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This study aims to explore the asymmetric effects of macroeconomic factors on the profitability of large-cap companies in an emerging country like Colombia, using the Morgan Stanley Capital International (MSCI) Colombia index as the basis.

We employ a combination of singular spectrum analysis (SSA) and principal component analysis (PCA) to identify and estimate four key macroeconomic factors that account for approximately 47.8% of Colombia's macroeconomy. These factors encompass indicators related to inflation and cost of living, foreign trade and exchange rate, employment and labor force and trade and production in Colombia. We utilize the distributed lag nonlinear model (DLNM) to analyze the asymmetric relationships between these factors and corporate profitability, considering different scenarios and lags.

Our analysis reveals that there are indeed asymmetric relationships between the identified macroeconomic factors and corporate profitability. These relationships exhibit variability over time and lags, indicating the nuanced nature of their impact on corporate performance.

This study contributes to the existing literature by applying a novel methodology that combines SSA and PCA to identify macroeconomic factors within the Colombian context. Additionally, our focus on asymmetric relationships and their dynamic nature in relation to corporate profitability, using DLNM, adds original insights to the research on this subject.

The study examines the impact of macroeconomic risk and volatility associated with key macroeconomic indicators on financial market uncertainty; and the extent to which governance and institutional structures moderate such relationships.

The study employs data from 33 countries in Sub-Saharan Africa (SSA) for the period between 1996 and 2019. Variable derivation techniques such as the generalized autoregressive conditional heteroskedasticity (GARCH) for deriving volatility data, and the principal component analysis (PCA) for index construction were employed. The data is examined using the two-step system generalized method of moments (TS-SGMM) technique.

Empirical results suggest that macroeconomic risk and exchange rate volatility heighten financial market uncertainty among economies in the sub-region. Further empirical estimates show that institutional quality and government effectiveness have a negative moderating effect on the nexus between macroeconomic risk, inflation uncertainty, GDP growth, exchange rate, and financial market uncertainty.

The key macroeconomic conditions with the propensity to foment financial market uncertainty are worth monitoring with adequate buffers to mitigate their impacts on the financial market.

Compared to related studies, this study focuses on uncertainty associated with financial markets among emerging economies in sub-Saharan Africa (SSA) instead of the performance of the financial markets or specific financial market indicators such as the stock market; and the extent to which a host of macroeconomic conditions influence such uncertainty. For instance, Abaidoo and Agyapong (2023) focused on the impact of macroeconomic indicators or conditions on the performance of the financial market and the efficiency of financial institutions respectively instead of the uncertainty or risk associated with the financial market as pursued in the current study. This differing approach is pursued with the goal of proffering appropriate strategies for policy makers towards assuaging the financial market risk (uncertainty) due to macroeconomic dynamics. We further examine how the various fundamental relationships may be moderated by effective governance and institutional quality.

This study seeks to examine the extent to which strands of inflationary related conditions (inflation expectations, inflation uncertainty and realized inflation); macroeconomic uncertainty and the likelihood of recessionary conditions influence performance indicators in the US banking sector over a specified time period.

The study adopts seemingly unrelated regression model (SUR) advanced by Zellner (1962) in its examination of how specific strands of inflationary conditions, and other adverse macroeconomic conditions influence performance dynamics in the US banking sector.

Empirical evidence suggest that among various adverse macroeconomic conditions examined, inflation expectations and macroeconomic uncertainty tend to have significant constraining impact on key performance indicators in the US banking sector than other conditions examined. Comparatively, this study finds that inflation expectations and macroeconomic uncertainty tend to have much more constraining impact on return on equity, than on return on assets in the US banking sector. Results further suggest that among the three bank performance indicators examined, net interest margin is the least vulnerable bank performance indicator to various adverse macroeconomic conditions examined in the study.

Apart from the various empirical results noted above, this study's findings are projected to help inform strategic planning decisions among institutions in the banking sector. The various findings could, for instance, inform policies and operational strategies geared toward reducing vulnerability associated with specific performance indicators such as return on equity. This reduction could be achieved by critically examining how the various performance indicators react to individual adverse macroeconomic conditions examined in this study. The process could ultimately help in developing tailored measures/procedures aimed at reducing how susceptible key performance indicators are to the various adverse macroeconomic conditions. This study's findings could also provide the platform for more adaptive policies aimed at minimizing the effects of noted macroeconomic conditions on operational efficiency in the banking sector.

