In many service industries, the firm adjusts the product price dynamically by taking into account the current product inventory and the future demand distribution. Because the firm can easily monitor the product inventory, the success of dynamic pricing relies on an accurate demand forecast. In this paper, we consider a situation where the firm does not have an accurate demand forecast, but can...

Forecast sharing in a supply chain using linear price contracts often leads to inefficiencies as the buyer has an incentive to inflate demand forecasts to ensure sufficient supply. Recent research in supply chain contracting has focused on one-shot relationships, and has identified various contracts that align incentives in the supply chain and induce the buyer to reveal forecast information tr...

Equity analysts’ target price can be decomposed into two components: the earnings forecast and the price-to-earnings (P/E) ratio forecast, with the former containing shortterm earnings news and the latter containing news about long-term earnings growth and discount rates. Using a large database of target prices from 1997 to 2004, we document that both components are important in driving target ...

This paper focuses on forecasting the price of Bitcoin, motivated by its market growth and recent interest participants academics. We deploy six machine learning algorithms (e.g., Artificial Neural Network, Support Vector Machine, Random Forest, k-Nearest Neighbours, AdaBoost, Ridge regression), without deciding a priori which one is ‘best’ model. The main contribution to use these data analyti...

We study supply chain contracting with investment in demand forecasting under downstream competition. Supporting some recent industry observations, we show that under common pricing schemes, such as wholesale price or two-part tariff, downstream firms overinvest in demand forecasting. Analyzing the bounds and determinants of overinvestment, we demonstrate that the wholesale price and two-part t...