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Although the pervasive influence of investor sentiment in equity markets is well documented, little is known about behavioral manifestations in bond markets. In this paper, we explore the impact of investor sentiment on corporate bond yield spreads. Our results reveal that bond yield spreads co‐vary with sentiment, and sentiment‐drivenmispricings and systematic reversal trends are very similar to those for stocks. Bonds appear underpriced (with high yields) during pessimistic periods and overpriced (with low yields) when optimism reigns. Consequent reversals result in predictable trends in post‐sentiment yield spreads.When beginning‐of‐period sentiment is low, subsequent yield spreads are low; high sentiment periods are followed by high spreads. High‐yield bonds (low ratings, Industrials and Utilities, extreme maturities or low durations, specially if low rated) demonstrate greater susceptibility to mispricings due to sentiment compared to low‐yield bonds. The incremental yield spread gap between highand low‐yield bonds converges subsequent to periods of low sentiment, and diverges after high sentiment. Equity attributes marginally influence the impact of sentiment on bond spreads, but mostly for distressed bonds only.

The purpose of this paper is to examine the time series behavior of Greek labor market series by providing an empirical perspective on trend breaks and unit roots. Trend breaks represent aggregate behavior responses to “infrequent” changes in economic fundamentals, including changes in fiscal or labor market conditions, as have been perceived in Greece during the last years. Unit roots reveal whether “regular” shocks have significant effects on the level of the series over a specified finite horizon.

The authors employ recent procedures that deal with the “circular testing problem” between tests on the parameters of the trend function and unit root tests that often arises in empirical applications. These techniques assess trend function stability and are robust regardless of whether the noise component is stationary or having a unit root. Then, conditional on the presence of breaks, the authors test whether the series can be characterized by a stochastic trend.

The analysis provides evidence of “infrequent” trend breaks that appear to coincide with the recent global economic crisis and the implementation of the counteraction (fiscal) measures to the Greek debt crisis. Allowing for trend breaks does not lead to a rejection of the unit root hypothesis, which might reflect the low flexibility of the country’s labor market operation.

The procedures employed can be viewed as new tools that might help empirical researchers to explore more accurately the characteristics of individual time series and to find reasonable approximations to the true processes of the time series examined.

The paper provides new information on the presence of structural changes in the Greek labor market, and on whether the “aggressive” and “occasional” nature of fiscal measures can be approximated by infrequent changes in the slope of the trend function.

In the run‐up to the 1992 single‐market deadline, there were concerns that inter‐industry adjustment pressures among EU member countries would increase. Such expectations were due partly to a perceived reversal of the post‐Second World War growth in intra‐industry trade (IIT). Finds that average IIT levels continued to rise during the implementation of the single market. It is argued that the concept of marginal IIT(MIIT) is of greater relevance to adjustment than “static” IIT. Some evidence is shown to support this proposition, and a comprehensive set of intra‐EU MIIT indices is calculated for the 1980s. Since average MIIT levels in the 1988‐92 period were higher than in the early 1980s, this analysis also supports the conclusion that, on average, adjustment to the single market was no more disruptive than that experienced during earlier stages of European integration. It also appears that the forces for inter‐industry adjustment are stronger in traditional, declining industries, whereas the expansion of relatively advanced industries tends to be more evenly shared by the EU member countries.

This paper aims to analyze the heuristics and cognitive biases described by behavioral finance in the investment decision-making process of Portugal’s housing market.

In a first step, the authors applied an exploratory factor analysis (EFA) to assess the impact of heuristics and cognitive biases on investors’ decision-making. In a second step, the authors run a structural equation model (SEM) diagram path to assess if the sociodemographic characteristics of housing market investors determine the identified heuristics and if the heuristics condition the investors’ investment criteria.

Herd behavior and the heuristics of representativeness, availability and anchoring influence the housing market’s investors’ behavior in their decision-making process. Investors with above-average income show higher levels of overconfidence. Investors showing higher levels of overconfidence also tend to be more sensitive to the house price under analysis for investment. Women tend to show higher levels of the availability and anchoring heuristic. In turn, housing market investors showing higher levels of availability and anchoring heuristic tend to be more sensitive to the price and location of the house under analysis for investment.

The explained variance of the EFA is below 50%, and the root mean square of approximation of the SEM is above the threshold of 0.05. These indicators are evidence of the models’ fragility.

Governments and regulators can better prevent real estate bubbles if they monitor behavioral biases and heuristics of housing investors together with quantitative indicators. Realtors can profit from adapting their marketing strategy and commercial communication to investors of sociodemographic groups more prone to a specific type of heuristics.

To the best of the authors’ knowledge, this is the first study that combines the contributions of behavioral finance with Portugal’s housing investment market and the first study connecting heuristics to investment criteria.

This study examines credit score migration rates of farm businesses, testing whether migration probabilities differ across business cycles. Results suggest that agricultural credit ratings are more likely to improve during expansions and deteriorate during recessions. The analysis also tests whether agricultural credit ratings depend on the previous period migration trends. The findings show that credit score ratings exhibit trend reversal where upgrades (downgrades) are more likely to be followed by downgrades (upgrades).

Loan migration analysis is conducted using a large data set of loan risk ratings in the Farm Credit System. We find path dependence and limited support for a trend reversal pattern. There is evidence that the magnitude of migrations reported in previous credit score proxy studies overstates trend reversal in agricultural loans rated by lenders. Our results indicate that retention rates of agricultural loan risk ratings are quite high. Small loans are less likely to migrate than medium and large‐sized loans, and unseasoned loans are more likely to migrate than seasoned farm loans