Starting from the twelve distinct risk factors in four well-established asset pricing models, a pool we refer to as the winners, we construct and compare 4,095 asset pricing models and find that the model with the risk factors, Mkt, SMB, MOM, ROE, MGMT, and PEAD, performs the best in terms of...

The erosion of high-end fashion brands by fast fashion copycats (e.g., Zara, H&M) has provoked ongoing controversies and unceasing legal attempts to copyright fashion designs. Despite this tension around the enforcement of copyrights and the purported negative impact of copycats, the effect of...

The expansion of marketing data is encouraging the growing use of deep learning in marketing. I summarize the intuition behind deep learning and explain the mechanisms of six popular algorithms: three discriminative (CNN, RNN, and Transformer), two generative (VAE and GAN), and one RL (DQN). I...

To mitigate global climate change and achieve the targets of the Nationally Determined Contributions (NDCs), the Chinese government implemented a carbon emission trading scheme (ETS) pilot policy in batches. However, there has been no unified consensus at present on whether the ETS pilot policy...

Machine learning is bringing us self-driving cars, medical diagnoses, and language translation, but how can machine learning help marketers improve marketing decisions? Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to analyze rich media...

Accurate forecasting of sales/consumption is particularly important for marketing because this information can be used to adjust marketing budget allocations and overall marketing strategies. Recently, online social platforms have produced an unparalleled amount of data on consumer behavior....