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The innovations in fundamentals coupled with noise traders induce co-movement in diverse markets. This co-movement in equity markets which is evidenced higher during the turmoil period influences economic fundamentals of a country dissimilar in nature. The purpose of this paper is to examine whether economic fundamentals or investors’ behavior attributable to disturbances across the world are the rationale behind the crisis transmission, and thereby distinguish fundamental-based contagion from investor-induced contagion.

Initially, the study investigates the role of macroeconomic fundamentals and stock returns on crisis occurrence using panel probit estimates. Additionally, ordinary least squares estimates controlling the influence of fundamentals on domestic return capture the discrete country effect measuring the influence of domestic as well as foreign economic fundamentals along with foreign returns on the domestic stock index.

The empirical results reveal that foreign country stock index returns are having a significant influence on domestic returns besides a prominent role in crisis occurrence. The binary probit model confirmed the influence of both macroeconomic factors and foreign returns in crisis occurrence. The OLS estimates found evidence for investor-induced contagion in the crisis period where the effects of economic fundamentals are small in comparison to foreign market returns that are mainly dominant in pre- and post-crisis period.

The propagation of crisis from one market to other would enable the policy makers to make clear regulations at right time to control for the crisis in future. The results can help the policy makers as well as investors in reducing the impact of the crisis in future by clearly monitoring the behavior of the factors under study.

The current study addresses the role of macro fundamentals and investors influence in crisis propagation. Adopting subprime crisis of 2008-2009 as a reference point and separating the sample period into pre-crisis, crisis and post-crisis period, the study explains how badly the other 30 markets impacted the crisis that emerged in the USA.

The equity premium of the S&P 500 index is explained in this paper by several variables that can be grouped into fundamental, behavioral, and macroeconomic factors. We hypothesize that the statistical significance of these variables changes across economic regimes. The three regimes we consider are the low‐volatility, medium‐volatility, and high‐volatility regimes in contrast to previous studies that do not differentiate across economic regimes. By using the three‐state Markov switching regime econometric methodology, we confirm that the statistical significance of the independent variables representing fundamentals, macroeconomic conditions, and a behavioral variable changes across economic regimes. Our findings offer an improved understanding of what moves the equity premium across economic regimes than what we can learn from single‐equation estimation. Our results also confirm the significance of momentum as a behavioral variable across all economic regimes

This paper aims to provide an empirical analysis of the macroeconomic determinants of sovereign bond yield spreads in the Eurozone from 2000 until August 2012, when the Outright Monetary Transactions programme was launched.

The authors constructed an unbalanced panel with quarterly data from 2000 Q1 to 2012 Q2 for the 12 Eurozone countries: Austria, Belgium, Finland, France, Germany, Greece, Ireland, Luxembourg, Italy, The Netherlands, Portugal and Spain. The authors propose a model that explains spreads through the main categories of variables observed in the literature. The relationship between variables is analysed using ordinary least squares and quantile regressions. As discussed by the authors, quantile regressions provide a more precise estimation, given the huge heterogeneity across counties that can be observed in the Eurozone.

Results show that the relationship between sovereign risk and macroeconomic fundamentals is affected by a strong country sentiment effect. The impact of country sentiment on sovereign risk is larger for those countries that were already experiencing higher spreads. Regardless the impact that European Central Bank’s (ECB) intervention had on sovereign risk from 2012, quantile regression results suggest that policy recommendations and goals should be adapted to each country’s market perception.

The results obtained improve on previous findings on this topic (De Grauwe and Ji, 2012) in two ways. First, they show that even introducing every category of determinants found in the literature in the main specification, fundamentals can only partially explain the evolution of sovereign risk in the Eurozone. Second, they find there is a country-sentiment effect that affects the relationship between macroeconomic indicators and sovereign risk. Furthermore, the paper finds that the country-sentiment effect is larger for countries facing high spreads.

Housing prices in Sydney have increased rapidly in the past three decades. This leads to a debate of whether Sydney housing prices have departed from macroeconomic fundamentals. However, little research has been devoted to this area. Therefore, this study aims to fill this gap by examining the long-run association between housing prices and market fundamentals. Further, it also examines the long-run determinants of housing prices in Greater Sydney.

The analysis of this study involves two stages. The first stage is to estimate the presence of long-run relationship between housing prices and market fundamentals with the Johansen and Juselius Cointegration test. Thereafter, the determinants of housing prices in Greater Sydney is assessed by using a vector error correction model.

The empirical results show that Sydney housing prices are cointegrated with market fundamentals in the long run. In addition, there is evidence to suggest that market fundamentals such as gross disposable income, housing supply, unemployment rate and gross domestic product are the key long-run determinants of Sydney housing prices, reflecting that Sydney housing prices, in general, can be explained by market fundamentals in the long run.

The findings enable more informed and practical policy and investment decision-making regarding the relation between housing prices and market fundamentals.

This paper is the first study to offer empirical evidence of the degree to which the behaviour of housing prices can be explained by market fundamentals, from a capital city instead of at a national level, using a relatively disaggregated dataset of housing price series for Greater Sydney.