The uniqueness of this study, compared to related ones found in the literature, stems from its treatment of three variant of related strands of macroeconomic condition (different variant of inflationary conditions) in the same framework in its empirical analysis.

本研究旨在探討與通貨膨脹有關的狀況的組成部分(通脹預期 、通脹不確定性及體現了的通脹), 宏觀經濟不確定性及經濟衰退狀況的可能性、在一段特定時間內對美國銀行業的表現指數有何種程度的影響。

研究採用塞爾納 (Zellner) (1962) 提出的看似無關迴歸模型 (SUR)，去探討通脹狀況的特定組成部分及其它不利的宏觀經濟狀況如何影響美國銀行業內的績效動態。

實證證據暗示在被研究的各個不利宏觀經濟狀況中，通脹預期及宏觀經濟不確定性，對美國銀行業內的主要業績指標的約束影響, 與其它被探討的狀況相比，往往會較重大。相對地、本研究結果顯示通脹預期及宏觀經濟不確定性，對美國銀行業資本回報率的約束影響、往往遠多於資產收益率。研究結果進一步顯示，在被探討的三個銀行業績指標中，就本研究所探討的各個不利的宏觀經濟狀況而言，淨息差是脆弱性最小的銀行業績指標。

除了上述各實證結果外，本研究結果預期會給銀行業內機構間作戰略規劃的決定時提供資料，譬如，各項研究結果或可在制定旨在減少與特定業績指標如資本回報率相聯繫的脆弱性的政策和經營策略時提供資料。這脆弱性的減少，是透過嚴謹地研究各個業績指標，如何對在本研究中被探討的個別不利宏觀經濟狀況作出反應而達致的。這程序或許最終會幫助建立一個以減少各個不利宏觀經濟狀況對主要業績指標的影響為目的的量身定制措施／程序。本研究的結果，或許亦可為更多旨在減弱眾所周知的宏觀經濟狀況對銀行業運營效率的影響的適應性政策提供平台。

與文獻中可見的相關研究比較，本研究的獨特性源於其實證分析，是涉及在同一個構架內處理宏觀經濟狀況相互有關的組成部分的三個變體 (通脹狀況的不同變體) 。

The purpose of the paper is to examine macroeconomic and institutional factors that influence capital flows to low-income sub-Saharan African (SSAn) countries. It analyzes capital flows in a disaggregated manner: foreign divert investment, portfolio equity and portfolio debt. There is a gap in the empirical literature in examining the factors that are important for various types of capital flows to low-income SSAn countries. Low-income SSAn countries attract very low levels of foreign investment compared to other developing economies in the SSAn region and other developing economies and this paper attempts to make a contribution in this area.

This paper examines data on capital flows and that of various push and pull factors. Trends and dynamics of capital inflows and their macroeconomic and institutional drivers are analyzed for low-income sub-Saharan African countries. Such an analysis has not been fully explored for low-income SSAn countries.

Capital inflows to low-income sub-Saharan Africa (SSA) have increased sevenfold since the 1990s, dominated by foreign direct investment (FDI). They overtook official development assistance and aid in the 2010s. Mozambique and Ethiopia attract the largest size of FDI compared to other low-income SSAn economies, with natural resources as key factors in the former. The largest share of FDI to low-income SSAn countries comes from other SSAn countries, mostly South Africa and Mauritius. Among macroeconomic push factors, capital inflows are more closely related to commodity prices, while the volatility index and global liquidity are also important. Among macroeconomic pull factors, trade openness and economic growth appear more closely related to capital inflows. The surge in capital inflows in the 2000s also followed the implementation of several regional trade and investment agreements in the region. The improvement in internal conflict in the 1990s and mid-2000s seems to have helped support the increase in capital inflows during that period. This institutional quality variable appears to more closely track capital inflows compared to other institutional quality indicators. There were also improvements in the investment profile, law and order, and government stability in the 1990s to early 2000s when capital inflows picked up.

