We study how learning affects an uninformed monopolist's supply and investment decisions under multiplicative uncertainty in demand. The monopolist is uninformed because it does not know one of the parameters defining the distribution of the random demand. Observing prices reveals this...

We address the question of designing dynamic menus to sell experience goods. A dynamic menu consists of a set of price-quantity pairs in each period. The quality of the product is initially unknown, and more information is generated through experimentation. The amount of information in the...

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...

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...

This paper presents a novel take on the effect of uncertainty on investor learning about managerial skills by examining the fund flow-performance relationship in ESG rated funds in the context of climate uncertainty. Utilizing a large sample of mutual funds domiciled in Australia and New Zealand...

We propose and find that aggregating a small number of earnings signals from highly macroeconomically exposed firms yields an informative leading indicator of future GDP. This challenges the convention of defining aggregate earnings using a comprehensive set of public earnings signals. Our...

We examine whether earnings forecasts of sell-side equity analysts are influenced by the forecasts of other analysts on other firms in the analyst portfolio. We find that analysts exhibit “social learning” where analyst optimism is negatively correlated with the recent forecast errors among...

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...

Introduction and Excel Basics -- Blockchain (I): Numbers and Alphanumeric -- Blockchain (II): ASCII and Sha256 -- Ledge and Distributed Ledger -- Cryptography Basics: public and private keys -- Advanced Cryptography -- Cryptocurrency and Ganache -- Crypto markets, risk and risk-return tradeoff...

This paper investigates the design of incentives in a dynamic adverse selection framework when agents’ production technologies display learning effects and agents’ rate of learning is private knowledge. In a simple two-period model with full commitment available to the principal, we show...