This paper examines which valuation approaches financial analysts use to value a company and whether the chosen valuation approach affects the target price accuracy. To address these questions, we conduct content analyses of 867 hand-collected analyst reports on German publicly listed companies published between January 2014 and June 2017. We find that sell-side analysts more frequently use the single-period market approach when formulating target prices, followed by the multi-period income approach, and a mixture of both by combining the results, the so-called hybrid valuation approach. Additionally, we show that 612 of the analyzed analyst reports are based on a holistic valuation methodology instead of a sum of the parts valuation technique. Both univariate and multivariate analyses emphasize that the choice of valuation approach is significantly associated with the accuracy of price targets. Specifically, the income and market approach lead to significantly more accurate target prices compared to the hybrid approach. We also find that the target price accuracy is higher when analysts apply the holistic rather than the sum of the parts valuation approach to determine the fundamental value of the company. Additional results emphasize that target price accuracy improves when analysts use the sum of the parts valuation that bases solely on market or income approaches rather than hybrid approaches. Hence, we contribute to theory and practice by providing evidence on the link between the choice of valuation approach and the analysts’ target price accuracy as well as on the performance of certain valuation techniques.

This study investigates if and how the influence of compensation interdependence on risk-taking depends on mutual monitoring of risky investment decisions. We argue that individuals under compensation interdependence have a behavioral incentive for higher risk-taking if mutual monitoring is present. Impression management is hypothesized to be the driving force behind this effect, with the visibility of actions to the peers through mutual monitoring as an important prerequisite. The results of a laboratory experiment support our predictions. Additional analyses reveal that impression management drives our results because participants incorporate their peers’ preferences in their decision process. This reasoning is further substantiated as individuals increase their risk-taking if they took less risk than their peers in previous experimental rounds and thus adjust to their respective peer group. Our findings inform firms about the effect of compensation interdependence in working environments with differing opportunities for mutual monitoring.

The literature on cross-sectional stock return predictability has documented over 450 factors. We take the perspective of an institutional investor and navigate this zoo of factors by focusing on the evidence relevant to the practicalities of factor-based investment strategies. Establishing a sound theoretical rationale is key to identifying “true” factors, and we emphasize the need to recognize data-mining concerns that may cast doubt on the relevance of many factors. From a practical investment perspective, much of the factor evidence documented by academics may be more apparent than real. The performance of many factors is dependent on the inclusion of small- and micro-cap stocks in academic studies, although such stocks would likely be excluded from the real investment universe due to illiquidity and transaction costs. Nevertheless, a parsimonious set of factors emerges in equities and other asset classes, including currencies, fixed income, and commodities. These factors can serve as meaningful ingredients to factor-based portfolio construction.

In the chemical industry, shortened product life cycles and greater differentiation of customer demand increase challenges to efficiently meet specific customer requirements. Thus, production systems with high flexibility are required. One innovative production concept that meets this requirement is decentralized, small-scale modular production which offers significantly more flexibility in the tactical configuration of the production network. Corresponding production plants are assembled from standardized apparatus modules in transportation containers, hereby enabling a fast relocation of modular plants and adjustments of the production process. Therefore, modular plants can be operated close to customers or suppliers, which supports local sourcing strategies and a reduction in delivery costs. In this paper, we analyze the advantages of these modular production systems for a case from the specialty chemicals industry. Respective advantages arise especially from a technically flexible design of parallel process lines, autonomous production and local sourcing. In order to evaluate economic efficiency and network configuration of modular production networks, an efficient mathematical formulation for the optimization is proposed. This formulation includes a new way to model relocations of modules. We apply this model to a case based on real data from the chemical industry. As a result of this application we come to three technical and managerial conclusions. Firstly, technical designs with parallel process lines improve flexibility and efficiency compared to mono processes. Secondly, autonomous production increases economic efficiency in contrast to staffed production and finally, local sourcing offers significant cost reduction potential compared to central sourcing.

