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In this paper, we explore an extensive panel data set covering more than 4,000 listed firms in 16 European countries to study the effects of shareholder protection on ownership structure and firm performance. We document a negative firm-level correlation between shareholder protection and ownership concentration. Differentiating between shareholder types, we find that this pattern is mainly driven by strategic investors. In contrast, we find a positive correlation between shareholder protection and block ownership of institutional investors, in particular when we restrict the analysis to independent institutional investors. Finally, we find that independent institutional investors are positively associated with firm valuation as measured by Tobin’s Q. The opposite applies for strategic investors. Overall, our results are consistent with the view that (i) high shareholder protection and (ii) limited ownership by strategic investors make small investors and investors interested in security returns more confident in their investments.

The purpose of this paper is to determine the extent to which outliers have persisted in augmenting the Halloween effect over time and to offer an econometric test of seasonality in return skewness that might provide a partial explanation for the Halloween effect.

The authors split the Morgan Stanley Capital International data for 37 countries into two subperiods and, using median regression and influence vectors, examine these periods for a possible change in the interplay between outliers and the Halloween effect. The authors perform a statistical assessment of whether outliers are a significant contributor to the overall Halloween effect using a bootstrap test of seasonal differences in return skewness.

Large returns (positive and negative) persist in being generally favorable to the Halloween effect in most countries. The authors find seasonality in return skewness to be statistically significant in many countries. Returns over the May through October timeframe are negatively skewed relative to returns over the November through April period.

This paper offers the first statistical test of seasonality in return skewness in the context of the Halloween effect. The authors show the Halloween effect to be a more complex phenomenon than the simple seasonality in mean returns documented in prior research.

The purpose of this paper is to understand the association between litigation risk and working capital management.

The authors employ four different regression techniques (OLS regressions, regressions with industry and time controls, median regressions, and Fama Macbeth regressions) to study the relation between litigation risk (contemporaneous and lagged measures) and working capital management (cash conversion cycle (CCC) and its components). The authors also conduct numerous robustness tests.

The authors find that high-litigation risk firms tend to have longer CCC. Decomposing CCC into days receivable outstanding, days inventory outstanding and days payable outstanding, the authors find that high-litigation risk firms have longer receivable periods, take a longer time to convert inventory to cash and do not pay their suppliers promptly. These results are robust to a series of robustness tests including using an alternate measure of working capital and accounting for firm type (high-tech vs labor intensive).

This paper contributes in several ways to the litigation and corporate finance literature. The authors identify another determinant of working capital management and document another avenue whereby legal institutions affect short-term financial decision making. The link between litigation risk and working capital management is of interest to the business community, financial economists, management and the investing public.

The purpose of this paper is to examine how the impact of Chinese peer-to-peer (P2P) platform reputation directly and indirectly (mediate effect) affects investors’ (lenders) investment choices.

Using data collected from 478 P2P platforms, this paper calculates platform reputation via a β function after establishing a reputation mechanism by game analysis. This is followed by testing both the direct effect of platform reputation on investors’ investment choices (proxying by transaction volume) and the indirect effect through credit-enhancing information using three regression models (median regression, OLS regression and random effect OLS regression). A robustness test by adding instrument variables is conducted to confirm the findings from the main regressions.

In China, P2P lending platform reputations have played both a direct and indirect (through credit-enhancing information) role on investors’ investment choices.

This paper expands the boundary of P2P online lending research by not only examining the direct, but also, importantly, the indirect effects of platform reputations.

This paper aims to investigate whether there is heterogeneity in the relationship between the bank loan interest rate and its determinants using the quantile regression method and to reconcile some conflicting findings in prior literature.

First, the effects of 18 determinants were examined on the bank loan interest rate using the ordinary least squares method (OLS). Second, it was investigated whether the relationship between the loan rate and its determinants is heterogeneous across quantiles of loan rates using the quantile regression method.

Considerable heterogeneity was found in the relationship between the loan rate and its determinants. Specifically, a determinant that is beneficial for the bank loan rate, on average, as revealed by the OLS method may become unimportant or even detrimental for firms located at extremely high or low loan rate quantiles. By revealing extreme heterogeneity in the relationship between the loan rate and some of its determinants, the authors potentially explain two conflicting findings in prior literature.

The conventional OLS method masks the heterogeneity in the relationship between the bank loan interest rate and its determinants. Quantile regression can be used to supplement the OLS estimates to gain a more detailed and complete picture of the relationship between the dependent variable and explanatory variables.

This study aims to introduce a tree-structured linear and quantile regression framework to the analysis and modeling of equity returns, within the context of asset pricing.

