The collapse of an investment mania usually reminds people that the phrase "This time is different" is dangerous. Recollections of this mantra then typically either state outright or at least imply that "It is never different." However, there is at least one counterexample to this cautious view,...

In this paper we use the tools and frameworks from Oxford University’s postgraduate diploma in financial strategy to study the performance and benefits of algorithmic trading strategies (algos), and specifically those that use artificial intelligence (AI) and machine learning (ML).We discover...

Retail investors, on average, are known to be less informed. The democratized access to big financial data enabled by recent technological advances has the potential to make them better informed. At the same time, behavioral finance and economic theories postulate that such unprecedented access...

We create a firm-level ChatGPT investment score, based on conference calls, that measures managers' anticipated changes in capital expenditures. We validate the score with interpretable textual content and its strong correlation with CFO survey responses. The investment score predicts future...

Among the ecosystem of decentralized financial services, yield farming is a complex investment strategy with hidden downside risks providing opportunities for passively earning income. We characterize the risk and return characteristics of yield farming and show that yield farms dynamically...

On the basis of empirical data for the Swiss market this paper confirms the hypothesis that the lower direct costs of online trading (brokerage) are cancelled out by higher indirect costs (in the form of information processing costs). In addition, the report provides evidence that during the...

Bayesian learning provides the core concept of processing noisy information. In standard Bayesian frameworks, assessing the price impact of information requires perfect knowledge of news' precision. In practice, however, precision is rarely dis- closed. Therefore, we extend standard Bayesian...

Bayesian learning provides a core concept of information processing in financial markets. Typically it is assumed that market participants perfectly know the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning...

Despite a large and growing theoretical literature on flights to safety, there does not appear to exist an empirical characterization of flight-to-safety (FTS) episodes. Using only data on bond and stock returns, we identify and characterize flight to safety episodes for 23 countries. On...

Bayesian learning provides a core concept of information processing in financial markets. Typically it is assumed that market participants perfectly know the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning...