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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 whether Fama–French common risk-factor portfolio investors herd on a daily basis for five developed markets, namely, Europe, Japan, Asia Pacific ex Japan, North America and Globe.

To examine the herd behavior of common risk-factor portfolio investors, this paper utilizes the cross-sectional absolute deviations (CSAD) methodology, covering a daily data sampling period of July 1990 to January 2019 from Kenneth R. French-Data Library. CSAD driven by fundamental and non-fundamental information is assessed using Fama–French five-factor model.

The results do not provide evidence for herding under normal market conditions, either when reacting to fundamental information or non-fundamental information, for any region under consideration. However, Fama–French common risk-factor portfolio investors mimic the underlying risk factors in returns related to size and book-to-market value, size and operating profitability, size and investment and size and momentum of the equity stocks in European and Japanese markets during crisis period. Also, no considerable evidence is found for herding (on fundamental information) under crisis and up-market conditions except for Japan. Ancillary findings are discussed under conclusion.

Further research on new risk factors explaining stock return variation may help improve the model performance. The performance can be improved by adding new risk factors that are free from behavioral bias but significant in explaining common stock return variation. Also, it is necessary to revisit the existing common risk factors in order to understand behavioral aspects that may affect cost of capital calculations (e.g. pricing errors) and valuation of investment portfolios.

This is the first paper that examines the herd behavior (fundamental and non-fundamental) of Fama–French common risk-factor investors using five-factor model.

This study aims to fill the research gap regarding the usability of group reporting information in the central government. It answers the question of how the consolidated information should be formed to benefit the real needs of governmental information users.

The empirical research is based on a survey and interviews among key internal preparers and users in the central government sector in the case country, Finland.

Results show that the private sector approach regarding consolidation is not appropriately transferable to the central government sector. The key stakeholders identified several economic and financial reporting needs that exceed what formal Consolidated Financial Statement (CFS) can offer. Consolidation is needed but not according to the extensive full control approach, but rather following the budgetary approach consolidating units of the legal person of the government, and further using the partial control approach for consolidating by discretion essential special purpose SOEs.

Respondents and interviewees represented governmental internal organisations, free experts, auditors and financial managers from the group entities. Politicians and citizens were not directly represented.

Research gives applicable insights into central governments planning and developing group reporting for information needs in a favourable cost-benefit ratio. Findings benefit the development of EU's EPSAS (European Public Sector Accounting Standards) project which is still incomplete.

Research recommends governments to make a thorough analysis before deciding on a new financial reporting system. A critical analysis prevents governments to waste money and resources on a reporting system not fulfilling the real needs of information users.

The value of this research is that the private sector approach in consolidation was not taken as granted. This study investigated critically and empirically the real need for consolidated information serving steering and overseeing purposes of the government's group entities.

This study examines the long term effects of macroeconomic fundamentals on apartment price dynamics in major metropolitan areas in Sweden and Germany.

The main approach is panel cointegration analysis that allows to overcome certain data restrictions such as spatial heterogeneity, cross-sectional dependence, and non-stationary, but cointegrated data. The Swedish dataset includes three cities over a period of 23 years, while the German dataset includes seven cities for 29 years. Analysis of apartment price dynamics include population, disposable income, mortgage interest rate, and apartment stock as underlying macroeconomic variables in the model.

The empirical results indicate that apartment prices react more strongly on changes in fundamental factors in major Swedish cities than in German ones despite quite similar development of these macroeconomic variables in the long run in both countries. On one hand, overreactions in apartment price dynamics might be considered as the evidence of the price bubble building in Sweden. On the other hand, these two countries differ in institutional arrangements of the housing markets, and these differences might contribute to the size of apartment price elasticities from changes in fundamentals. These arrangements include various banking sector policies, such as mortgage financing and valuation approaches, as well as different government regulations of the housing market as, for example, rent control.

In distinction to the previous studies carried out on Swedish and German data for single-family houses, this study focuses on the apartment segment of the market and examines apartment price elasticities from a long term perspective. In addition, the results from this study highlight the differences between the two countries at the city level in an integrated long run equilibrium framework.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

Homeownership provides shelter and is a vital component of wealth, and house purchase signifies a lifetime achievement for many households. For South Africa confronted with social and structural challenges, homeownership by the low and lower middle-income household is pivotal for its structural transformation process. In spite of these potential benefits, research on the affordable housing market in the context of South Africa is limited. This study aims to contribute to this knowledge gap by answering the question “do changes in household income per capita have a symmetric or asymmetric effect on affordable house prices?”

A survey of the international literature on house prices and income revealed that linear modelling that assumes symmetric reaction of macroeconomic variables dominates the empirical strategy. This linearity assumption is restrictive and fails to capture possible asymmetric dynamics inherent in the housing market. The authors address this empirical limitation by using asymmetric non-linear autoregressive distributed lag models that can test and detect the existence of asymmetry in both the long and short run using data from 1985Q1 to 2016Q3.