This study focuses on low-income SSAn countries, which are less studied in the empirical literature and that face immense developmental needs that require foreign and domestic capital.

Findings of this paper can shed light to policy makers on the factors that are most important to help the region attract capital inflows and areas where further improvement is needed in the macroeconomic and institutional environment.

There is a gap in the empirical literature in examining the factors that are important for attracting capital flows to low-income SSAn countries. To our knowledge, this study may be the first to explore dynamics of capital flows against institional quality for low-income SSAn countries at a disaggregated level.

The purpose of this paper is to examine key macroeconomic determinants on Cameroon's economic growth from 1970 to 2018.

Data were obtained from the World Development Indicators and applied on time series data econometric techniques. The auto-regressive distributed lag (ARDL) bounds model analyzed the data since the variables had different order of integration.

The results showed long and short runs’ positive and significant connection between economic growth in Cameroon and government expenditure; trade openness, gross capital formation and exchange rate. Human capital development, foreign aid, money supply, inflation and foreign direct investment negatively and significantly affected economic growth in the short and long-runs. Hence, the macroeconomic indicators are not death.

The present research paper has tried to capture the impact of nine macroeconomic determinants on economic growth such as the government expenditure (LNGOVEXP), human capital development (LNHCD), foreign aids (AID), trade openness (LNTOP), foreign direct investment (LNFDI), gross capital formation (INVEST), broad money (LNM2), official exchange rate (LNEXHRATE) and Inflation (LNINFLA). However, these variables have the tendency to affect each other in a unidirectional or bidirectional manner. Further, the present research paper is unable to capture the impact of other macroeconomic variable due to the unavailability of data.

The study recommends that Cameroon should use proper planning and strategic policy interventions to achieve higher sustainable economic growth with human capital development, foreign aid, money supply, foreign direct investment and moderate inflation.

Macroeconomic indicators, if managed well, increase economic growth.

This paper to the best of the researcher's knowledge presents new background information to both policymakers and researchers on the main macroeconomic determinants using econometric analysis.

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 aims to investigate the impact of global macro and other risk factors of the New York Stock Exchange (NYSE)- and National Association of Securities Dealers Automated Quotation (NASDAQ)-listed shipping companies’ stock returns from January 2001 to December 2019.

The methodological design includes multi-factor regressions for individual companies, augmented versions of these regressions to examine the likely impact of additional factors and finally panel regressions to assess the impact risk factors on all companies simultaneously. Estimations are done via ordinary least squares and the generalized method of moments.

Multi-factor model results showed that some of the US-specific and global macro risk factors surfaced as statistically significant for most of the companies and appeared to exhibit a consistent pattern in the way they affected shipping stocks. Thus, these companies’ exposures emanate mostly from the general US market’s movements and to a lesser extent from other firm-specific factors. Second, from the results of panel specifications, this study observes that domestic risk factors such as unemployment, inflation rates and industrial production growth emerged as significant for the NYSE-listed companies. As regard, the NASDAQ-listed ones, it was found that Libor and the G20 inflation rate were also affecting their stock returns.

Companies examined are listed only in the US’s NYSE and NASDAQ. Hence, companies listed elsewhere were excluded. It may be concluded that these US exchange-listed companies abide mostly by domestic fundamentals and to some extent to selected global factors.

The significance of the findings in this study pertains to global investors and shipping companies’ managers alike. Specifically, given the differential sensitivities of the shipping companies to various risk factors (and the global business cycle, in general), it is possible to view the shipping companies’ stocks as a separate, alternate asset class in a global, well-diversified portfolio. Thus, such a broader portfolio would permit investors to earn positive returns and reduce overall risk. Managers of shipping companies would also benefit from the findings in this study in the sense that they should better understand the varying exposures of their companies to changing global and domestic macro conditions and successfully navigate their companies through business cycles.