The purpose of this paper is to examine the impact of industry structure and macroeconomic indicators on return on equity (ROE) of listed financial services firms.

Herfindahl–Hirschman Index concentration scales were used to categorise industries into competitive, moderate and concentrated segments, while Arbitrage Pricing Model principles were used to capture the effect of macroeconomic fundamentals on ROE. Generalised method of moments estimator was used to model random effects which were supported by the Hausman test.

Findings suggest that the influence of macroeconomic fundamentals on ROE deteriorates as one moves from competitive to concentrated industries. ROE is volatile in concentrated markets and less volatile in competitive markets. Concentrated markets generally enjoy monopoly profits. Gross domestic product and interest rates have a positive impact on ROE, while inflation, unemployment and exchange rates have a negative effect.

This study highlights the need to apply appropriate business strategies and policies depending on the structure of the industry. Competitive advantage strategies may assist in sustaining profits of firms in competitive markets. Regulators need to be proactive and stress test the impact of a policy on industry performance before implementation because competitive and concentrated markets react differently to external shocks. Risk tolerant investors may invest in volatile markets such as Russia and South Africa, while risk-averse investors may prefer to invest in less volatile markets such as India and China.

This paper aims to examine asymmetries in the house price cycle and to understand the dynamic of housing prices, incorporating macroeconomic variables at regional and country level, namely, housing affordability, the unemployment rate, mortgage rate and inflation rate.

To highlight significant differences in the asymmetric patterns of house prices between regions, the STAR model is adopted.

The authors highlight significant differences in the asymmetric patterns of house prices between regions, in which some areas showed asymmetric response over the housing cycle; here the LSTAR model outperforms other models. In contrast, some regions (the South West and the North West) showed symmetric properties in the tails of the cycle; therefore, the ESTAR model was adopted in their case.

Being limited to a few fundamentals, this study opens an avenue for further research to investigate this dynamic using in addition such demand-supply factors as land supply, construction cost and loans made for housing. These findings can also be used to examine whether other models such as ARIMA, exponential smoothing or artificial neural networks can more accurately forecast housing prices.

The present paper aims to highlight housing affordability as a cause of asymmetric behaviour in house prices. Put differently, the authors seek to understand the dynamics of housing prices with other fundamentals incorporating macroeconomic variables in regions and country level data as a means of achieving a more concise result.

The purpose of this paper is to use the Barberis et al. (1998)’s valuation model to calculate the fundamental value of a stock and examine whether the differences between predicted and realized stock prices are explained both by psychological factors (that affect investor reaction to information) and by key macroeconomic variables.

This paper adopts a time-series analysis, as well as a panel data approach, to examine whether the price deviations from fundamental values are because of macroeconomic and psychological factors, using data from the London Stock Exchange.

The results indicate that these differences are explained by important macroeconomic variables, as well as by the sentiment of investors (that is used as a proxy of the psychological factors).

Based on the above results, this paper suggests that the price deviations from fundamental values are not treated as model estimation errors as proposed by Penman and Sougiannis (1998) but rather as deviations that are because of psychological factors, as well as to macroeconomic conditions.

This study aims to analyze the influence of political regime on economic growth.

The methodology was based on an inter-period comparison of the evolution of macroeconomic fundamentals in three different political regimes in Ecuador, a South American country.

The results showed that what determines the evolution of macroeconomic fundamentals is not the political regime that oversees it, but the size of a positive exogenous shock on the price of raw materials, which, by providing higher incomes, considerably increases the level of investment and net exports. However, the political regime does affect the distribution of income in sectors such as health and education.

As far as the authors know, this may be the first paper to explore the importance of a positive exogenous shock on a political regime for the case of primary-exporting Latin American economies, which are price takers subject to exogenous shocks.

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.

In the light of past financial and economic turmoil, there has been a marked increase in the volatility in real estate markets. This has impacted on the pricing of property assets, partly through market sentiment and particularly concerning risk. It also limits modelling accuracy model accuracy. The purpose of this paper is to create a new variable and model to enhance analysis of what drives real estate yields incorporating market sentiment to risk.

This paper specifically considers the modelling of property pricing within a volatile economic environment. The theoretical context begins by analysing the relationship between property yields and government bonds. The analytical context then moves on to specifically include a measurement of risk which stresses its role and importance in investment markets since the Global Financial Crisis. The model thus incorporates macroeconomic and real estate data, together with an international risk multiplier, which is calculated within the paper.

The paper finds the use of measurements of market sentiment and risk are more powerful tools for modelling yields than previous techniques alone.

This is an initial paper outlining the creation of sentiment and risk measurements in the financial market and showing an example of its application to a commercial real estate market. The implication is that this could add a major new explanatory variable to modelling of yields.

The paper highlights the importance of risk in the pricing of commercial real estate, over and above normal variables. It highlights how this can help explain over and undershooting of yields within commercial real estate which would be of great importance in the investment world.

This paper attempts to explicitly measure market sentiment, pricing of risk and how this impacts real estate pricing.