The results revealed the presence of an asymmetric long-run relationship between affordable house prices and household income per capita. The estimated asymmetric long-run coefficients of logIncome[+] and logIncome[−] are 1.080 and −4.354, respectively, implying that a 1% increase/decrease in household income per capita induces a 1.08% rise/4.35% decline in affordable house prices everything being equal. The positive increase in affordable house prices creates wealth, helps low and middle-income household climb the property ladder and can reduce inequality, which provides support for the country’s structural transformation process. Conversely, a decline in affordable house prices tends to reduce wealth and widen inequality.

This paper recommends both supply- and demand-side policies to support affordable housing development. Supply-side stimulants should include incentives to attract developers to affordable markets such as municipal serviced land and tax credit. Demand-side policy should focus on asset-based welfare policy; for example, the current Finance Linked Income Subsidy Programme (FLISP). Efficient management and coordination of the FLISP are essential to enhance the affordability of first-time buyers. Given the enormous size of the affordable property market, the practice of mortgage securitization by financial institutions should be monitored, as a persistent decline in income can trigger a systemic risk to the economy.

The study results illustrate the importance of homeownership by low- and middle-income households and that the development of the affordable market segment can boost wealth creation and reduce residential segregation. This, in turn, provides support to the country’s structural transformation process.

The affordable housing market in South Africa is of strategic importance to the economy, accounting for 71.4% of all residential properties. Homeownership by low and lower middle-income households creates wealth, reduces wealth inequality and improves revenue collection for local governments. This paper contributes to the empirical literature by modelling the asymmetric behaviour of affordable house prices to changes in household income per capita and other macroeconomic fundamentals. Based on available evidence, this is the first attempt to examine the dynamic asymmetry between affordable house prices and household income per capita in South Africa.

A controversy about whether liberalization through market opening is a necessary and sufficient condition for a stable and balanced growth in the developing countries was retriggered by the 2008 global financial crisis. This paper aims to analyze 1) the impact of market openness on the economic growth and financial development, 2) the dynamic correlation between the compositional change in foreign investments and the returns of domestic financial markets, 3) the effect of foreign portfolio investment on the stock market activity (liquidity and profitability). Our empirical findings infer that the income level has a positive relationship with financial openness and the foreign portfolio investments cause price fluctuations in the domestic stock market. These results imply that the precautionary and effective policies such as prudential regulations on the short-term capital transactions are strongly needed to emerging markets in order to prevent the excessive fluctuations in the financial markets over the macroeconomic fundamentals.

Despite being a viable source of funds, African sovereign bond markets are relatively underexplored. The empirical literature fails to consider the impact of exclusively macroeconomic factors and the volatile contexts in which African markets operate. The purpose of this paper is to fill the vacuum by proposing a context-sensitive theoretical framework. The study targets, specifically, macroeconomic factors and assesses the extent to which they affect bond market development.

Using panel data on sovereign bond markets from 26 African economies, the study extends previous methodologies used in similar studies by accounting for downside risk in a generalized method of moments (GMM) framework and employing tighter robustness measures.

This study finds that inflation, domestic debt, external debt, GDP at PPP, fiscal balance and exports are important macroeconomic drivers of sovereign bond market development in African emerging economies.

While GMM estimation is beneficial in the presence of endogeneity between the dependent variables that are instrumented with lagged independent variables, it guarantees consistency but, not unbiased estimations.

Market-oriented government funding with well-defined debt management strategies must be implemented to support the development of sovereign bond markets. External debt must be set at a sustainable level, and government should be dedicated to the confirmation of this. Furthermore, inflation rates must be kept low and stable.

If policymakers are to take this study seriously, bond markets may begin to be viable sources of funds for African emerging economies.

This study introduces a methodology for measuring bond market development that considers the systemic volatility in emerging markets and proposes a theoretical framework for African emerging economies. In addition, the authors identify a new macroeconomic determinant of bond market development in the region.

This paper aims to apply the debt sustainability framework using various ratios to review the current state of sovereign debt of Economic Community of West African States (ECOWAS) member countries.

Debt sustainability framework using various ratios (which include the present value approach, Country Policy and Institutional Assessment debt policy assessment ranking and solvency ratio of external debt) for the period 2010 and 2017 were used for the analysis to determine external debt sustainability and solvency of ECOWAS members.

The findings indicate that most ECOWAS countries are already turning at the unsustainable debt path and may renege in their debt obligations, thus creating a vicious cycle of external borrowing that could lead to capital flight.

This paper offers the empirical evidence to identify which of the ECOWAS countries are already at the threshold of external debt stress, and in the likelihood to renege on their debt obligations.