Corporate valuation often relies on the assumption of a constant and homogenous growth rate. However, large firms frequently (re)balance their activities by diverting cash flows from some business units to fund investments in other units. We develop a value driver model of terminal value for a firm with two units. The model relaxes common assumptions and allows for cross-unit differences in the return on invested capital. We consider intra-unit and cross-unit investments and show their implications for firm value and the long-term development of key accounting variables. Our results help characterize business unit strategies that can be reconciled with popular firm strategies such as the constant payout and constant growth strategies. We find that popular valuation methods that assume both constant payout ratios and constant growth rates (e.g., Gordon and Shapiro, Manage Sci 3:102–110, 1956) constitute a restrictive special case of our model and should only be applied to firms with homogenous business units. We use a simulation analysis to compare our results with alternative valuation models and to illustrate the economic relevance of our findings. The simulation shows that an accurate depiction of business unit strategy is particularly useful if firms plan large-scale cross-unit investments into business units with high returns and if the cost of capital is low.

In this paper, the liquidity (inverse of time on market) of rental dwellings and its determinants for different liquidity quantiles are examined for the seven largest German cities. The determinants are estimated using censored quantile regressions in order to investigate the impact on very liquid to very illiquid dwellings. As market heterogeneity is not only observed between cities but also within a city, each of the seven cities is considered individually. Micro data for almost 500,000 observations from 2013 to 2017 is used to examine the time on market. Substantial differences in the magnitude and direction of the regression coefficients for the different liquidity quantiles are found. Furthermore, both the magnitude and direction of the impact of an explanatory variable on the liquidity, differ between the cities. To the best of the authors’ knowledge this is the first paper, to apply censored quantile regressions to liquidity analysis of the real estate rental market. The model reveals that the proportionality assumption underlying the Cox proportional hazards model cannot be confirmed for all variables across all cities, but for most of them.

This paper revisits the impact of collection cost on a manufacturer’s optimal reverse channel choice. A manufacturer who remanufactures his own products has the choice between managing collection of used products himself, let the retailer manage collection or involve a third party company to manage collection. In particular, we consider a convex collection cost function depending on the collection rate. Contrary to previous literature, we show that the manufacturer always prefers retailer-managed collection, independent of collection cost. The retailer will always choose a positive collection rate. If collection cost is above a certain threshold, not all used products will be collected and the manufacturer (almost) collects all channel profits. Third party-managed collection is always dominated. In extensions, we also consider a restriction to equilibria and a minimum collection rate, which may be imposed by regulation. Both extensions may change the reverse channel choice to manufacturer-managed. Moreover, we see that it may be impossible for regulation to increase collection because the profit-maximizing collection rate may already be the highest economically viable one.

We study the problem to simultaneously decide on the structures and the schedules for an entire portfolio of flexible projects. The projects are flexible as alternative technologies and procedures can be used to achieve the respective project task. The choice between different technologies and procedures affects the activities to be implemented and thus the precedence relations, i.e., the structure of the project. The different projects have given due dates with specific delay payments and compete for scarce resources. In this situation, project structure decisions and scheduling decisions are highly intertwined and have to be made simultaneously in order to achieve the assumed objective of minimizing the delay payments for the entire project portfolio. The problem is formally stated and solved via novel and problem-specific genetic algorithms. The performance of the new algorithms is evaluated with respect to speed and accuracy in a systematic and comprehensive numerical study.

This experimental study analyzes how a key factor, information load, influences decision making in escalation situations, i.e., in situations in which decision makers reinvest further resources in a losing course of action, even when accounting information indicates that the project is performing poorly and should be discontinued. This study synthesizes prior escalation research with information overload and investigates how different levels of information load influence the escalation of commitment. Our findings reveal a U-shaped effect of information load: When decision makers face negative feedback, a higher information load mitigates the escalation tendency up to a certain point. However, beyond this point, more information reinforces the escalation tendency. Moreover, we find that the type of feedback affects self-justification, and we find a negative and significant interaction between information load and self-justification in negative-feedback cases. Thus, studies investigating escalation of commitment should control for self-justification and information load when utilizing high levels of information load. Finally, in the positive-feedback condition, higher information load encourages decision makers to continue promising courses of action, i.e., increases decision-making performance.

Recent empirical evidence raises doubt about the ability of financial market participants to generate information efficient valuations for capital market instruments whose cash flows are related to residual claims and dependent on real estate income. We contribute to this literature with the examination of value implications of non-performing loan (NPL) divestitures in the banking industry during the period 2012–2018. In a first step, we provide descriptive statistics of the European NPL market, which lacks transparency and publicly available basic information on portfolio size and components. We then analyze wealth effects of distressed loan sale announcements for a uniquely large transaction database with 317 NPL deals, which is largely driven by real estate collateral. Our results show positive stock market reactions for vendor banks following NPL divestitures that tend to be driven by real estate collateral and a size effect.