current and future volatility in value premium; however, volatility associated with the market risk premium appears to be a predictor of future macroeconomic risk. A caveat is that the results are dependent on the proxies used for macroeconomic risk and more refined measures of macroeconomic risk may yield different results.

This paper suggests that examination of the relationship between the volatility of macroeconomic factors and the explanatory factors in asset‐pricing models will help to further understanding of the relationship between risk and expected return.

This paper focuses directly on the links between risk associated with the Fama–French factors and macroeconomic risk. This added knowledge is beneficial to practitioners and academics whose interest lies in asset price modelling.

Drawing on institutional theory and knowledge spillover, the study aims to examine whether there is a causality relationship between macroeconomic factors and research productivity.

The study uses fixed-effects (FE) panel regression analysis, utilizing 1,614 country–year observations and 541,732 citable publications between 1996 and 2017, to explore the relationship between macroeconomic factors, research and development (R&D) expenditure and research productivity in economics and finance.

The results highlight a two-way relationship between R&D expenditure and economic development and research productivity. However, research productivity has no relationship with foreign direct investment (FDI), trade and financial development. In terms of remaining macroeconomic factors, financial development, trade and FDI have insignificant associations with research productivity in both directions of causality. In line with institutional theory, the findings support the notion that economically more developed countries and countries dedicating greater R&D funds have more potential to support research activities. On the other hand, in line with knowledge spillover, the research output of nations contributes to the economic development and expansion of R&D budgets. The results are robust to alternative methodology, endogeneity concerns, additional control variables, alternative sampling and alternative research productivity proxy.

The study suggests practical implications for nations to formulate macro-policies and a better research environment for academicians and to establish links between academic research and macroeconomic factors.

First, as there is limited research focusing on the bidirectional causality between the macroeconomic environment and academic research activity, the study adds to the understanding of the causality relationship between these two constructs. Second, it examines the bidirectional relationship between macroeconomic factors and research output at a global scale, while prior studies mostly focus on a single country, or a certain region or continent. Further, it is one of the few attempts particularly focusing on economics and finance research's bidirectional relation with the macroeconomic environment.

The purpose of this paper is to investigate the role of macroeconomic factors and the institutional environment on corporate financial flexibility (FF). Most studies focus on well-developed financial markets and very little is known about corporate FF in less developed financial markets and emerging markets (Buvanendra et al., 2016). The present study contributes to filling this gap in the literature and provides a more practical and functional framework to assess the FF of firms located in emerging economies.

The study used annual data for the period from 1991 to 2018. To examine the relationship between macroeconomic indicators, institutional environment and corporate FF, hypotheses were tested using an unbalanced panel logistic regression model.

The paper provides empirical insights into the relationships between macroeconomic factors, institutional environment and corporate FF. The results suggest a substantial change in FF across firms. Inflation, institutional quality and banking sector development negatively affect FF, while equity market development has a significant positive impact. Gross domestic product growth was found to be an insignificant predictor of FF.

This study has practical implications for corporate finance managers, regulators and investors, who must consider the significant factors of this study when making economic decisions. Finance managers can thus make appropriate decisions regarding capital structure and FF. Regulators of the banking sector can take appropriate measures to enhance competition and increase the development of the banking sector. Further, regulators of the equity market can enhance the development of the market to enhance the supply of capital.

This study adds to the literature showing that not only firm-specific factors affect corporate FF, but country-specific macroeconomic and institutional factors also have a significant effect. It also adds to the literature in the area of corporate FF; this field is in its initial stage, even in developed countries, while, in developing countries, little work has been done.

This paper aims to find out significant macroeconomic variables, incorporated as sensitivity variables (macroeconomic sensitivities), affecting financial distress for a sample of listed Indian firms.

The study uses a matched pair sample of defaulting and non-defaulting listed Indian firms. It uses two alternative statistical techniques, viz., logistic regression and multiple discriminant analysis. The macroeconomic sensitivities are estimated by regressing the monthly stock return of the individual firm on the monthly changes in each macroeconomic variable.

Sensitivity to changes in the stock market (stock market sensitivity) and sensitivity to changes in inflation [Consumer Price Index (CPI) sensitivity] have a significant impact on the default probability of a firm. Stock market sensitivity has a significant positive relationship with the probability of default, and CPI sensitivity has a significant negative relationship with the probability of default.

The study links the developments in the external environment to the firm’s susceptibility to default. Furthermore, it highlights the significance of sensitivity of a firm to uncertainties in the macroeconomic environment and its impact on default risk. This establishes the fact that each firm is uniquely affected by the changes in the overall macroeconomic environment. The findings could be valuable to lenders such as banks and financial institutions, investors and policymakers.