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The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the ”Natural Language Toolkit” that uses machine learning models to extract the news’ sentiment. We consider the period from January till June 2020 and analyze 203,886 online articles that deal with the pandemic and that were published on three platforms: MarketWatch.com, Reuters.com and NYtimes.com. Our findings show that there is a significant and positive relationship between sentiment score and market returns. This result indicates that an increase (decrease) in the sentiment score implies a rise in positive (negative) news and corresponds to positive (negative) market returns. We also find that the variance of the sentiments and the volume of the news sources for Reuters and MarketWatch, respectively, are negatively associated to market returns indicating that an increase of the uncertainty of the sentiment and an increase in the arrival of news have an adverse impact on the stock market.
Using experimental data from a comprehensive field study, we explore the causal effects of algorithmic discrimination on economic efficiency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing counterfactuals, which generally impedes assessing economic downstream consequences of algorithmic discrimination. This way, we are able to precisely quantify downstream efficiency and welfare ramifications, which provides us a unique opportunity to assess whether the introduction of an AI system is actually desirable. Our results highlight that AI systems’ capabilities in enhancing welfare critically depends on the degree of inherent algorithmic biases. While an unbiased system in our setting outperforms humans and creates substantial welfare gains, the positive impact steadily decreases and ultimately reverses the more biased an AI system becomes. We show that this relation is particularly concerning in selective-labels environments, i.e., settings where outcomes are only observed if decision-makers take a particular action so that the data is selectively labeled, because commonly used technical performance metrics like the precision measure are prone to be deceptive. Finally, our results depict that continued learning, by creating feedback loops, can remedy algorithmic discrimination and associated negative effects over time.
In this paper we adopt the Hamiltonian Monte Carlo (HMC) estimator for DSGE models by implementing it into a state-of-the-art, freely available high-performance software package. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model on US data. Our results and sampling diagnostics confirm the parameter estimates available in existing literature. In addition we combine the HMC framework with the Sequential Monte Carlo (SMC) algorithm which permits the estimation of DSGE models with ill-behaved posterior densities.
In these volumes, we are very pleased to present a collection of papers based on talks and posters at Sinn und Bedeutung 22, which took place in Berlin and Potsdam on September 7-10, 2017, jointly organized by the Leibniz-Centre for General Linguistics (ZAS) and the University of Potsdam.
SuB22 received 183 submitted abstracts. Out of these, the organizing committee selected 39 oral presentations in the main session, 4 oral presentations in the special session ‘Semantics and Natural Logic’, and 24 poster presentations. There were an additional 6 invited talks. In total, 58 of these contributions appear in paper form in the present volumes.
Incentivized experiments in which individuals receive monetary rewards according to the outcomes of their decisions are regarded as the gold standard for preference elicitation in experimental economics. These task-related real payments are considered necessary to reveal subjects' "true preferences". Using a systematic, large-sample approach with three subject pools of private investors, professional investors, and students, we test the effect of task-related monetary incentives on risk preferences elicited in four standard experimental tasks. We find no systematic differences in behavior between subjects in the incentivized and non-incentivized regimes. We discuss implications for academic research and for applications in the field.
The present paper seeks to study the possible diversification potential by the integration of indirect real estate investments in international portfolios. To this end, monthly index-return time-series in the time-period from January 1985 till December 1998 from real estate investment companies as well as common stocks and bonds in Germany, France, Switzerland, Great Britain and the USA were used. We utilize, due to the critical normal distribution assumption, a mean/lower-partial-moment framework. In order to take into account the influence of the currency risk for international investments the analyses have been undertaken both with as well as without hedging the currency risk. We take the viewpoint of a German as well as that of a US-investor to gain insight into the dependency of the diversification potential on the reference currency of the investor.
Access to loans and other financial services is extremely valuable for micro-, small- and medium-sized enterprises in developing and transition countries as it enables their owners as well as their employees to exploit their economic potential and to increase their income. Although this insight has lead development aid institutions to undertake many attempts to create sustainable microfinance institutions, only a small fraction of these has been successful so far. This article analyses what determines the success of attempts to provide financial services in general, and credit in particular, to low income target groups in these countries. We argue that it is crucial to understand, and to mitigate or even eliminate in practice, the serious and numerous incentive problems at the level of the lending operations as well as those at the levels of the human resource management and the governance of microfinance institutions. We attempt to show moreover, that unsolved incentive problems at only one level will ultimately undermine any potential success at the other levels. In our paper, we first analyse information and incentive problems from a theoretical perspective, using and extending the well-known Stiglitz-Weiss model of credit rationing, and derive theoretical requirements for solutions of these problems. In the light of these considerations, we then discuss how problems are solved in practice. Section 3 deals with the credit relationship. Section 4 extends the argument by showing how incentive problems within the institution can be handled, and section 5 analyses corporate governance-related problems of development finance institutions as incentive problems. In section 6 it is demonstrated why, and how, the incentive problems at the different levels, as well as their solutions, are interrelated. From this we derive the proposition that, as the institutional devices for dealing with these problems constitute a complementary system, any sustainable solution requires consistent arrangements of all elements and at all levels of the system. In the last section we will show the potential of strategic networks to set up institutions which we consider to be consistent systems for successfully solving the problems at all three levels simultaneously.
Insider trading and portfolio structure in experimental asset markets with a long lived asset
(1997)
We report results of a series of nine market experiments with asymmetric information and a fundamental value process that is more "realistic" than those in previous experiments. Both a call market institution and a continuous double auction mechanism are employed. We find considerable pricing inefficiencies that are only partially exploited by insiders. The magnitude of insider gains is analyzed separately for each experiment. We find support for the hypothesis that the continuous double auction leads to more efficient outcomes. Finally, we present evidence of an endowment effect: the initial portfolio structure influences the final asset holdings of experimental subjects.
During the last years issues of strategic management accounting have received widespread attention in the accounting literature. Yet the conceptual foundation of most proposals is not clear. This paper presents a theoretical analysis of one of the most prominent approaches of strategic management accounting, i.e., Target Costing. First, the relationship between Target Costing and Life-Cycle-Costing is shown. Secondly, a model based on a mechanism-design-approach is used to answer the question of whether the „Market-into-Company“-method of Target Costing can somehow be endogenized. The model captures problems of asymmetric information, price policy and cost structures (i.e. learning effects etc.). The analysis shows that the more „strategic“ is the firm´s cost function, the less valid is „strategic“ management accounting in terms of the usual way Target Costing is employed.
The main argument in this paper is that new information and communication technologies (ICT) in the financial industry will increase specialisation and competition within the European financial centre system and thereby lead to a ‘re-bundling’ of functions of the various financial centres. Frankfurt plays an interesting role in this development as it is one of the main development centres for ‘financial technology’. With these technologies, remote access to the Frankfurt stock exchange and inter-bank payment system is now feasible from most European cities. This leads to a reduced need for physical presence, which opens up new possibilities for the financial sector’s spatial organisation. However, as financial production is information- and knowledge-intensive, spatial and other types of proximity between financial actors and clients are still essential in many stages. We examine the value chains of three different products (advisory, lending, trading) with regard to different proximities, in order to identify possible patterns of their spatial (re)organisation. From these findings, inferences are drawn for a ‘new’ role for Frankfurt in the European financial centre system.