The energy sector will undergo fundamental changes over the next ten years. Prices for fossil energy resources are continuously increasing, there is an urgent need to reduce CO2 emissions, and the United States and European Union are strongly motivated to become more independent from foreign...

The trust-free nature of blockchain-based systems challenges the role of traditional platform providers and enables the creation of new, intermediary-free markets. Despite the growing number of such markets, the impact of the blockchain's configuration on market outcomes remains unclear. In this...

Despite a growing interest, researchers and practitioners still struggle to transfer the blockchain concept introduced by Bitcoin to market-oriented application scenarios. To shed light on the technology's usage in markets with asymmetric information, this study analyzes the effect of the...

We employ and analyze various machine learning models for daily cryptocurrency market prediction and trading. We train the models to predict binary relative daily market movements of the 100 largest cryptocurrencies. Our results show that all employed models make statistically viable...

We analyze the predictability of the bitcoin market across prediction horizons ranging from 1 to 60 min. In doing so, we test various machine learning models and find that, while all models outperform a random classifier, recurrent neural networks and gradient boosting classifiers are especially...

We study the trading behavior of retail investors in the market of leveraged bank-issued retail derivatives designed to trade excessively, speculate and gamble on ongoing trends and market movements. We analyze whether retail investors have private information and benefit disproportionately or...