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This study explores whether exposure to macroeconomic information provides bellwether firms with information advantages at the macroeconomic level and facilitates managers to utilize such informational advantage for investment decision-making. The author tests whether firms' macroeconomic exposure is associated with sensitivity of their segment-level investments to growth opportunities and how internal and external frictions affect this association cross-sectionally.

This study follows prior research to identify high-macroinformation firms and measures the level of macroexposure based on how closely the firms' underlying business varies with macroeconomic conditions. The main specification is a segment-level regression of investment on growth opportunities and an interaction between growth opportunities and the level of macroeconomic exposure.

The results indicate a significantly positive association between firms' macroeconomic exposure and sensitivity of segment-level investments to growth opportunities, suggesting that bellwether firms can leverage their greater exposure to macroeconomic and external information to improve the quality of their investment decisions. Further evidence shows that this positive association is decreasing in firms' corporate diversification level and is also decreasing in their foreign operation level, implying that internal and external frictions could limit the information benefits ultimately gained by firms from their macroeconomic exposure.

Accounting researchers have recently documented evidence that bellwether firms' management earnings forecasts convey timely information about macroeconomic states, suggesting that managers of certain types of firms are likely to have private macroeconomic information. The main research question in this paper is motivated by incorporating insights derived from recent accounting research findings to shed further light on the impact of firms' macroexposure on their investment decision process.

The purpose of this study is to investigate how changes in the firm's information disclosure practices impact the way investors process macroeconomic news. Specifically, the authors examine the role of derivative instruments and hedging activities disclosure, as required by SFAS 133, in shaping invertors response to good and bad interest rate news. In addition, the authors examine whether the effect of SFAS 133 on investors' response to good and bad interest rate news varies between firms with higher and lower earnings volatility.

This study uses data on all US public firms over the period from 1990 to 2019. The authors mainly apply multivariate regression and a difference-in-difference approach to test their hypotheses.

The results show a significant decrease in the asymmetry of responses to good and bad interest rate news for users of interest rate derivatives following the adoption of SFAS 133. However, in contrast to this finding, the authors also find that the adoption of SFAS 133 has no impact on the asymmetry of responses to good and bad interest rate news for nonusers of interest rate derivatives. Consistent with the ambiguity theory, the finding suggests that SFAS 133 indeed decreases investors’ uncertainty (ambiguity) about the cash flow implications of changes in the interest rate. The authors also find that the decrease in the asymmetry of response to good and bad interest rate news after the adoption of SFAS 133 is greater for users of interest rate derivatives with higher than lower earnings volatility. This implies that derivatives and hedging activities disclosure, as required by SFAS 133, are more important for firms with higher than lower earnings volatility. The finding is consistent with the idea that investors demand more accounting information when underlying earnings volatility is higher. In a set of additional analyses, the authors find that the effect of SFAS 133 on investors' response to good and bad interest rate news varies depending on the level of analyst coverage and interest rate exposure. Specifically, the authors find that the decrease in the asymmetry of response to good and bad interest rate news after the adoption of SFAS 133 is greater for users of interest rate derivatives with higher interest rate exposure and lower analyst coverage.

The findings of this study help market participants including regulators and standard setters to understand the impact of mandatory disclosure practices on investors' reaction to macroeconomic news. Moreover, the findings of the study help managers to understand the influence firm-specific characteristics (e.g. earnings volatility, analyst coverage and interest rates exposure) on the effectiveness of mandatory derivative instruments and hedging activities disclosure.

To the best of the authors' knowledge, this is the first paper to explore how firm-specific information environment affects the way investors process macroeconomic news. This study contributes to the literature by providing the empirical evidence that derivatives instruments and hedging activities, as required by SFAS 133, affect investors' response to good and bad interest rate news. In doing so, the results provide insights about how firm-specific information environment affects the way investors process macroeconomic news. This study shows that the cross-sectional variation in earnings volatility, analysts’ coverage and interest rate exposure affects the impact of SFAS 133 on investors' response to good and bad interest rate news. The findings are not only the notable addition to the existing literature on the topic but also can aid to market participants including policy makers, regulators, standard setters and managers to understand the influence of firm-specific characteristics on the effectiveness of mandatory derivative instruments and hedging activities disclosure. Finally, the findings contribute to the general debate about the effectiveness of SFAS 133 by showing that the adoption of SFAS 133 indeed decreases information ambiguity.

