Chemical discovery as belief revision

In this paper we describe STAHLp, a system that constructs componential models of chemical substances. STAHLp is a descendent of Zytkow and Simon's (1986) STAHL system, and both use chemical reactions and known componential models in order to construct new chemical models. However, STAHLp employs a more unified and effective strategy for recovering from erroneous inferences, based partly on de Kleer's (1984) assumption-based method of belief revision. This involves recording the underlying source beliefs or premises which lead to each inferred reaction or model. Where Zytkow and Simon's system required multiple methods for detecting errors and recovering from them, STAHLp uses a more powerful representation and additional rules which allow a unified method for error detection and recovery. When given the same initial data, the new system constructs the same historically correct models as STAHL, but it has other capabilities as well. In particular, STAHLp can modify data it has been given if this is necessary to achieve consistent models, and then proceed to construct new models based on the revised data

Cross-listing, price discovery and the informativeness of the trading process

This paper analyzes the price discovery process of a set of Spanish stocks cross-listed at the NYSE. Our methodology distinguishes between two sources of information asymmetries. Market-specific information that is revealed through the trading process and public disclosures simultaneously revealed to both markets but subject to informed judgments. We compute the information share of the Spanish and U.S. trading activity during the daily 2-hour overlapping interval. Empirical results show that the NYSE contribution to the price discovery process is not negligible. But the NYSE information is basically trade-unrelated

Measuring market liquidity: An introductory survey

Asset liquidity in modern financial markets is a key but elusive concept. A market is often said to be liquid when the prevailing structure of transactions provides a prompt and secure link between the demand and supply of assets, thus delivering low costs of transaction. Providing a rigorous and empirically relevant definition of market liquidity has, however, provided to be a difficult task. This paper provides a critical review of the frameworks currently available for modelling and estimating the market liquidity of assets. We consider definitions that stress the role of the bid-ask spread and the estimation of its components that arise from alternative sources of market friction. In this case, intra-daily measures of liquidity appear relevant for capturing the core features of a market, and for their ability to describe the arrival of new information to market participants