The approach is based on the idea of a binary tree, where every terminal node parameterizes a local regression model for a specific partition of the data. A Bayesian stochastic method is developed including model selection and estimation of the tree structure parameters. The framework is applied on numerous U.S. asset pricing models, using alternative mimicking factor portfolios, frequency of data, market indices, and equity portfolios.

The findings reveal strong evidence that asset returns exhibit asymmetric effects and non- linear patterns to different common factors, but, more importantly, that there are multiple thresholds that create several partitions in the common factor space.

To the best of the authors' knowledge, this paper is the first to explore and apply a tree-structured and quantile regression framework in an asset pricing context.

The purpose of this paper is to address the heterogeneity of real estate assets with regard to investment risk measurement, with Paris’ apartment market as a case study.

Quantile regression is used to handle the fact that willingness to pay for housing attributes may vary greatly over both space and asset value categories. The method is alternately applied on central and peripheral districts of Paris, or “arrondissements”, with hedonic indices built for nine deciles over a 17-year period (1990-2006). Portfolio allocation is subsequently analysed with deciles being the assets.

The findings suggest that during the slump, peripheral districts show better resilience and define the efficient frontier while also exhibiting a lower volatility. In addition, higher returns are observed for lower-priced apartments, both central and peripheral. During the recovery and boom stages of the cycle, the highest returns are experienced for the cheapest apartments in central locations, whereas upper-priced, centrally located units yield the lowest returns.

The originality of this research resides in the application of quantile regression in a real estate investment and risk management context. The methodology may raise individual investors’ and practitioners’ attention, especially index providers’.

This paper aims to study individual managers’ market timing capabilities while trading (either buying or selling) stock from their portfolios, as well as the impact of gender, seniority and trading frequency on their market timing performance.

This study uses a relative transaction price approach introduced by Dittmar and Field (2015) on 837 aggregated trades made by managers from their portfolios between 2010 and 2015. These were taken from publicly disclosed information through the Portuguese regulator. Furthermore, this study uses a median regression-based method to infer the authors’ conclusions.

The authors find that insiders buy (sell) at a relatively lower (higher) price when compared to other traders. This evidence shows that insiders have market timing capabilities. Moreover, this paper shows that contrarily to gender, both seniority and frequency help explain market timing performance and that insiders’ trades made over-the-counter (OTC) generally overperform the ones made on the open market (OM). Finally, this study finds a significant crisis-related influence on insiders’ market timing performance.

This study contributes to the literature by studying insider trading at the portfolio level, by analyzing the impact of personal characteristics of insiders (including gender, tenure and eagerness), focusing both on studying the buying and selling behavior across both OMs and OTC and analyzing firsthand the impact of a macroeconomic shift on insider trading performance.

Are firms able to time the market? The purpose of this paper is to focus on the study of own stock trading, emphasizing both repurchase and resell operations on the open market as well as over the counter.

The authors use data on 37,997 own stock transactions from 2005 to 2015 of Euronext Lisbon listed firms. Following Dittmar and Field (2015), this paper uses relative transaction prices to ascertain the relative performance of own stock transactions, in the open market and over the counter.

Results show that firms can time both repurchases as well as resales. Firms repurchase (resell) at lower (higher) prices than those prevailing in the market. Moreover, market-timing ability proves to be higher after the bailout period and to be influenced by the own stock trading frequency. Trading on the open market allows for increased timing ability for own stock repurchasing and reselling activity. Finally, results show seasonal effects both in repurchase and resale performance. Also, more efficient but less valuable firms are more likely to be successful in timing the market.

The authors study both the repurchasing and the reselling activity of the same set of firms, of already issued stock, using high-frequency (daily) data. In addition, the authors study own stock trading both in the open market and OTC, and also study the impact of a major economic shift on the firms’ ability to time the market.

The purpose of this paper is to determine whether there are empirical differences in the extent and motivation of early internationalisation between indigenous and foreign‐invested Chinese firms.

Data on 3,948 firms surveyed by the World Bank in 2002 and 2003 in China are used and four hypotheses are tested using regression analysis.

Despite having started with internationalisation relatively more recently than most foreign‐invested firms, and having less foreign experience, indigenous firms which internationalise early perform better than foreign‐invested firms.

The data were not gathered with international entrepreneurship in mind, may not include all relevant control variables, and lack a panel.

China is a country noted for its success in internationalisation. However, this has been due, in the most part, to foreign‐invested firms, with indigenous firms seemingly being less successful. This makes knowledge of the differences in early internationalisation behaviour of indigenous versus foreign‐invested firms potentially interesting.