Port throughput analysis is a challenging task, as it consists of intertwined interactions between a variety of cargos and numerous influencing factors. This study aims to propose a quantitative method to facilitate port throughput analysis by identification of important cargos and key macroeconomic variables.

Mutual information is applied to measure the linear and nonlinear correlation among variables. The method gives a unique measure of dependence between two variables by quantifying the amount of information held in one variable through another variable.

This study uses the mutual information to the Port of Isafjordur in Iceland to underpin the port throughput analysis. The results show that marine products are the main export cargo, whereas most imports are fuel oil, industrial materials and marine product. The aggregation of these cargos, handled in the port, meaningfully determines the non-containerized port throughput. The relation between non-containerized export and the national gross domestic product (GDP) is relatively high. However, non-containerized import is mostly related to the world GDP. The non-containerized throughput shows a strong relation to the national GDP. Furthermore, the results reveal that the volume of national export trade is the key influencing macroeconomic variable to the containerized throughput.

Application of the mutual information in port throughput analysis effectively reduces epistemic uncertainty in the identification of important cargos and key influencing macroeconomic variables. Thus, it increases the reliability of the port throughput forecast.

The purpose of the paper is to show that order flows determine exchange rate dynamics because they carry information about nonfundamental factors besides macroeconomic fundamentals.

To understand the role of nonfundamental factors in driving order flows, this study uses two approaches. Initially, Evans and Rime (2016) VAR framework is followed to study the incremental information transmitted by order flow compared to macroeconomic variables. Then, the study uses the settings in which Rime et al. (2010) conduct their empirical work, which gives the researcher more latitude in specifying the identity of the factors that drive order flows.

The findings evidence that order flows explain the dynamics of the TND/USD exchange rate. The results highlight that order flows convey information about technical strategies, the currency systematic factors and political risk. This study also documents the presence of a Ramadan effect in exchange rates and order flows.

This study makes four contributions to the literature. First, it complements the literature on the FX microstructure of emerging markets. The study investigates the information content carried by order flows, while the previous literature has focused solely on examining the explanatory power of order flows to explain exchange rates in emerging countries. The second contribution is that the study demonstrates formally that order flows determine exchange rates because they transmit information about nonfundamental factors. Third, this study is the first to examine whether order flows convey information about technical analysis. Four, the study relates order flow to nontraditional factors that are relevant to the Tunisian FX market.

What information do members of Congress (politicians) use when they trade stocks? The purpose of this paper is to attempt to answer this question by investigating the relationship between an aggregate measure of trading by members of Congress (aggregate congressional trading) and future stock market returns.

The authors follow the empirical framework used in academic work on corporate insiders. In particular, they aggregate 61,998 common stock transactions by politicians over the 2004–2010 period and estimate time series regressions at a monthly frequency with heteroskedasticity and autocorrelation robust t-statistics.

The authors find that aggregate congressional trading predicts future stock market returns, suggesting that politicians use economy-wide (i.e. macroeconomic) information in their stock trades. The authors also present evidence that aggregate congressional trading is related to the growth rate of industrial production, suggesting that industrial production serves as a potential channel through which aggregate congressional trading predicts future stock market returns.

To the best of the authors’ knowledge, this study is the first to document a relationship between aggregate congressional trading and stock market returns. The media and scholarly attention on politicians’ trades have mostly focused on the question of whether politicians have superior information on individual firms. The results from this study suggest that politicians’ informational advantage may go beyond individual firms such that they potentially have superior information on the overall trajectory of the economy as well.

The purpose of this study is to analyze the predictability of firm level data for determining macroeconomic indicators such as unemployment.

This study uses quarterly GDP and unemployment data manually collected from the Statistical Center of Iran (SCI). Accounting numbers are also collected from the Tehran Stock Exchange library for the 2004-2015 period. Dispersion of earnings growth provides related data about labour reallocation, unemployment change and finally aggregate output. To summarize, this study attempts to examine the effect of these variables using classical and Bayesian approaches.