Research on the global shipping industry has lagged behind and was mainly concentrated on the investigation of the sources of shipping finance and capital structure of shipping companies, investment and valuation, corporate governance and risk measurement and management. Empirical research on the potential micro and macro determinants of the stock returns of shipping companies, however, is scant. This paper fills the gap in the literature of identifying and evaluating the various macroeconomic, US and international risk, factors that affect shipping companies’ stock returns in a highly financially integrated world.

The economic and financial literature dealing with the subject of bank profitability has often been based in the measurement of banking results on three main indicators: ROA, ROE and MIN. This article aims to determine and analyze the different determinants that influence bank profitability and to identify the impact of these determinants on the profitability of Moroccan banks.

For this purpose, a fixed individual effect model was adopted for the case of six Moroccan banks during the period of study from 1997 to 2018. The authors carried out their estimates at three levels according to three categories of profitability factors: bank factors, factors of the banking system and macroeconomic factors.

The empirical findings show that Moroccan banks react on their size to boost their performance, which further explains the continued expansion of Moroccan banking networks. The authors confirm that Moroccan banks have not yet reached a level of size that will be detrimental to their performance. Therefore, the authors can conclude that the big Moroccan banks do not follow the concept of economy of scale. The effects of the variation in the level of economic growth as well as the evolution of the level of inflation on the performance of Moroccan banks are not significant.

The authors’ findings and results have some important originality and value. Primarily, these results would consist of better helping the State, bankers, and bank managers to better understand the various determinants of bank profitability. The results may also help to better examine the effect of each factor, whether internal or external, on banks' bottom line.

Fama–French model (FFM) has been successful in helping to predict the financial markets, but investors have been interested in creating more sophisticated models to better predict the performance of the stock market. The objective of the extended version is to create a more robust econometric model to better predict the performance of the Mexican Stock Market.

The study divides the Mexican Stock Market into six different portfolios. The criteria to build those portfolios are the same one used in Fama–French (1992). The study comprises 78 stocks listed in the Mexican Stock Market that are analyzed monthly during 1997–2018. The study analyzes the period before and after the 2008–2009 financial crisis to identify whether there are important changes. The estimation applies the traditional and an extended version of the FFM that include macroeconomic variables such as country risk, economic activity, inflation rate, and exchange rate and some financial variables recommended in the literature.

Results indicate that classic FFM variables are statistically significant in most cases, but relevant macroeconomic variables such as the interest rate, exchange rate and country risk stand out for being weakly relevant in most of the portfolios. However, it is noticed that some of these macroeconomic variables became relevant for different portfolios only after the 2008–2009 crisis, especially in portfolios which include small market capitalization firms.

The study includes the stocks listed in the Mexican Stock Market. One limitation is the small number of stocks available, which reduces the possibility of creating well diversified portfolios. This study includes 78 stocks. The stocks removed from the sample are from firms that were not listed during six consecutive months or whose market capitalization did not change in the same period. Outlier data were removed from the sample to capture in better way the general performance of the stock market.

The objective of the extended version is to create a more robust econometric model than the traditional model. It is expected that such estimations can be helpful to investors to make better decisions when they try to predict performance in the stock market.

An extended version of the FFM can be helpful to investors to make better decisions when they try to predict performance in the stock market.

To the best of our knowledge there are no more studies in the literature of the Mexican financial market that apply the same methodology.

The purpose of this paper is to examine the determinants of mutual funds’ performance at both a country level and a fund level in Vietnam.

The different types of funds with more than three-year operation are selected to remove outliers of the stock market boom from 2015 to 2018. The data set includes 54 mutual funds operating during the period from 2008 until November 2018.

The research finds that there is a positive relationship between macroeconomics and mutual funds’ performance. Furthermore, country-level governance such as regulation effectiveness, political stability, economic growth and financial development has a positive correlation with mutual funds’ performance. However, the impact of fund-level factors is diverse with the no significant impact of board size on mutual fund’s performance, while passive funds perform better than active funds in Vietnam.

The research results suggest that investors should pay attention to the types of funds and operating expense when making an investment decision in mutual funds. There are some recommendations for both government policy-makers and the mutual fund industry that are likely to facilitate the development of this field in Vietnam.

The research contributes to the understanding of what are the factors that should be considered when investing in mutual funds.