Refine
Year of publication
Institute
- Fachbereich Wirtschaftswissenschaften (205) (remove)
Has Fulltext
- no (205) (remove)
Language
- English (205) (remove)
Document Type
- Article (114)
- Conference Proceeding (42)
- Book (32)
- Part of a Book (14)
- Working Paper (2)
- Doctoral Thesis (1)
Keywords
- rebound-effect (2)
- sustainability (2)
- Active learning (1)
- Bank-issued Warrants (1)
- Brands (1)
- Business Models (1)
- Business Process Intelligence (1)
- Case Study (1)
- Challenges (1)
- Change (1)
- Clinical decision support systems (1)
- Consensus (1)
- Cross-platform (1)
- Deep learning (1)
- Discourse ethics (1)
- Disposition Effect (1)
- Evaluation (1)
- Explainability (1)
- Feature selection (1)
- Finland (1)
- Gamification (1)
- Germany (1)
- Guidelines (1)
- Human Development Index (1)
- IT Products (1)
- Individual Investors (1)
- Instagram store (1)
- Instructional design (1)
- Justice (1)
- Latvia (1)
- Leaderboard (1)
- Luxury (1)
- Measurement models (1)
- Measurement uncertainty (1)
- Medical AI (1)
- Mobile web (1)
- Modelling (1)
- Natural Language Processing (1)
- Natural language processing (1)
- Negative Feedback Trading (1)
- Normative standards (1)
- Operations (1)
- PLS (1)
- PWA (1)
- Process Model Extraction (1)
- Process mining (1)
- Product Management (1)
- Progressive Web App (1)
- Query learning (1)
- Reproducible research (1)
- Requirements prioritization (1)
- Requirements relations (1)
- SME (1)
- SSE) JEL : O33 (1)
- Software development (1)
- Software testing (1)
- Strategic Business Planning (1)
- Text Mining (1)
- Tool support (1)
- Trading Behavior (1)
- automotive (1)
- business culture (1)
- change (1)
- climate change (1)
- competence developing games (1)
- corporate sustainability (1)
- critical (1)
- digital twin (1)
- efficiency side-effects (1)
- entrepreneurship education (1)
- eye movement modelling examples (1)
- grey energy (1)
- industry 4.0 (1)
- jevons paradox (1)
- literature (1)
- management (1)
- marketing (1)
- motivation (1)
- purchase factor (1)
- requirements (1)
- resource abundance (1)
- review (1)
- shopping behavior (1)
- socio-economic welfare (1)
- software engineering (1)
- structural equation model (1)
- systematic (1)
- systematic literature review (1)
- video learning (1)
The construction of a statistical test is investigated which is based only on “reliability” and “precision” as quality criteria. The reliability of a statistical test is quantifiedin a straightforward way by the probability that the decision of the test is correct. However, the quantification of the precision of a statistical test is not at all evident. Thereforethe paper presents and discusses several approaches. Moreover the distinction of “nullhypothesis” and “alternative hypothesis” is not necessary any longer.
This paper investigates the extent to which corporate governance affects the cost of debt and equity capital of German exchange-listed companies. I examine corporate governance along three dimensions: financial information quality, ownership structure and board structure. The results suggest that firms with high levels of financial transparency and bonus compensations face lower cost of equity. In addition, block ownership is negatively related to firms' cost of equity when the blockholders are other firms, managers or founding-family members. Consistent with the conjecture that agency costs increase with firm size, I find significant cost of debt effects only in the largest German companies. Here, the creditors demand lower cost of debt from firms with block ownerships held by corporations or banks. My findings demonstrate that a uniform set of governance attributes is unlikely to satisfy suppliers of debt and equity capital equally.
Bitcoin is a cryptocurrency and is considered a high-risk asset class whose price changes are difficult to predict. Current research focusses on daily price movements with a limited number of predictors. The paper at hand aims at identifying measurable indicators for Bitcoin price movements and the development of a suitable forecasting model for hourly changes. The paper provides three research contributions. First, a set of significant indicators for predicting the Bitcoin price is identified. Second, the results of a trained Long Short-term Memory (LSTM) neural network that predicts price changes on an hourly basis is presented and compared with other algorithms. Third, the results foster discussions of the applicability of neural nets for stock price predictions. In total, 47 input features for a period of over 10 months could be retrieved to train a neural net that predicts the Bitcoin price movements with an error rate of 3.52 %.