In the feld of empirical asset pricing, the challenges of high dimensionality, non-linear relationships, and interaction efects have led to the increasing popularity of machine learning (ML) methods. This study investigates the performance of ML methods when predicting diferent measures of stock...

"The demand for durable goods is more cyclical than that for nondurable goods and services. Consequently, the cash flow and stock returns of durable-good producers are exposed to higher systematic risk. Using the NIPA input-output tables, we construct portfolios of durable-good, nondurable-good,...

The demand for durable goods is more cyclical than that for nondurable goods and services. Consequently, the cash flows and stock returns of durable-good producers are exposed to higher systematic risk. Using the benchmark input-output accounts of the National Income and Product Accounts, we...

The demand for durable goods is more cyclical than that for nondurable goods and services. Consequently, the cash flows and stock returns of durable-good producers are exposed to higher systematic risk. Using the benchmark input-output accounts of the National Income and Product Accounts, we...

Using the Michigan Survey of Consumers, we provide evidence that consumers' beliefs about current and future aggregate durable expenditure predict expected returns. We rationalize this finding through an asset pricing model with recursive preferences over non-durable and durable goods and belief...