Contributions in Merlin

This paper presents an analysis of the European Emission Trading System as a transaction network. It is shown that, given the lack of a centralized market place, industrial actors had to resort to local connections and financial intermediaries to participate in the market. This gave rise to a hierarchical structure in the transaction network. To empirically relate networks statistics to market outcomes a PLS-PM modeling technique is introduced. It is shown that the asymmetries in the network induced market inefficiencies (e.g. increased bid-ask spread). Albeit the efficiency of the market has improved from the beginning of Phase II, the asymmetry persists, imposing unnecessary additional costs on agents and reducing the effectiveness of the market as a mitigation instrument.

The data-driven economy has led to a significant shortage of data scientists. To address this shortage, this study explores the prospects of outsourcing data analysis tasks to freelancers available on online labor markets (OLMs) by identifying the essential factors for this endeavor. Specifically, we explore the skills required from freelancers, collect information about the skills present on major OLMs, and identify the main hurdles for out-/crowd-sourcing data analysis. Adopting a sequential mixed-method approach, we interviewed 20 data scientists and subsequently surveyed 80 respondents from OLMs. Besides confirming the need for expected skills such as technical/mathematical capabilities, it also identifies less known ones such as domain understanding, an eye for aesthetic data visualization, good communication skills, and a natural understanding of the possibilities/limitations of data analysis in general. Finally, it elucidates obstacles for crowdsourcing like the communication overhead, knowledge gaps, quality assurance, and data confidentiality, which need to be mitigated.

One of the most challenging problems in technological forecasting is to identify as early as possible those technologies that have the potential to lead to radical changes in our society. In this paper, we use the US patent citation network (1926-2010) to test our ability to early identify a list of historically significant patents through citation network analysis. We show that in order to e?ectively uncover these patents shortly after they are issued, we need to go beyond raw citation counts and take into account both the citation network topology and temporal information. In particular, an age-normalized measure of patent centrality, called rescaled PageRank, allows us to identify the significant patents earlier than citation count and PageRank score.

By applying the inventory theory to hiring skilled workers under uncertainty, the authors explain how firms decide on their optimum investment in an "inventory of skills." This paper investigates the conditions under which firms are willing to make investments in a skilled workforce themselves rather than relying on skills produced within the education system or by other companies. By applying inventory theory to investments into apprenticeship training, the authors explain how firms decide on producing an optimum "inventory of skills" today to meet future demand. The authors derive hypotheses on how much firms are willing to invest in having a larger inventory of skilled worker depending on different types of inventory costs (overage cost, underage costs, demand structure). The authors use data from the BIBB Cost-Benefit-Survey 2012/2013, which comprises detailed information on different costs and benefits of training investments from the firm's perspective. The study applies a negative binomial estimation model. Results are threefold: firms are willing to invest in a larger inventory of skilled workers, i.e., to train more apprentices, first, if the costs of producing and retaining an excessive number of skilled workers (overage costs) are lower, second, if the costs of being short of skilled workers (underage costs) are higher, and third, given an identical cost structure, if it is more likely that the demand for skilled worker may be high in the future. Even more important is the relationship of the three: the combination of a firm's critical ratio (underage costs in relation to overage costs) with its demand structure (industry volatility) is associated with a higher inventory of skills. The findings (particularly the relation of underage and overage costs, in combination with the demand structure) have important policy implications for firms' incentives to invest in apprenticeship training.

Is the American put option in the Black-Scholes model simply an incognito European one? In this paper, we develop a numerical procedure, in the context of the Black-Scholes model, to approximate the payoff of a European type option that generates prices that are equal to the prices of the American put option in the continuation region. The resulting equivalent European payoff is a sum of power payoffs and therefore the price and the hedging indicators can be computed in closed form. For a given set of model parameters (interest rate, dividend rate and volatility) the computation of the equivalent European payoff reduces to solving a linear optimization problem. We conduct a numerical experiment spanning a wide range of model parameters and contract characteristics and, overall, the method produces American option prices with a relative RMSE less than 0.01% compared to a benchmark.

Under short sales prohibitions, no free lunch with vanishing risk (NFLVR-S) is known to be equivalent to the existence of an equivalent supermartingale measure for the price processes (Pulido, 2014). For two given price processes, we translate the property (NFLVR-S) in terms of so called structure conditions and we introduce the concept of fun- damental supermartingale measure. When a certain condition necessary to the construction of the fundamental martingale measure is not fulfilled, we provide the corresponding arbi- trage portfolios. The motivation of our study lies in understanding the particular case of converging prices, i.e., that are going to cross at a bounded random time.

In classical contagion models, default systems are Markovian conditionally on the observation of their stochastic environment, with interacting intensities. This necessitates that the environment evolves autonomously and is not influenced by the history of the default events. We extend the classical literature and allow a default system to have a contagious impact on its environment. In our framework, contagion can either be contained within the default system (i.e., direct contagion from a counterparty to another) or spill from the default system over its environment (indirect contagion). This type of model is of interest whenever one wants to capture within a model possible impacts of the defaults of a class of debtors on the more global economy and vice versa.