Socially responsible investing and stock performance: New empirical evidence for the US and European stock markets

This paper empirically examines the theoretically ambivalent relationship between socially responsible investing (SRI) and stock performance. It contributes to the existing literature by considering both the US and the entire European stock markets and by using consistent world-wide corporate sustainability performance data. Our portfolio analysis from 1998 to 2009 is based on the common four-factor model according to Carhart (1997), which comprises market return, size, value, and momentum factors. We show for the US and the European stock markets that SRI is associated with large-sized firms. The insignificant abnormal stock returns for SRI in both regions are the main result of our paper. Therefore, our study supports the view that SRI stocks are correctly priced by market participants, although we cannot rule out that a corresponding mispricing has existed before the beginning of our observation period in 1998.     

Behavioral Integration as a Relational Governance Mechanism in Family Firms—The Moderating Role of Family Involvement in Management

In this paper we introduce behavioral integration, a construct established in top management team (TMT) research, into the family firm field. TMT research argues that behavioral integration has a positive performance effect as it fosters commitment to the task at hand, joint goals, and mutual trust among TMT members. Because of these specific characteristics, we argue that behavioral integration might act as a relational governance mechanism that positively influences family firm performance. Based on research on family involvement in management, we posit that this positive performance effect of behavioral integration as a relational governance mechanism is particularly pronounced in family firms with a high degree of family involvement in management.     

Initial coin offerings (ICOs) to finance new ventures

In an initial coin offering (ICO), new ventures raise capital by selling tokens to a crowd of investors. Often, this token is a cryptocurrency, a digital medium of value exchange based on the distributed ledger technology. Both the number of ICOs and the amount of capital raised have exploded since 2017. Despite attracting significant attention from ventures, investors, and policy makers, little is known about the dynamics of ICOs. This initial study therefore assesses the determinants of the amount raised in 423 ICOs. Drawing on signaling theory, the study explores the role of signaling ventures' technological capabilities in ICOs. The results show that technical white papers and high-quality source codes increase the amount raised, while patents are not associated with increased amounts of funding. Exploring further determinants of the amount raised, the results indicate that some of the underlying mechanisms in ICOs resemble those found in prior research into entrepreneurial finance, while others are unique to the ICO context. The study's implications are multifold and discussed in detail. Importantly, the results enable investors to more accurately understand crucial determinants of the amount raised (e.g., technical white papers, source code quality, token supply, Ethereum-standard). This reduces the considerable uncertainty that investors face when investing in ICOs and enables more informed decision-making.     

Discrete time Wishart term structure models

This paper reveals that the class of Affine Term Structure Models (ATSMs) introduced by Duffie and Kan (1996) is larger than previously considered in the literature. In the framework of risk factors following a Wishart autoregressive process, we define the Wishart Term Structure Model (WTSM) as an extension of a subclass of Quadratic Term Structure Models (QTSMs), derive simple parameter restrictions that ensure positive bond yields at all maturities, and observe that the usual constraint on affine processes requiring that the volatility matrix be diagonal up to a path independent linear invertible transformation can be considerably relaxed.     

A Typology of International New Ventures: Empirical Evidence from High‐Technology Industries

We examine determinants of different types of International New Ventures (INVs), namely Export Start‐up, Geographically Focused Start‐up, Multinational Trader, and Global Start‐up. Whereas this typology of INVs has been widely accepted in the literature, empirical testing of the determinants of INV types is largely missing. Our arguments build on the International New Venture Theory (INVT). Hypotheses generated from our framework are tested on 195 German high‐tech enterprises. Results show that growth orientation, prior international experience, knowledge intensity, product differentiation, and learning orientation distinguish significantly between the different INV types.     

Testing time series data compatibility for benchmarking

Compatibility testing determines whether two series, say a sub-annual and an annual series, both of which are subject to sampling errors, can be considered suitable for benchmarking. We derive statistical tests and discuss the issues with their implementation. The results are illustrated using the artificial series from Denton (1971) and two empirical examples. A practical way of implementing the tests is also presented.     

A note on forecasting the prices of gold and silver: Asymmetric loss and forecast rationality

Given that the prices of gold and silver have witnessed large and substantial swings in recent years, policymakers and investors need readily available and reliable forecasts of the prices of these two precious metals. Survey data of forecasts of the prices of gold and silver provide a particularly rich data environment for policymakers and investors to study developments in the markets for gold and silver. Our research helps to develop a deeper understanding of the properties of survey data of the prices of gold and silver. We study the shape of forecasters’ loss function and the rationality of their forecasts. Assuming an asymmetric loss function weakens evidence against forecast rationality, but results depend on the empirical model being studied.