Online ratings play an important role in many markets. However, how fast they can reveal seller types remains unclear. To study this question, we propose a new model in which a buyer learns about the seller’s type from previous ratings and her own experience and rates the seller if she learns...

With the advent of big data, unique opportunities arise for data collection and analysis and thus for personalized pricing. We simulate a self-learning algorithm setting personalized prices based on additional information about consumer sensitivities in order to analyze market outcomes for...

Two factors have proven to be strongly relevant for the subprime mortgage crisis. The first is the lack of screening incentives of originators, which had not been anticipated by investors. The second is that investors relied too much on credit ratings. We examine whether investors have learned...

Because uncertainty is high in bad times, investors find it harder to assess firm prospects and, hence, should value analyst output more. However, higher uncertainty makes analysts' tasks harder so it is unclear if analyst output is more valuable in bad times. We find that, in bad times, analyst...

We review the recent literature on the financing of innovation, inclusive of large companies and new startups. This research strand has been very active over the past five years, generating important new findings, questioning some long-held beliefs, and creating its own puzzles. Our review...

When the market undergoes a learning process about a new issue, it takes time for the aggregate demand to converge to the equilibrium consistent with the stock's underlying fundamentals. As a result, the early market demand can deviate significantly from the sustainable demand. This problem...

Classical statistics (e.g., Econometrics) relies on assumptions that are often unrealistic in finance. Two critical assumptions are that the researcher has perfect knowledge about the model's specification, and that the researcher knows all the variables involved in a phenomenon (including all...

This paper will give a brief overview of the work of introducing machine learning intelligence in the Kineta e-markets system, to facilitate auto-hedging, smart price engine algorithms and proprietary automatic positioning within the foreign exchange market. In this paper we will give a brief...

More information about a firm should lead to a more precise valuation. As more publicly available information accumulates after a firm's initial public offering (IPO), valuations should become both easier to carry out and more precise. We examine how this declining valuation uncertainty affects...

Leveraging the detailed project-level data on biotech startups and their IPO records, this paper studies how adverse selection in capital markets affects financing decisions of entrepreneurs and firm values. By structurally estimating a dynamic model that features strategic experimentation and...