At a firm level, our results suggest that sectoral shift in previous years is likely to increase labour reallocation in subsequent years. At the macro level, the results reveal that dispersion of earnings growth and labour reallocation has a negative and positive impact on unemployment changes, respectively. However, the study suggests no significant relationship between stock return and unemployment changes. Consequently, we determine that the real estimates of macroeconomic indicators have predictive power because nominal estimates are not statistically associated with firm-level details. Finally, the results obtained from classical and Bayesian approaches suggest similar findings, thus confirming the robustness of our conclusions. Note that, based on Bayesian approach, the nominal reallocation has predictive power in unemployment rate.

The study is the first conducted in a developing country and the results provide important insight into current line of accounting literature.

This paper aims to study the connection between the systematic equity risk of US tourism industry companies and a set of information from inside these firms and the market. The authors sought to identify which information explains equity risk to estimate patterns of behavior – especially for those companies that cannot have a beta – in terms of the cost of share capital.

To carry out the research, the authors used a panel data technique and combined accounting information from the selected companies with macroeconomic information to develop independent variables. The sample consisted of 79 firms of the arts, entertainment and recreation and accommodation and food services sectors in the USA for 2004-2013. The authors incorporated two dummy variables into the analyses. The first one was used to find out if a difference exists between the two sectors, and the other was used to examine differences before and after 2008, when the current economic and financial crisis began.

The results reveal that equity risk is explained by businesses’ size and growth, along with three indicators of business efficiency, consumer price and Stoxx Europe 50 indices. The 2008 financial crisis did not alter the behavior of the estimated model, and no difference was found between the two sectors in question.

The study’s most important limitation is the number of companies and years that make up the sample, although a broader set of data was analyzed in this work compared to previous studies.

The research results are quite useful to tourism enterprise management in the US market as they provide information that explains companies’ equity risk. Knowing this information could facilitate more efficient management, and an understanding of which information determines company risk can help to quantify risk objectively without access to betas.

The authors studied the US market as an important financial market and the tourist industry, in particular, for its economic significance, as shown by the direct contribution of travel and tourism to the US gross domestic product. Although this type of research in the tourism sector is not new, the present study answers the need identified by Park and Jang (2014) to continue this line of research by using a more interdisciplinary approach that combines hospitality research with finance and/or accounting studies.

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.

The study examines the effect of macroeconomic risk, inflation uncertainty and instability associated with key macroeconomic indicators on the efficiency of financial institutions among economies in sub-Saharan Africa (SSA).

Data for the empirical inquiry were compiled from 35 SSA economies from 1996 to 2019. The empirical estimates were carried out using pooled ordinary least squares (POLS) with Driscoll and Kraay’s (1998) standard errors.

Reported empirical estimates show that macroeconomic risk and exchange rate volatility constrain the efficiency of financial institutions. Further results suggest that inflation uncertainty has a significant influence on the efficiency of financial institutions among economies in the subregion. Additionally, reviewed empirical estimates show that institutional quality positively moderates the nexus between inflation uncertainty and financial institution efficiency. At the same time, political instability is found to worsen the adverse effect of macroeconomic risk on the efficiency of financial institutions.

For policymakers and governments, improved institutional structures are recommended to ensure the operational efficiency of financial institutions, especially during an inflationary period. For decision-makers among financial institutions, the study recommends policies that have the potential to make their institutions less vulnerable to macroeconomic risk and exchange rate fluctuations.

The approach adopted in this study differs significantly from related studies in that the study examines and reviews interactions and relationships not readily found in the reviewed literature.

The purpose of this paper is to investigate who trade actively in the Malaysian stock market and what determines investors’ active trading decisions.

Using a cross-sectional survey on individual investors, the study identifies active and inactive investors and then, investigates active trading by estimating binary logistic regression.

Active investors in Malaysia are more likely to be male, working in non-finance-related sectors and are more experienced. The likelihood of active trading increases with the number of hours spent on researching investment, very short-term favorable unemployment and economic growth expectations (three-month) and past investment outcomes, whereas this probability decreases with higher cognitive ability and short-term unemployment expectations.

The results imply that regulators may focus on certain groups of investors, based on the result of this study, and provide them training to reduce inactivity in this market. As active trading in response to past investment outcomes indicate rational response, regulators therefore may inform investors to learn about their ability and skill from their prior investment outcome, through educational program. Educational program may also include the role of macroeconomic indicators in active investing decisions.

This is the first study to combine a list of demographic and socio-economic characteristics, investment characteristics, macroeconomic expectations and past investment outcomes together to explain the likelihood of active trading.